This release is not done yet.
- Python3.5: Coroutine methods using
super
were crashing the compiler. Issue#340. Fixed in 0.5.24.2 already. - Python3.3: Generator return values were properly transmitted in case of
tuple
orStopIteration
values. - Python3.5: Better interoperability between compiled coroutines and uncompiled generator coroutines.
- Python3.5: Added support to compile in Python debug mode under Windows too.
- Generators with arguments were using two code objects, one with, and one
without the
CO_NOFREE
flag, one for the generator object creating function, and one for the generator object. - Python3.5: The duplicate code objects for generators with arguments lead to interoperability issues with between such compiled generator coroutines and compiled coroutines. Issue#341. Fixed in 0.5.24.2 already.
- Standalone: On some Linux variants, e.g. Debian Stretch and Gentoo, the linker
needs more flags to really compile to a binary with
RPATH
.
- Added dedicated
xrange
built-in implementation for Python2 andrange
for Python3. This makes these slightly faster while also solving ordering problems when creating constants of these types. - Faster
sum
again, using quick iteration interface and specialized quick iteration code for typical standard type containers,tuple
andlist
. - Compiled generators were making sure
StopIteration
was set after their iteration, although most users were only going to clear it. Now only thesend
method, which really needs that does it. This speed up the closing of generators quite a bit.
- This release also prepares Python 3.6 support, it includes full language support on the level of CPython 3.6.0b4.
- Added repository for Ubuntu Yekkety (16.10) for download.
- Windows: Added support to detect and to switch debug Python where available to also be able to execute reference counting tests.
The quick iteration is a precursor to generally faster iteration over unknown
object iterables. Expanding this to general code generation, and not just the
sum
built-in, might yield significant gains for normal code in the future.
This release is again focusing on optimization, this time very heavily on the generator performance, which was found to be much slower than CPython for some cases. Also there is the usual compatibility work and improvements for Pure C support.
- Windows: The 3.5.2 coroutine new protocol implementation was using the wrapper from CPython, but it's not part of the ABI on Windows. Have our own instead. Fixed in 0.5.23.1 already.
- Windows: Fixed second compilation with MSVC failing. The files renamed to be C++ files already existed, crashing the compilation. Fixed in 0.5.23.1 already.
- Mac OS: Fixed creating extension modules with
.so
suffix. This is now properly determined by looking at the importer details, leading to correct suffix on all platforms. Fixed in 0.5.23.1 already. - Debian: Don't depend on a C++ compiler primarily anymore, the C compiler from GNU or clang will do too. Fixed in 0.5.23.1 already.
- Pure C: Adapted scons compiler detecting to properly consider C11 compilers from the environment, and more gracefully report things.
- Python2: Generators were saving and restoring exceptions, updating the variables
sys.exc_type
for every context switch, making it really slow, as these are 3 dictionary updates, normally not needed. Now it's only doing it if it means a change. - Sped up creating generators, coroutines and coroutines by attaching the closure
variable storage directly to the object, using one variable size allocation, instead
of two, once of which was a standard
malloc
. This makes creating them easier and avoids maintaining the closure pointer entirely. - Using dedicated compiled cell implementation similar to
PyCellObject
but fully under our control. This allowed for smaller code generated, while still giving a slight performance improvement. - Added free list implementation to cache generator, coroutines, and function objects, avoiding the need to create and delete this kind of objects in a loop.
- Added support for the built-in
sum
, making slight optimizations to be much faster when iterating over lists and tuples, as well as fastlong
sum for Python2, and much fasterbool
sums too. This is using a prototype version of a "qiter" concept. - Provide type shape for
xrange
calls that are not constant too, allowing for better optimization related to those.
- Added workarounds for locks being held by Virus Scanners on Windows to our test runner.
- Enhanced constructs that test generator expressions to more clearly show the actual construct cost.
- Added construct tests for the
sum
built-in on verious types ofint
containers, making sure we can do all of those really fast.
This release improves very heavily on generators in Nuitka. The memory allocator is used more cleverly, and free lists all around save a lot of interactions with it. More work lies ahead in this field, as these are not yet as fast as they should be. However, at least Nuitka should be faster than CPython for these kind of usages now.
Also, proper pure C in the Scons is relatively important to cover more of the rarer use cases, where the C compiler is too old.
The most important part is actually how sum
optimization is staging a new
kind of approach for code generation. This could become the standard code for
iterators in loops eventually, making for
loops even faster. This will be
for future releases to expand.
This release is focusing on optimization, the most significant part for the users being enhanced scalability due to memory usage, but also break through structural improvements for static analysis of iterators and the debut of type shapes and value shapes, giving way to "shape tracing".
Fix support Python 3.5.2 coroutine changes. The checks got added for improved mode for older 3.5.x, the new protocol is only supported when run with that version or higher.
Fix, was falsely optimizing away unused iterations for non-iterable compile time constants.
iter(1) # needs to raise.
Python3: Fix,
eval
must not attempt tostrip
memoryviews. The was preventing it from working with that type.Fix, calling
type
without any arguments was crashing the compiler. Also the exception raised for anything but 1 or 3 arguments was claiming that only 3 arguments were allowed, which is not the compatible thing.Python3.5: Fix, follow enhanced error checking for complex call handling of star arguments.
Compatibility: The
from x import x, y
re-formulation was doing two__import__
calls instead of re-using the module value.
Uses only about 66% of the memory compared to last release, which is very important step for scalability independent of re-loading. This was achieved by making sure to break loop traces and their reference cycle when they become unused.
Properly detect the
len
of multiplications at compile time from newly introduces value shapes, so that this is e.g. statically optimized.print(len("*" * 10000000000))
Due to newly introduced type shapes,
len
anditer
now properly detect more often if values will raise or not, and warn about detected raises.iter(len((something)) # Will always raise
Due to newly introduced "iterator tracing", we can now properly detect if the length of an unpacking matches its source or not. This allows to remove the check of the generic re-formulations of unpackings at compile time.
a, b = b, a # Will never raise due to unpacking a, b = b, a, c # Will always raise, 3 items cannot unpack to 2
Added support for optimization of the
xrange
built-in for Python2.Python2: Added support for
xrange
iterable constant values, pre-building those constants ahead of time.Python3: Added support and
range
iterable constant values, pre-building those constants ahead of time. This brings optimization support for Python3 ranges to what was available for Python2 already.Avoid having a special node variange for
range
with no arguments, but create the exception raising node directly.Specialized constant value nodes are using less generic implementations to query e.g. their length or iteration capabilities, which should speed up many checks on them.
Added support for the
format
built-in.Python3: Added support for the
ascii
built-in.
- The movement to pure C got the final big push. All C++ only idoms of C++ were removed, and everything works with C11 compilers. A C++03 compiler can be used as a fallback, in case of MSVC or too old gcc for instance.
- Using pure C, MinGW64 6x is now working properly. The latest version had
problems with
hypot
related changes in the C++ standard library. Using C11 solves that. - This release also prepares Python 3.6 support, it includes full language support on the level of CPython 3.6.0b1.
- The CPython 3.6 test suite was run with Python 3.5 to ensure bug level compatibility, and had a few findings of incompatibilities.
- The last holdouts of classes in Nuitka were removed, and many idioms of C++ were stopped using.
- Moved range related helper functions to a dedicated include file.
- Using
str is not bytes
to detect Python3str
handling or actualbytes
type existence. - Trace collections were using a mix-in that was merged with the base class that every user of it was having.
- Added more static optimization tests, a lot more has become feasible to decide at run time, and is now done. These are to detect regressions in that domain.
- The CPython 3.6 test suite is now also run with CPython 3.5 which found some incompatibilities.
This release marks a huge step forward. We are having the structure for type inference now. This will expand in coming releases to cover more cases, and there are many low hanging fruits for optimization. Specialized codes for variable versions of certain known shapes seems feasible now.
Then there is also the move towards pure C. This will make the backend compilation lighter, but due to using C11, we will not suffer any loss of convinience compared to "C-ish". The plan is to use continue to use C++ for compilation for compilers not capable of supporting C11.
The amount of static analysis done in Nuitka is now going to quickly expand, with more and more constructs predicted to raise errors or simplified. This will be an ongoing activity, as many types of expressions need to be enhanced, and only one missing will not let it optimize as well.
Also, it seems about time to add dedicated code for specific types to be as
fast as C code. This opens up vast possibilities for acceleration and will
lead us to zero overhead C bindings eventually. But initially the drive is
towards enhanced import
analysis, to become able to know the precide module
expected to be imported, and derive type information from this.
The coming work will attack to start whole program optimization, as well as enhanced local value shape analysis, as well specialized type code generation, which will make Nuitka improve speed.
This release is mostly an intermediate release on the way to the large goal of having per module compilation that is cachable and requires far less memory for large programs. This is currently in progress, but required many changes that are in this release, more will be needed.
It also contains a bunch of bug fixes and enhancements that are worth to be released, and the next changes are going to be more invasive.
- Compatibility: Classes with decorated
__new__
functions could miss out on thestaticmethod
decorator that is implicit. It's now applied always, unless of course it's already done manually. This corrects an issue found with Pandas. Fixed in 0.5.22.1 already. - Standalone: For at least Python 3.4 or higher, it could happen that the locale needed was not importable. Fixed in 0.5.22.1 already.
- Compatibility: Do not falsely assume that
not
expressions cannot raise on boolean expressions, since those arguments might raise during creation. This could lead to wrong optimization. Fixed in 0.5.22.2 already. - Standalone: Do not include system specific C libraries in the distribution created. This would lead to problems for some configurations on Linux in cases the glibc is no longer compatible with newer oder older kernels. Fixed in 0.5.22.2 already.
- The
--recurse-directory
option didn't check with decision mechanisms for module inclusion, making it impossible to avoid some things.
- Introduced specialized constant classes for empty dictionaries and other special constants, e.g. "True" and "False", so that they can have more hard coded properties and save memory by sharing constant values.
- The "technical" sharing of a variable is only consider for variables that had some sharing going in the first place, speeing things up quite a bit for that still critical check.
- Memory savings coming from enhanced trace storage are already visible at about 1%. That is not as much as the reloading will mean, but still helpful to use less overall.
- The global variable registry was removed. It was in the way of unloading and reloading modules easily. Instead variables are now attached to their owner and referenced by other users. When they are released, these variables are released.
- Global variable traces were removed. Instead each variable has a list of the traces attached to it. For non-shared variables, this allows to sooner tell attributes of those variables, allowing for sooner optimization of them.
- No longer trace all initial users of a variable, just merely if there were such and if it constitutes sharing syntactically too. Not only does this save memory, it avoids useless references of the variable to functions that stop using it due to optimization.
- Create constant nodes via a factory function to avoid non-special instances where variants exist that would be faster to use.
- Moved the C string functions to a proper
nuitka.utils.CStrings
package as we use it for better code names of functions and modules. - Made
functions
and explicit child node of modules, which makes their use more generic, esp. for re-loading modules. - Have a dedicated function for building frame nodes, making it easier to see where they are created.
This release is the result of a couple of months work, and somwhat means that proper re-loading of cached results is becoming in sight. The reloading of modules still fails for some things, and more changes will be needed, but with that out of the way, Nuitka's footprint is about to drop and making it then absolutely scalable. Something considered very important before starting to trace more information about values.
This next thing big ought to be one thing that structurally holds Nuitka back from generating C level performance code with say integer operations.
This release focused on scalability work. Making Nuitka more usable in the common case, and covering more standalone use cases.
- Windows: Support for newer MinGW64 was broken by a workaround for older MinGW64 versions.
- Compatibility: Added support for the (inofficial) C-Python API
Py_GetArgcArgv
that was causingprctl
module to fail loading on ARM platforms. - Compatibility: The proper error message template for complex call arguments is now detected as compile time. There are changes comming, that are already in some pre-releases of CPython.
- Standalone: Wasn't properly ignoring
Tools
and other directories in the standard library.
- Windows: Detect the MinGW compiler arch and compare it to the Python arch. In case of a mismatch, the compiler is not used. Otherwise compilation or linking gives hard to understand errors. This also rules out MinGW32 as a compiler that can be used, as its arch doesn't match MinGW64 32 bits variant.
- Compile modules in two passes with the option to specify which modules will be considered for a second pass at all (compiled without program optimization) or even become bytecode.
- The developer mode installation of Nuitka in
develop
mode with the commandpip install -e nuitka_git_checkout_dir
is now supported too.
- Popular modules known to not be performance relevant are no longer C compiled,
e.g.
numpy.distutils
and many others frequently imported (from some other module), but mostly not used and definitely not performance relevant.
- The progress tracing and the memory tracing and now more clearly separate and therefore more readable.
- Moved RPM related files to new
rpm
directory. - Moved documentation related files to
doc
directory. - Converted import sorting helper script to Python and made it run fast.
- The Buildbot infrastructure for Nuitka was updated to Buildbot 0.8.12 and is now maintained up to date with Ansible.
- Upgraded the Nuitka bug tracker to Roundup 1.5.1 to which I had previously contributed security fixes already active.
- Added SSL certificates from Let's Encrypt for the web server.
This release advances the scalability of Nuitka somewhat. The two pass approach does not yet carry all possible fruits. Caching of single pass compiled modules should follow for it to become consistently fast.
More work will be needed to achieve fast and scalable compilation, and that is going to remain the focus for some time.
This release is mostly about catching up with issues. Most address standalone problems with special modules, but there are also some general compatibility corrections, as well as important fixes for Python3.5 and coroutines and to improve compatibility with special Python variants like AnaConda under the Windows system.
- Standalone Python3.5: The
_decimal
module at least is using a__name__
that doesn't match the name at load time, causing programs that use it to crash. - Compatibility: For Python3.3 the
__loader__
attribute is now set in all cases, and it needs to have a__module__
attribute. This makes inspection as done by e.g.flask
working. - Standalone: Added missing hidden dependencies for
Tkinter
module, adding support for this to work properly. - Windows: Detecting the Python DLL and EXE used at compile time and preserving this information use during backend compilation. This should make sure we use the proper ones, and avoids hacks for specific Python variants, enhancing the support for AnaConda, WinPython, and CPython installations.
- Windows: The
--python-debug
flag now properly detects if the run time is supporting things and error exits if it's not available. For a CPython3.5 installation, it will switch between debug and non-debug Python binaries and DLLs. - Standalone: Added plug-in for the
Pwm
package to properly combine it into a single file, suitable for distribution. - Standalone: Packages from standard library, e.g.
xml
now have proper__path__
as a list and not as a string value, which breaks code of e.g. PyXML. Issue#183. - Standalone: Added missing dependency of
twisted.protocols.tls
. Issue#288. - Python3.5: When finalizing coroutines that were not finished, a corruption of its reference count could happen under some circumstances.
- Standalone: Added missing DLL dependency of the
uuid
module at run time, which uses ctypes to load it.
- Added support for AnaConda Python on this Linux. Both accelerated and standalone mode work now. Issue#295.
- Added support for standalone mode on FreeBSD. Issue#294.
- The plug-in framework was expanded with new features to allow addressing some specific issues.
- Moved memory related stuff to dedicated utils package
nuitka.utils.MemoryUsage
as part of an effort to have more topical modules. - Plug-ins how have a dedicated module through which the core accesses the API, which was partially cleaned up.
- No more "early" and "late" import detections for standalone mode. We now scan everything at the start.
This release focused on expanding plugins. These were then used to enhance the success of standalone compatibility. Eventually this should lead to a finished and documented plug-in API, which will open up the Nuitka core to easier hacks and more user contribution for these topics.
This release brings optimization improvements for dictionary using code. This is now lowering subscripts to dictionary accesses where possible and adds new code generation for known dictionary values. Besides this there is the usual range of bug fixes.
- Fix, attribute assignments or deletions where the assigned value or the attribute source was statically raising crashed the compiler.
- Fix, the order of evaluation during optimization was considered in the wrong order for attribute assignments source and value.
- Windows: Fix, when
g++
is the path, it was not used automatically, but now it is. - Windows: Detect the 32 bits variant of MinGW64 too.
- Python3.4: The finalize of compiled generators could corrupt reference counts for shared generator objects. Fixed in 0.5.18.1 already.
- Python3.5: The finalize of compiled coroutines could corrupt reference counts for shared generator objects.
When a variable is known to have dictionary shape (assigned from a constant value, result of
dict
built-in, or a general dictionary creation), or the branch merge thereof, we lower subscripts from expecting mapping nodes to dictionary specific nodes. These generate more efficient code, and some are then known to not raise an exception.def someFunction(a,b): value = {a : b} value["c"] = 1 return value
The above function is not yet fully optimized (dictionary key/value tracing is not yet finished), however it at least knows that no exception can raise from assigning
value["c"]
anymore and creates more efficient code for the typicalresult = {}
functions.The use of "logical" sharing during optimization has been replaced with checks for actual sharing. So closure variables that were written to in dead code no longer inhibit optimization of the then no more shared local variable.
Global variable traces are now faster to decide definite writes without need to check traces for this each time.
- No more using "logical sharing" allowed to remove that function entirely.
- Using "technical sharing" less often for decisions during optimization and instead rely more often on proper variable registry.
- Connected variables with their global variable trace statically avoid the need to check in variable registry for it.
- Removed old and mostly unused "assume unclear locals" indications, we use global variable traces for this now.
This release aimed at dictionary tracing. As a first step, the value assign is now traced to have a dictionary shape, and this this then used to lower the operations which used to be normal subscript operations to mapping, but now can be more specific.
Making use of the dictionary values knowledge, tracing keys and values is not yet inside the scope, but expected to follow. We got the first signs of type inference here, but to really take advantage, more specific shape tracing will be needed.
This release mainly has a scalability focus. While there are few compatibility improvements, the larger goal has been to make Nuitka compilation and the final C compilation faster.
Compatibility: The nested arguments functions can now be called using their keyword arguments.
def someFunction(a,(b,c)): return a, b, c someFunction(a = 1, **{".1" : (2,3)})
Compatibility: Generators with Python3.4 or higher now also have a
__del__
attribute, and therefore properly participate in finalization. This should improve their interactions with garbage collection reference cycles, although no issues had been observed so far.Windows: Was outputting command line arguments debug information at program start. Issue#284. Fixed in 0.5.17.1 already.
- Code generated for parameter parsing is now a lot less verbose. Python level loops and conditionals to generate code for each variable has been replaced with C level generic code. This will speed up the backend compilation by a lot.
- Function calls with constant arguments were speed up specifically, as their call is now fully prepared, and yet using less code. Variable arguments are also faster, and all defaulted arguments are also much faster. Method calls are not affected by these improvements though.
- Nested argument functions now have a quick call entry point as well, making them faster to call too.
- The
slice
built-in, and internal creation of slices (e.g. in re-formulations of Python3 slices as subscripts) cannot raise. Issue#262. - Standalone: Avoid inclusion of bytecode of
unittest.test
,sqlite3.test
,distutils.test
, andensurepip
. These are not needed, but simply bloat the amount of bytecode used on e.g. MacOS. Issue#272. - Speed up compilation with Nuitka itself by avoid to copying and constructing variable lists as much as possible using an always accurate variable registry.
- Nested argument functions of Python2 are now re-formulated into a wrapping function that directly calls the actual function body with the unpacking of nested arguments done in nodes explicitly. This allows for better optimization and checks of these steps and potential in-lining of these functions too.
- Unified slice object creation and built-in
slice
nodes, these were two distinct nodes before. - The code generation for all statement kinds is now done via dispatching from
a dictionary instead of long
elif
chains. - Named nodes more often consistently, e.g. all loop related nodes start with
Loop
now, making them easier to group. - Parameter specifications got simplified to work without variables where it is possible.
- Nuitka is now available on the social code platforms gitlab as well.
Long standing weaknesses have been addressed in this release, also quite a few structural cleanups have been performed, e.g. strengthening the role of the variable registry to always be accurate, is groundlaying to further improvement of optimization.
However, this release cycle was mostly dedicated to performance of the actual compilation, and more accurate information was needed to e.g. not search for information that should be instant.
Upcoming releases will focus on usability issues and further optimization, it was nice however to see speedups of created code even from these scalability improvements.
This release is a major feature release, as it adds full support for Python3.5 and its coroutines. In addition, in order to properly support coroutines, the generator implementation got enhanced. On top of that, there is the usual range of corrections.
- Windows: Command line arguments that are unicode strings were not properly working.
- Compatibility: Fix, only the code object attached to exceptions contained all variable names, but not the one of the function object.
- Python3: Support for virtualenv on Windows was using non-portable code and therefore failing. Issue#266.
- The tree displayed with
--display-tree
duplicated all functions and did not resolve source lines for functions. It also displayed unused functions, which is not helpful. - Generators with parameters leaked C level memory for each instance of them leading to memory bloat for long running programs that use a lot of generators. Fixed in 0.5.16.1 already.
- Don't drop positional arguments when called with
--run
, also make it an error if they are present without that option.
- Added full support for Python3.5, coroutines work now too.
- Optimized frame access of generators to not use both a local frame variable and the frame object stored in the generator object itself. This gave about 1% speed up to setting them up.
- Avoid having multiple code objects for functions that can raise and have local variables. Previously one code object would be used to create the function (with parameter variable names only) and when raising an exception, another one would be used (with all local variable names). Creating them both at start-up was wasteful and also needed two tuples to be created, thus more constants setup code.
- The entry point for generators is now shared code instead of being generated for each one over and over. This should make things more cache local and also results in less generated C code.
- When creating frame codes, avoid working with strings, but use proper emission for less memory churn during code generation.
- Updated the key for the Debian/Ubuntu repositories to remain valid for 2 more years.
- Added support for Fedora 23.
- MinGW32 is no more supported, use MinGW64 in the 32 bits variant, which has less issues.
- Detecting function type ahead of times, allows to handle generators different from normal functions immediately.
- Massive removal of code duplication between normal functions and generator functions. The later are now normal functions creating generator objects, which makes them much more lightweight.
- The
return
statement in generators is now immediately set to the proper node as opposed to doing this in variable closure phase only. We can now use the ahead knowledge of the function type. - The
nonlocal
statement is now immediately checked for syntax errors as opposed to doing that only in variable closure phase. - The name of contraction making functions is no longer skewed to empty, but the real thing instead. The code name is solved differently now.
- The
local_locals
mode for function node was removed, it was always true ever since Python2 list contractions stop using pseudo functions. - The outline nodes allowed to provide a body when creating them, although creating that body required using the outline node already to create temporary variables. Removed that argument.
- Removed PyLint false positive annotations no more needed for PyLint 1.5 and solved some TODOs.
- Code objects are now mostly created from specs (not yet complete) which are attached and shared between statement frames and function creations nodes, in order to have less guess work to do.
- Added the CPython3.5 test suite.
- Updated generated doctests to fix typos and use common code in all CPython test suites.
This release continues to address technical debt. Adding support for Python3.5 was the major driving force, while at the same time removing obstacles to the changes that were needed for coroutine support.
With Python3.5 sorted out, it will be time to focus on general optimization again, but there is more technical debt related to classes, so the cleanup has to continue.
This is a maintenance release, largely intended to put out improved support for new platforms and minor corrections. It should improve the speed for standalone mode, and compilation in general for some use cases, but this is mostly to clean up open ends.
Fix, the
len
built-in could give false values for dictionary and set creations with the same element.# This was falsely optimized to 2 even if "a is b and a == b" was true. len({a, b})
Python: Fix, the
gi_running
attribute of generators is no longer anint
, butbool
instead.Python3: Fix, the
int
built-in with two arguments, value and base, raisedUnicodeDecodeError
instead ofValueError
for illegal bytes given as value.Python3: Using
tokenize.open
to read source code, instead of reading manually and decoding fromtokenize.detect_encoding
, this handles corner cases more compatible.Fix, the PyLint warnings plug-in could crash in some cases, make sure it's more robust.
Windows: Fix, the combination of AnaConda Python, MinGW 64 bits and mere acceleration was not working. Issue#254.
Standalone: Preserve not only namespace packages created by
.pth
files, but also make the imports done by them. This makes it more compatible with uses of it in Fedora 22.Standalone: The extension modules could be duplicated, turned this into an error and cache finding them during compile time and during early import resolution to avoid duplication.
Standalone: Handle "not found" from
ldd
output, on some systems not all the libraries wanted are accessible for every library.Python3.5: Fixed support for namespace packages, these were not yet working for that version yet.
Python3.5: Fixes lack of support for unpacking in normal
tuple
,list
, andset
creations.[*a] # this has become legal in 3.5 and now works too.
Now also gives compatible
SyntaxError
for earlier versions. Python2 was good already.Python3.5: Fix, need to reduce compiled functions to
__qualname__
value, rather than just__name__
or else pickling methods doesn't work.Python3.5: Fix, added
gi_yieldfrom
attribute to generator objects.Windows: Fixed harmless warnings for Visual Studio 2015 in
--debug
mode.
- Re-formulate
exec
andeval
to default toglobals()
as the default for the locals dictionary in modules. - The
try
node was making a description of nodes moved to the outside when shrinking its scope, which was using a lot of time, just to not be output, now these can be postponed. - Refactored how freezing of bytecode works. Uncompiled modules are now explicit nodes too, and in the registry. We only have one or the other of it, avoiding to compile both.
- When
strace
ordtruss
are not found, given proper error message, so people know what to do. - The doc tests extracted and then generated for CPython3 test suites were not printing the expressions of the doc test, leading to largely decreased test coverage here.
- The CPython 3.4 test suite is now also using common runner code, and avoids ignoring all Nuitka warnings, instead more white listing was added.
- Started to run CPython 3.5 test suite almost completely, but coroutines are blocking some parts of that, so these tests that use this feature are currently skipped.
- Removed more CPython tests that access the network and are generally useless to testing Nuitka.
- When comparing outputs, normalize typical temporary file names used on posix systems.
- Coverage tests have made some progress, and some changes were made due to its results.
- Added test to cover too complex code module of
idna
module. - Added Python3.5 only test for unpacking variants.
- Prepare plug-in interface to allow suppression of import warnings to access the node doing it, making the import node is accessible.
- Have dedicated class function body object, which is a specialization of the function body node base class. This allowed removing class specific code from that class.
- The use of "win_target" as a scons parameter was useless. Make more consistent use of it as a flag indicator in the scons file.
- Compiled types were mixing uses of
compiled_
prefixes, something with a space, sometimes with an underscore.
- Improved support for Python3.5 missing compatibility with new language features.
- Updated the Developer Manual with changes that SSA is now a fact.
- Added Python3.5 Windows MSI downloads.
- Added repository for Ubuntu Wily (15.10) for download. Removed Ubuntu Utopic package download, no longer supported by Ubuntu.
- Added repository with RPM packages for Fedora 22.
So this release is mostly to lower the technical debt incurred that holds it back from supporting making more interesting changes. Upcoming releases may have continue that trend for some time.
This release is mostly about catching up with Python3.5, to make sure we did not miss anything important. The new function body variants will make it easier to implement coroutines, and help with optimization and compatibility problems that remain for Python3 classes.
Ultimately it will be nice to require a lot less checks for when function in-line is going to be acceptable. Also code generation will need a continued push to use the new structure in preparation for making type specific code generation a reality.
This release enables SSA based optimization, the huge leap, not so much in terms of actual performance increase, but for now making the things possible that will allow it.
This has been in the making literally for years. Over and over, there was just "one more thing" needed. But now it's there.
The release includes much stuff, and there is a perspective on the open tasks in the summary, but first out to the many details.
Standalone: Added implicit import for
reportlab
package configuration dynamic import. Fixed in 0.5.14.1 already.Standalone: Fix, compilation of the
ctypes
module could happen for some import patterns, and then prevented the distribution to contain all necessary libraries. Now it is made certain to not include compiled and frozen form both. Issue#241. Fixed in 0.5.14.1 already.Fix, compilation for conditional statements where the boolean check on the condition cannot raise, could fail compilation. Issue#240. Fixed in 0.5.14.2 already.
Fix, the
__import__
built-in was making static optimization assuming compile time constants to be strings, which in the error case they are not, which was crashing the compiler. Issue#240.__import__(("some.module",)) # tuples don't work
This error became only apparent, because now in some cases, Nuitka forward propagates values.
Windows: Fix, when installing Python2 only for the user, the detection of it via registry failed as it was only searching system key. This was a github pull request. Fixed in 0.5.14.3 already.
Some modules have extremely complex expressions requiring too deep recursion to work on all platforms. These modules are now included entirely as bytecode fallback. Issue#240.
The standard library may contain broken code due to installation mistakes. We have to ignore their
SyntaxError
. Issue#244.Fix, pickling compiled methods was failing with the wrong kind of error, because they should not implement
__reduce__
, but only__deepcopy__
. Issue#219.Fix, when running under
wine
, the check for scons binary was fooled by existance of/usr/bin/scons
. Issue#251.
- Added experimental support for Python3.5, coroutines don't work yet, but it works perfectly as a 3.4 replacement.
- Added experimental Nuitka plug-in framework, and use it for the packaging of Qt plugins in standalone mode. The API is not yet stable nor polished.
- New option
--debugger
that makes--run
execute directly ingdb
and gives a stack trace on crash. - New option
--profile
executes compiled binary and outputs measured performance withvmprof
. This is work in progress and not functional yet. - Started work on
--graph
to render the SSA state into diagrams. This is work in progress and not functional yet. - Plug-in framework added. Not yet ready for users. Working
PyQt4
andPyQt5
plug-in support. Experimental Windowsmultiprocessing
support. Experimental PyLint warnings disable support. More to come. - Added support for AnaConda accelerated mode on MacOS by modifying the rpath to the Python DLL.
- Added experimental support for
multiprocessing
on Windows, which needs money patching of the module to support compiled methods.
- The SSA analysis is now enabled by default, eliminating variables that are not shared, and can be forward propagated. This is currently limited mostly to compile time constants, but things won't remain that way.
- Code generation for many constructs now takes into account if a specific operation can raise or not. If e.g. an attribute look-up is known to not raise, then that is now decided by the node the looked is done to, and then more often can determine this, or even directly the value.
- Calls to C-API that we know cannot raise, no longer check, but merely assert the result.
- For attribute look-up and other operations that might be known to not raise, we now only assert that it succeeds.
- Built-in loop-ups cannot fail, merely assert that.
- Creation of built-in exceptions never raises, merely assert that too.
- More Python operation slots now have their own computations and some of these gained overloads for more compile time constant optimization.
- When taking an iterator cannot raise, this is now detected more often.
- The
try
/finally
construct is now represented by duplicating the final block into all kinds of handlers (break
,continue
,return
, orexcept
) and optimized separately. This allows for SSA to trace values more correctly. - The
hash
built-in now has dedicated node and code generation too. This is mostly intended to represent the side effects of dictionary look-up, but gives more compact and faster code too. - Type
type
built-in cannot raise and has no side effect. - Speed improvement for in-place float operations for
+=
and*=
, as these will be common cases.
- Made the construct based testing executable with Python3.
- Removed warnings using the new PyLint warnings plug-in for the reflected test. Nuitka now uses the PyLint annotations to not warn. Also do not go into PyQt for reflected test, not needed. Many Python3 improvements for cases where there are differences to report.
- The optimization tests no longer use 2to3 anymore, made the tests portable to all versions.
- Checked more in-place operations for speed.
- Many improvements to the coverage taking. We can hope to see public data from this, some improvements were triggered from this already, but full runs of the test suite with coverage data collection are yet to be done.
The release includes many important new directions. Coverage analysis will be important to remain certain of test coverage of Nuitka itself. This is mostly done, but needs more work to complete.
Then the graphing surely will help us to debug and understand code examples. So instead of tracing, and reading stuff, we should visualize things, to more clearly see, how things evolve under optimization iteration, and where exactly one thing goes wrong. This will be improved as it proves necessary to do just that. So far, this has been rare. Expect this to become end user capable with time. If only to allow you to understand why Nuitka won't optimize code of yours, and what change of Nuitka it will need to improve.
The comparative performance benchmarking is clearly the most important thing to
have for users. It deserves to be the top priority. Thanks to the PyPy tool
vmprof
, we may already be there on the data taking side, but the presenting
and correlation part, is still open and a fair bit of work. It will be most
important to empower users to make competent performance bug reports, now that
Nuitka enters the phase, where these things matter.
As this is a lot of ground to cover. More than ever. We can make this compiler, but only if you help, it will arrive in your life time.
This release is an intermediate step towards value propagation, which is not
considered ready for stable release yet. The major point is the elimination
of the try
/finally
expressions, as they are problems to SSA. The
try
/finally
statement change is delayed.
There are also a lot of bug fixes, and enhancements to code generation, as well as major cleanups of code base.
Python3: Added support assignments trailing star assignment.
*a, b = 1, 2
This raised
ValueError
before.Python3: Properly detect illegal double star assignments.
*a, *b = c
Python3: Properly detect the syntax error to star assign from non-tuple/list.
*a = 1
Python3.4: Fixed a crash of the binary when copying dictionaries with split tables received as star arguments.
Python3: Fixed reference loss, when using
raise a from b
whereb
was an exception instance. Fixed in 0.5.13.8 already.Windows: Fix, the flag
--disable-windows-console
was not properly handled for MinGW32 run time resulting in a crash.Python2.7.10: Was not recognizing this as a 2.7.x variant and therefore not applying minor version compatibility levels properly.
Fix, when choosing to have frozen source references, code objects were not use the same value as
__file__
did for its filename.Fix, when re-executing itself to drop the
site
module, make sure we find the same file again, and not according to thePYTHONPATH
changes coming from it. Issue#223. Fixed in 0.5.13.4 already.Enhanced code generation for
del variable
statements, where it's clear that the value must be assigned.When pressing CTRL-C, the stack traces from both Nuitka and Scons were given, we now avoid the one from Scons.
Fix, the dump from
--xml
no longer contains functions that have become unused during analysis.Standalone: Creating or running programs from inside unicode paths was not working on Windows. Issue#231 Issue#229 and. Fixed in 0.5.13.7 already.
Namespace package support was not yet complete, importing the parent of a package was still failing. Issue#230. Fixed in 0.5.13.7 already.
Python2.6: Compatibility for exception check messages enhanced with newest minor releases.
Compatibility: The
NameError
in classes needs to sayglobal name
and not justname
too.Python3: Fixed creation of XML representation, now done without
lxml
as it doesn't support needed features on that version. Fixed in 0.5.13.5 already.Python2: Fix, when creating code for the largest negative constant to still fit into
int
, that was only working in the main module. Issue#228. Fixed in 0.5.13.5 already.Compatibility: The
print
statement raised an assertion on unicode objects that could not be encoded withascii
codec.
- Added support for Windows 10.
- Followed changes for Python 3.5 beta 2. Still only usable as a Python 3.4 replacement, no new features.
- Using a self compiled Python running from the source tree is now supported.
- Added support for
AnaConda
Python distribution. As it doesn't install the Python DLL, we copy it along for acceleration mode. - Added support for Visual Studio 2015. Issue#222. Fixed in 0.5.13.3 already.
- Added support for self compiled Python versions running from build tree, this is intended to help debug things on Windows.
Function in-lining is now present in the code, but still disabled, because it needs more changes in other areas, before we can generally do it.
Trivial outlines, result of re-formulations or function in-lining, are now in-lined, in case they just return an expression.
The re-formulation for
or
andand
has been giving up, eliminating the use of atry
/finally
expression, at the cost of dedicated boolean nodes and code generation for these.This saves around 8% of compile time memory for Nuitka, and allows for faster and more complete optimization, and gets rid of a complicated structure for analysis.
When a frame is used in an exception, its locals are detached. This was done more often than necessary and even for frames that are not necessary our own ones. This will speed up some exception cases.
When the default arguments, or the keyword default arguments (Python3) or the annotations (Python3) were raising an exception, the function definition is now replaced with the exception, saving a code generation. This happens frequently with Python2/Python3 compatible code guarded by version checks.
The SSA analysis for loops now properly traces "break" statement situations and merges the post-loop situation from all of them. This significantly allows for and improves optimization of code following the loop.
The SSA analysis of
try
/finally
statements has been greatly enhanced. The handler forfinally
is now optimized for exception raise and no exception raise individually, as well as forbreak
,continue
andreturn
in the tried code. The SSA analysis for after the statement is now the result of merging these different cases, should they not abort.The code generation for del statements is now taking advantage should there be definite knowledge of previous value. This speed them up slightly.
The SSA analysis of del statements now properly decided if the statement can raise or not, allowing for more optimization.
For list contractions, the re-formulation was enhanced using the new outline construct instead of a pseudo function, leading to better analysis and code generation.
Comparison chains are now re-formulated into outlines too, allowing for better analysis of them.
Exceptions raised in function creations, e.g. in default values, are now propagated, eliminating the function's code. This happens most often with Python2/Python3 in branches. On the other hand, function creations that cannot are also annotated now.
Closure variables that become unreferenced outside of the function become normal variables leading to better tracing and code generation for them.
Function creations cannot raise except their defaults, keyword defaults or annotations do.
Built-in references can now be converted to strings at compile time, e.g. when printed.
- Removed gitorious mirror of the git repository, they shut down.
- Make it more clear in the documentation that Python2 is needed at compile time to create Python3 executables.
Moved more parts of code generation to their own modules, and used registry for code generation for more expression kinds.
Unified
try
/except
andtry
/finally
into a single construct that handles both throughtry
/except
/break
/continue
/return
semantics. Finally is now solved via duplicating the handler into cases necessary.No longer are nodes annotated with information if they need to publish the exception or not, this is now all done with the dedicated nodes.
The
try
/finally
expressions have been replaced with outline function bodies, that instead of side effect statements, are more like functions with return values, allowing for easier analysis and dedicated code generation of much lower complexity.No more "tolerant" flag for release nodes, we now decide this fully based on SSA information.
Added helper for assertions that code flow does not reach certain positions, e.g. a function must return or raise, aborting statements do not continue and so on.
To keep cloning of code parts as simple as possible, the limited use of
makeCloneAt
has been changed to a newmakeClone
which produces identical copies, which is what we always do. And a generic cloning based on "details" has been added, requiring to make constructor arguments and details complete and consistent.The re-formulation code helpers have been improved to be more convenient at creating nodes.
The old
nuitka.codegen
moduleGenerator
was still used for many things. These now all got moved to appropriate code generation modules, and their users got updated, also moving some code generator functions in the process.The module
nuitka.codegen.CodeTemplates
got replaces with direct uses of the proper topic module fromnuitka.codegen.templates
, with some more added, and their names harmonized to be more easily recognizable.Added more assertions to the generated code, to aid bug finding.
The autoformat now sorts pylint markups for increased consistency.
Releases no longer have a
tolerant
flag, this was not needed anymore as we use SSA.Handle CTRL-C in scons code preventing per job messages that are not helpful and avoid tracebacks from scons, also remove more unused tools like
rpm
from out in-line copy.
Added the CPython3.4 test suite.
The CPython3.2, CPython3.3, and CPython3.4 test suite now run with Python2 giving the same errors. Previously there were a few specific errors, some with line numbers, some with different
SyntaxError
be raised, due to different order of checks.This increases the coverage of the exception raising tests somewhat.
Also the CPython3.x test suites now all pass with debug Python, as does the CPython 2.6 test suite with 2.6 now.
Added tests to cover all forms of unpacking assignments supported in Python3, to be sure there are no other errors unknown to us.
Started to document the reference count tests, and to make it more robust against SSA optimization. This will take some time and is work in progress.
Made the compile library test robust against modules that raise a syntax error, checking that Nuitka does the same.
Refined more tests to be directly execuable with Python3, this is an ongoing effort.
This release is clearly major. It represents a huge step forward for Nuitka as
it improves nearly every aspect of code generation and analysis. Removing the
try
/finally
expression nodes proved to be necessary in order to even
have the correct SSA in their cases. Very important optimization was blocked by
it.
Going forward, the try
/finally
statements will be removed and dead
variable elimination will happen, which then will give function inlining. This
is expected to happen in one of the next releases.
This release is a consolidation of 8 hotfix releases, and many refactorings needed towards the next big step, which might also break things, and for that reason is going to get its own release cycle.
This release contains the first use of SSA for value propagation and massive amounts of bug fixes and optimization. Some of the bugs that were delivered as hotfixes, were only revealed when doing the value propagation as they still could apply to real code.
- Fix, relative imports in packages were not working with absolute imports enabled via future flags. Fixed in 0.5.12.1 already.
- Loops were not properly degrading knowledge from inside the loop at loop
exit, and therefore this could have lead missing checks and releases in code
generation for cases, for
del
statements in the loop body. Fixed in 0.5.12.1 already. - The
or
andand
re-formulation could trigger false assertions, due to early releases for compatibility. Fixed in 0.5.12.1 already. - Fix, optimizion of calls of constant objects (always an exception), crashed the compiler. This corrects Issue#202. Fixed in 0.5.12.2 already.
- Standalone: Added support for
site.py
installations with a leadingdef
orclass
statement, which is defeating our attempt to patch__file__
for it. This corrects Issue#189. - Compatibility: In full compatibility mode, the tracebacks of
or
andand
expressions are now as wrong as they are in CPython. Does not apply to--improved
mode. - Standalone: Added missing dependency on
QtGui
byQtWidgets
for PyQt5. - MacOS: Improved parsing of
otool
output to avoid duplicate entries, which can also be entirely wrong in the case of Qt plugins at least. - Avoid relative paths for main program with file reference mode
original
, as it otherwise changes as the file moves. - MinGW: The created modules depended on MinGW to be in
PATH
for their usage. This is no longer necessary, as we now link these libraries statically for modules too. - Windows: For modules, the option
--run
to immediately load the modules had been broken for a while. - Standalone: Ignore Windows DLLs that were attempted to be loaded, but then failed to load. This happens e.g. when both PySide and PyQt are installed, and could cause the dreaded conflicting DLLs message. The DLL loaded in error is now ignored, which avoids this.
- MinGW: The resource file used might be empty, in which case it doesn't get created, avoiding an error due to that.
- MinGW: Modules can now be created again. The run time relative code uses an API that is WinXP only, and MinGW failed to find it without guidance.
Make direct calls out of called function creations. Initially this applies to lambda functions only, but it's expected to become common place in coming releases. This is now 20x faster than CPython.
# Nuitka avoids creating a function object, parsing function arguments: (lambda x:x)(something)
Propagate assignments from non-mutable constants forward based on SSA information. This is the first step of using SSA for real compile time optimization.
Specialized the creation of call nodes at creation, avoiding to have all kinds be the most flexible form (keyword and plain arguments), but instead only what kind of call they really are. This saves lots of memory, and makes the tree faster to visit.
Added support for optimizing the
slice
built-in with compile time constant arguments to constants. The re-formulation for slices in Python3 uses these a lot. And the lack of this optimization prevented a bunch of optimization in this area. For Python2 the built-in is optimized too, but not as important probably.Added support for optimizing
isinstance
calls with compile time constant arguments. This avoids static exception raises in theexec
re-formulation which tests forfile
type, and then optimization couldn't tell that astr
is not afile
instance. Now it can.Lower in-place operations on immutable types to normal operations. This will allow to compile time compute these more accurately.
The re-formulation of loops puts the loop condition as a conditional statement with break. The
not
that needs to apply was only added in later optimization, leading to unnecessary compile time efforts.Removed per variable trace visit from optimization, removing useless code and compile time overhead. We are going to optimize things by making decision in assignment and reference nodes based on forward looking statements using the last trace collection.
- Added experimental support for Python 3.5, which seems to be passing the
test suites just fine. The new
@
matrix multiplicator operators are not yet supported though. - Added support for patching source on the fly. This is used to work around
a (now fixed) issue with
numexpr.cpuinfo
making type checks with theis
operation, about the only thing we cannot detect.
- Added repository for Ubuntu Vivid (15.04) for download. Removed Ubuntu Saucy and Ubuntu Raring package downloads, these are no longer supported by Ubuntu.
- Added repository for Debian Stretch, after Jessie release.
- Make it more clear in the documentation that in order to compile Python3, a Python2 is needed to execute Scons, but that the end result is a Python3 binary.
- The PyLint checker tool now can operate on directories given on the command line, and whitelists an error that is Windows only.
- Split up standalone code further, moving
depends.exe
handling to a separate module. - Reduced code complexity of scons interface.
- Cleaned up where trace collection is being done. It was partially still done inside the collection itself instead in the owner.
- In case of conflicting DLLs for standalone mode, these are now output with nicer formatting, that makes it easy to recognize what is going on.
- Moved code to fetch
depends.exe
to dedicated module, so it's not as much in the way of standalone code.
- Made
BuiltinsTest
directly executable with Python3. - Added construct test to demonstrate the speed up of direct lambda calls.
- The deletion of
@test
for the CPython test suite is more robust now, esp. on Windows, the symbolic links are now handled. - Added test to cover
or
usage with in-place assignment. - Cover local relative
import from .
withabsolute_import
future flag enabled. - Again, more basic tests are now directly executable with Python3.
This release is major due to amount of ground covered. The reduction in memory usage of Nuitka itself (the C++ compiler will still use much memory) is very massive and an important aspect of scalability too.
Then the SSA changes are truly the first sign of major improvements to come. In their current form, without eliminating dead assignments, the full advantage is not taken yet, but the next releases will do this, and that's a major milestone to Nuitka.
The other optimization mostly stem from looking at things closer, and trying to work towards function in-lining, for which we are making a lot of progress now.
This release contains massive amounts of corrections for long standing issues
in the import recursion mechanism, as well as for standalone issues now visible
after the __file__
and __path__
values have changed to become runtime
dependent values.
Fix, the
__path__
attribute for packages was still the original filename's directory, even in file reference mode wasruntime
.The use of
runtime
as default file reference mode for executables, even if not in standalone mode, was making acceleration harder than necessary. Changed tooriginal
for that case. Fixed in 0.5.11.1 already.The constant value for the smallest
int
that is not yet along
is created using1
due to C compiler limitations, but1
was not yet initialized properly, if this was a global constant, i.e. used in multiple modules. Fixed in 0.5.11.2 already.Standalone: Recent fixes around
__path__
revealed issues with PyWin32, where modules fromwin32com.shell
were not properly recursed to. Fixed in 0.5.11.2 already.The importing of modules with the same name as a built-in module inside a package falsely assumed these were the built-ins which need not exist, and then didn't recurse into them. This affected standalone mode the most, as the module was then missing entirely. This corrects Issue#178.
# Inside "x.y" module: import x.y.exceptions
Similarily, the importing of modules with the same name as standard library modules could go wrong. This corrects Issue#184.
# Inside "x.y" module: import x.y.types
Importing modules on Windows and MacOS was not properly checking the checking the case, making it associate wrong modules from files with mismatching case. This corrects Issue#188.
Standalone: Importing with
from __future__ import absolute_import
would prefer relative imports still. This corrects Issue#187.Python3: Code generation for
try
/return expr
/finally
could loose exceptions whenexpr
raised an exception, leading to aRuntimeError
forNULL
return value. The real exception was lost.Lambda expressions that were directly called with star arguments caused the compiler to crash.
(lambda *args:args)(*args) # was crashing Nuitka
- Focusing on compile time memory usage, cyclic dependencies of trace merges that prevented them from being released, even when replaced were removed.
- More memory efficient updating of global SSA traces, reducing memory usage during optimization by ca. 50%.
- Code paths that cannot and therefore must not happen are now more clearly indicated to the backend compiler, allowing for slightly better code to be generated by it, as it can tell that certain code flows need not be merged.
- Standalone: On systems, where
.pth
files inject Python packages at launch, these are now detected, and taking into account. Previously Nuitka did not recognize them, due to lack of__init__.py
files. These are mostly pip installations of e.g.zope.interface
. - Added option
--explain-imports
to debug the import resolution code of Nuitka. - Added options
--show-memory
to display the amount of memory used in total and how it's spread across the different node types during compilation. - The option
--trace-execution
now also covers early program initialisation before any Python code runs, to ease finding bugs in this domain as well.
- Changed default for file reference mode to
original
unless standalone or module mode are used. For mere acceleration, breaking the reading of data files from__file__
is useless. - Added check that the in-line copy of scons is not run with Python3, which is not supported. Nuitka works fine with Python3, but a Python2 is required to execute scons.
- Discover more kinds of Python2 installations on Linux/MacOS installations.
- Added instructions for MacOS to the download page.
- Moved
oset
andodict
modules which provide ordered sets and dictionaries into a new packagenuitka.container
to clean up the top level scope. - Moved
SyntaxErrors
tonuitka.tree
package, where it is used to format error messages. - Moved
nuitka.Utils
package tonuitka.utils.Utils
creating a whole package for utils, so as to better structure them for their purpose.
This release is a major maintenance release. Support for namespace modules
injected by *.pth
is a major step for new compatibility. The import logic
improvements expand the ability of standalone mode widely. Many more use cases
will now work out of the box, and less errors will be found on case insensitive
systems.
There is aside of memory issues, no new optimization though as many of these improvements could not be delivered as hotfixes (too invasive code changes), and should be out to the users as a stable release. Real optimization changes have been postponed to be next release.
The last release represented a significant change and introduced a few regressions, which got addressed with hot fix releases. But it also had a focus on cleaning up open optimization issues that were postponed in the last release.
The filenames of source files as found in the
__file__
attribute are now made relative for all modes, not just standalone mode.This makes it possible to put data files along side compiled modules in a deployment. This solves Issue#170.
Local functions that reference themselves were not released. They now are.
def someFunction(): def f(): f() # referencing 'f' in 'f' caused the garbage collection to fail.
Recent changes to code generation attached closure variable values to the function object, so now they can be properly visited. This corrects Issue#45. Fixed in 0.5.10.1 already.
Python2.6: The complex constants with real or imaginary parts
-0.0
were collapsed with constants of value0.0
. This became more evident after we started to optimize thecomplex
built-in. Fixed in 0.5.10.1 already.complex(0.0, 0.0) complex(-0.0, -0.0) # Could be confused with the above.
Complex call helpers could leak references to their arguments. This was a regression. Fixed in 0.5.10.1 already.
Parameter variables offered as closure variables were not properly released, only the cell object was, but not the value. This was a regression. Fixed in 0.5.10.1 already.
Compatibility: The exception type given when accessing local variable values not initialized in a closure taking function, needs to be
NameError
andUnboundLocalError
for accesses in the providing function. Fixed in 0.5.10.1 already.Fix support for "venv" on systems, where the system Python uses symbolic links too. This is the case on at least on Mageia Linux. Fixed in 0.5.10.2 already.
Python3.4: On systems where
long
andPy_ssize_t
are different (e.g. Win64) iterators could be corrupted if used by uncompiled Python code. Fixed in 0.5.10.2 already.Fix, generator objects didn't release weak references to them properly. Fixed in 0.5.10.2 already.
Compatiblity: The
__closure__
attributes of functions was so far not supported, and rarely missing. Recent changes made it easy to expose, so now it was added. This corrects Issue#45.MacOS: A linker warning about deprecated linker option
-s
was solved by removing the option.Compatibility: Nuitka was enforcing that the
__doc__
attribute to be a string object, and gave a misleading error message. This check must not be done though,__doc__
can be any type in Python. This corrects Issue#177.
Variables that need not be shared, because the uses in closure taking functions were eliminated, no longer use cell objects.
The
try
/except
andtry
/finally
statements now both have actual merging for SSA, allowing for better optimization of code behind it.def f(): try: a = something() except: return 2 # Since the above exception handling cannot continue the code flow, # we do not have to invalidate the trace of "a", and e.g. do not have # to generate code to check if it's assigned. return a
Since
try
/finally
is used in almost all re-formulations of complex Python constructs this is improving SSA application widely. The uses oftry
/except
in user code will no longer degrade optimization and code generation efficiency as much as they did.The
try
/except
statement now reduces the scope of tried block if possible. When no statement raised, already the handling was removed, but leading and trailing statements that cannot raise, were not considered.def f(): try: b = 1 a = something() c = 1 except: return 2
This is now optimized to.
def f(): b = 1 try: a = something() except: return 2 c = 1
The impact may on execution speed may be marginal, but it is definitely going to improve the branch merging to be added later. Note that
c
can only be optimized, because the exception handler is aborting, otherwise it would change behaviour.The creation of code objects for standalone mode and now all code objects was creating a distinct filename object for every function in a module, despite them being same content. This was wasteful for module loading. Now it's done only once.
Also, when having multiple modules, the code to build the run time filename used for code objects, was calling import logic, and doing lookups to find
os.path.join
again and again. These are now cached, speeding up the use of many modules as well.
Nuitka used to have "variable usage profiles" and still used them to decide if a global variable is written to, in which case, it stays away from doing optimization of it to built-in lookups, and later calls.
The have been replaced by "global variable traces", which collect the traces to a variable across all modules and functions. While this is now only a replacement, and getting rid of old code, and basing on SSA, later it will also allow to become more correct and more optimized.
The standalone now queries its hidden dependencies from a plugin framework, which will become an interface to Nuitka internals in the future.
- The use of deep hashing of constants allows us to check if constants become mutated during the run-time of a program. This allows to discover corruption should we encounter it.
- The tests of CPython are now also run with Python in debug mode, but only on Linux, enhancing reference leak coverage.
- The CPython test parts which had been disabled due to reference cycles
involving compiled functions, or usage of
__closure__
attribute, were reactivated.
- Since Google Code has shutdown, it has been removed from the Nuitka git mirrors.
This release brings exciting new optimization with the focus on the try
constructs, now being done more optimal. It is also a maintenance release,
bringing out compatibility improvements, and important bug fixes, and important
usability features for the deployment of modules and packages, that further
expand the use cases of Nuitka.
The git flow had to be applied this time to get out fixes for regression bug fixes, that the big change of the last release brought, so this is also to consolidate these and the other corrections into a full release before making more invasive changes.
The cleanups are leading the way to expanded SSA applied to global variable and shared variable values as well. Already the built-in detect is now based on global SSA information, which was an important step ahead.
This release has a focus on code generation optimization. Doing major changes away from "C++-ish" code to "C-ish" code, many constructs are now faster or got looked at and optimized.
- Compatibility: The variable name in locals for the iterator provided to the
generator expression should be
.0
, now it is. - Generators could leak frames until program exit, these are now properly freed immediately.
Faster exception save and restore functions that might be in-lined by the backend C compiler.
Faster error checks for many operations, where these errors are expected, e.g. instance attribute lookups.
Do not create traceback and locals dictionary for frame when
StopIteration
orGeneratorExit
are raised. These tracebacks were wasted, as they were immediately released afterwards.Closure variables to functions and parameters of generator functions are now attached to the function and generator objects.
The creation of functions with closure taking was accelerated.
The creation and destruction of generator objects was accelerated.
The re-formulation for in-place assignments got simplified and got faster doing so.
In-place operations of
str
were always copying the string, even if was not necessary. This corrects Issue#124.a += b # Was not re-using the storage of "a" in case of strings
Python2: Additions of
int
for Python2 are now even faster.Access to local variable values got slightly accelerated at the expense of closure variables.
Added support for optimizing the
complex
built-in.Removing unused temporary and local variables as a result of optimization, these previously still allocated storage.
- The use of C++ classes for variable objects was removed. Closure variables
are now attached as
PyCellObject
to the function objects owning them. - The use of C++ context classes for closure taking and generator parameters has been replaced with attaching values directly to functions and generator objects.
- The indentation of code template instantiations spanning multiple was not
in all cases proper. We were using emission objects that handle it new lines
in code and mere
list
objects, that don't handle them in mixed forms. Now only the emission objects are used. - Some templates with C++ helper functions that had no variables got changed to be properly formatted templates.
- The internal API for handling of exceptions is now more consistent and used more efficiently.
- The printing helpers got cleaned up and moved to static code, removing any need for forward declaration.
- The use of
INCREASE_REFCOUNT_X
was removed, it got replaced with properPy_XINCREF
usages. The function was once required before "C-ish" lifted the need to do everything in one function call. - The use of
INCREASE_REFCOUNT
got reduced. See above for why that is any good. The idea is thatPy_INCREF
must be good enough, and that we want to avoid the C function it was, even if in-lined. - The
assertObject
function that checks if an object is notNULL
and has positive reference count, i.e. is sane, got turned into a preprocessor macro. - Deep hashes of constant values created in
--debug
mode, which cover also mutable values, and attempt to depend on actual content. These are checked at program exit for corruption. This may help uncover bugs.
- Speedcenter has been enhanced with better graphing and has more benchmarks now. More work will be needed to make it useful.
- Updates to the Developer Manual, reflecting the current near finished state of "C-ish" code generation.
- New reference count tests to cover generator expressions and their usage got added.
- Many new construct based tests got added, these will be used for performance graphing, and serve as micro benchmarks now.
- Again, more basic tests are directly executable with Python3.
This is the next evolution of "C-ish" coming to pass. The use of C++ has for all practical purposes vanished. It will remain an ongoing activity to clear that up and become real C. The C++ classes were a huge road block to many things, that now will become simpler. One example of these were in-place operations, which now can be dealt with easily.
Also, lots of polishing and tweaking was done while adding construct benchmarks that were made to check the impact of these changes. Here, generators probably stand out the most, as some of the missed optimization got revealed and then addressed.
Their speed increases will be visible to some programs that depend a lot on generators.
This release is clearly major in that the most important issues got addressed, future releases will provide more tuning and completeness, but structurally the "C-ish" migration has succeeded, and now we can reap the benefits in the coming releases. More work will be needed for all in-place operations to be accelerated.
More work will be needed to complete this, but it's good that this is coming to an end, so we can focus on SSA based optimization for the major gains to be had.
This release is mostly a maintenance release, bringing out minor compatibility improvements, and some standalone improvements. Also new options to control the recursion into modules are added.
Compatibility: Checks for iterators were using
PyIter_Check
which is buggy when running outside of Python core, because it's comparing pointers we don't see. Replaced withHAS_ITERNEXT
helper which compares against the pointer as extracting for a real non-iterator object.class Iterable: def __init__(self): self.consumed = 2 def __iter__(self): return Iterable() iter(Iterable()) # This is suppose to raise, but didn't with Nuitka
Python3: Errors when creating class dictionaries raised by the
__prepare__
dictionary (e.g.enum
classes with wrong identifiers) were not immediately raised, but only by thetype
call. This was not observable, but might have caused issues potentially.Standalone MacOS: Shared libraries and extension modules didn't have their DLL load paths updated, but only the main binary. This is not sufficient for more complex programs.
Standalone Linux: Shared libraries copied into the
.dist
folder were read-only and executingchrpath
could potentially then fail. This has not been observed, but is a conclusion of MacOS fix.Standalone: When freezing standard library, the path of Nuitka and the current directory remained in the search path, which could lead to looking at the wrong files.
- The
getattr
built-in is now optimized for compile time constants if possible, even in the presence of adefault
argument. This is more a cleanup than actually useful yet. - The calling of
PyCFunction
from normal Python extension modules got accelerated, especially for the no or single argument cases where Nuitka now avoids building the tuple.
Added the option
--recurse-pattern
to include modules per filename, which for Python3 is the only way to not have them in a package automatically.Added the option
--generate-c++-only
to only generate the C++ source code without starting the compiler.Mostly used for debugging and testing coverage. In the later case we do not want the C++ compiler to create any binary, but only to measure what would have been used.
- Renamed the debug option
--c++-only
to--recompile-c++-only
to make its purpose more clear and there now is--generate-c++-only
too.
- Added support for taking coverage of Nuitka in a test run on a given input file.
- Added support for taking coverage for all Nuitka test runners, migrating them all to common code for searching.
- Added uniform way of reporting skipped tests, not generally used yet.
This release marks progress towards having coverage testing. Recent releases had made it clear that not all code of Nuitka is actually used at least once in our release tests. We aim at identifying these.
Another direction was to catch cases, where Nuitka leaks exceptions or is subject to leaked exceptions, which revealed previously unnoticed errors.
Important changes have been delayed, e.g. the closure variables will not yet
use C++ objects to share storage, but proper PyCellObject
for improved
compatibility, and to approach a more "C-ish" status. These is unfinished code
that does this. And the forward propagation of values is not enabled yet
again either.
So this is an interim step to get the bug fixes and improvements accumulated out. Expect more actual changes in the next releases.
This release has mainly a focus on cleanups and compatibility improvements. It also advances standalone support, and a few optimization improvements, but it mostly is a maintenance release, attacking long standing issues.
Compatibility Windows MacOS: Fix importing on case insensitive systems.
It was not always working properly, if there was both a package
Something
andsomething
, by merit of having filesSomething/__init__.py
andsomething.py
.Standalone: The search path was preferring system directories and therefore could have conflicting DLLs. Issue#144.
Fix, the optimization of
getattr
with predictable result was crashing the compilation. This was a regression, fixed in 0.5.7.1 already.Compatibility: The name mangling inside classes also needs to be applied to global variables.
Fix, proving
clang++
forCXX
was mistakingly thinking of it as ag++
and making version checks on it.Python3: Declaring
__class__
global is now aSyntaxError
before Python3.4.Standalone Python3: Making use of module state in extension modules was not working properly.
The filenames of source files as found in the
__file__
attribute are now made relative in standalone mode.This should make it more apparent if things outside of the distribution folder are used, at the cost of tracebacks. Expect the default ability to copy the source code along in an upcoming release.
Added experimental standalone mode support for PyQt5. At least headless mode should be working, plug-ins (needed for anything graphical) are not yet copied and will need more work.
- No longer using
imp.find_module
anymore. To solve the casing issues we needed to make our own module finding implementation finally. - The name mangling was handled during code generation only. Moved to tree building instead.
- More code generation cleanups. The compatible line numbers are now attached during tree building and therefore better preserved, as well as that code no longer polluting code generation as much.
- No more packages for openSUSE 12.1/12.2/12.3 and Fedora 17/18/19 as requested by the openSUSE Build Service.
- Added RPM packages for Fedora 21 and CentOS 7 on openSUSE Build Service.
- Lots of test refinements for the CPython test suites to be run continuously in Buildbot for both Windows and Linux.
This release brings about two major changes, each with the risk to break things.
One is that we finally started to have our own import logic, which has the risk to cause breakage, but apparently currently rather improved compatibility. The case issues were not fixable with standard library code.
The second one is that the __file__
attributes for standalone mode is now no
longer pointing to the original install and therefore will expose missing stuff
sooner. This will have to be followed up with code to scan for missing "data"
files later on.
For SSA based optimization, there are cleanups in here, esp. the one removing the name mangling, allowing to remove special code for class variables. This makes the SSA tree more reliable. Hope is that the big step (forward propagation through variables) can be made in one of the next releases.
This release is brings a newly supported platform, bug fixes, and again lots of cleanups.
Fix, creation of dictionary and set literals with non-hashable indexes did not raise an exception.
{[]: None} # This is now a TypeError
Calls to the
dict
built-in with only keyword arguments are now optimized to mere dictionary creations. This is new for the case of non-constant arguments only of course.dict(a = b, c = d) # equivalent to {"a" : b, "c" : d}
Slice
del
with indexable arguments are now using optimized code that avoids Python objects too. This was already done for slice look-ups.Added support for
bytearray
built-in.
- Added support for OpenBSD with fiber implementation from library, as it has no context support.
- Moved slicing solutions for Python3 to the re-formulation stage. So far the slice nodes were used, but only at code generation time, there was made a distinction between Python2 and Python3 for them. Now these nodes are purely Python2 and slice objects are used universally for Python3.
- The test runners now have common code to scan for the first file to compile,
an implementation of the
search
mode. This will allow to introduce the ability to search for pattern matches, etc. - More tests are directly executable with Python3.
- Added
recurse_none
mode to test comparison, making using extra options for that purpose unnecessary.
This solves long standing issues with slicing and subscript not being properly distinguished in the Nuitka code. It also contains major bug fixes that really problematic. Due to the involved nature of these fixes they are made in this new release.
This release brings bug fixes, important new optimization, newly supported platforms, and important compatibility improvements. Progress on all fronts.
Closure taking of global variables in member functions of classes that had a class variable of the same name was binding to the class variable as opposed to the module variable.
Overwriting compiled function's
__doc__
attribute more than once could corrupt the old value, leading to crashes. Issue#156. Fixed in 0.5.5.2 already.Compatibility Python2: The
exec
statementexecfile
were changinglocals()
was given as an argument.def function(): a = 1 exec code in locals() # Cannot change local "a". exec code in None # Can change local "a" exec code
Previously Nuitka treated all 3 variants the same.
Compatibility: Empty branches with a condition were reduced to only the condition, but they need in fact to also check the truth value:
if condition: pass # must be treated as bool(condition) # and not (bug) condition
Detection of Windows virtualenv was not working properly. Fixed in 0.5.5.2 already.
Large enough constants structures are now unstreamed via
marshal
module, avoiding large codes being generated with no point. Fixed in 0.5.5.2 already.Windows: Pressing CTRL-C gave two stack traces, one from the re-execution of Nuitka which was rather pointless. Fixed in 0.5.5.1 already.
Windows: Searching for virtualenv environments didn't terminate in all cases. Fixed in 0.5.5.1 already.
During installation from PyPI with Python3 versions, there were errors given for the Python2 only scons files. Issue#153. Fixed in 0.5.5.3 already.
Fix, the arguments of
yield from
expressions could be leaked.Fix, closure taking of a class variable could have in a sub class where the module variable was meant.
var = 1 class C: var = 2 class D: def f(): # was C.var, now correctly addressed top level var return var
Fix, setting
CXX
environment variable because the installed gcc has too low version, wasn't affecting the version check at all.Fix, on Debian/Ubuntu with
hardening-wrapper
installed the version check was always failing, because these report a shortened version number to Scons.
- Local variables that must be assigned also have no side effects, making use of SSA. This allows for a host of optimization to be applied to them as well, often yielding simpler access/assign code, and discovering in more cases that frames are not necessary.
- Micro optimization to
dict
built-in for simpler code generation.
- Added support for ARM "hard float" architecture.
- Added package for Ubuntu 14.10 for download.
- Added package for openSUSE 13.2 for download.
- Donations were used to buy a Cubox-i4 Pro. It got Debian Jessie installed on it, and will be used to run an even larger amount of tests.
- Made it more clear in the user documentation that the
.exe
suffix is used for all platforms, and why. - Generally updated information in user manual and developer manual about the optimization status.
- Using Nikola 7.1 with external filters instead of our own, outdated branch for the web site.
- PyLint clean for the first time ever. We now have a Buildbot driven test that this stays that way.
- Massive indentation cleanup of keyword argument calls. We have a rule to align the keywords, but as this was done manually, it could easily get out of touch. Now with a "autoformat" tool based on RedBaron, it's correct. Also, spacing around arguments is now automatically corrected. More to come.
- For
exec
statements, the coping back to local variables is now an explicit node in the tree, leader to cleaner code generation, as it now uses normal variable assignment code generation. - The
MaybeLocalVariables
became explicit about which variable they might be, and contribute to its SSA trace as well, which was incomplete before. - Removed some cases of code duplication that were marked as TODO items. This often resulted in cleanups.
- Do not use
replaceWith
on child nodes, that potentially were re-used during their computation.
The release is mainly the result of consolidation work. While the previous
release contained many important enhancements, this is another important step
towards full SSA, closing one loop whole (class variables and exec
functions), as well as applying it to local variables, largely extending its
use.
The amount of cleanups is tremendous, in huge part due to infrastructure problems that prevented release repeatedly. This reduces the technological debt very much.
More importantly, it would appear that now eliminating local and temporary variables that are not necessary is only a small step away. But as usual, while this may be easy to implement now, it will uncover more bugs in existing code, that we need to address before we continue.
This release is finally making full use of SSA analysis knowledge for code generation, leading to many enhancements over previous releases.
It also adds support for Python3.4, which has been longer in the making, due to many rather subtle issues. In fact, even more work will be needed to fully solve remaining minor issues, but these should affect no real code.
And then there is much improved support for using standalone mode together with virtualenv. This combination was not previously supported, but should work now.
Added support for Python3.4
This means support for
clear
method of frames to close generators, dynamic__qualname__
, affected byglobal
statements, tuples asyield from
arguments, improved error messages, additional checks, and many more detail changes.
Using SSA knowledge, local variable assignments now no longer need to check if they need to release previous values, they know definitely for the most cases.
def f(): a = 1 # This used to check if old value of "a" needs a release ...
Using SSA knowledge, local variable references now no longer need to check for raising exceptions, let alone produce exceptions for cases, where that cannot be.
def f(): a = 1 return a # This used to check if "a" is assigned
Using SSA knowledge, local variable references now are known if they can raise the
UnboundLocalError
exception or not. This allows to eliminate frame usages for many cases. Including the above example.Using less memory for keeping variable information.
Also using less memory for constant nodes.
The standalone freezing code was reading Python source as UTF-8 and not using the code that handles the Python encoding properly. On some platforms there are files in standard library that are not encoded like that.
The fiber implementation for Linux amd64 was not working with glibc from RHEL 5. Fixed to use now multiple
int
to pass pointers as necessary. Also useuintptr_t
instead ofintprt_t
to transport pointers, which may be more optimal.Line numbers for exceptions were corrupted by
with
statements due to setting line numbers even for statements marked as internal.Partial support for
win32com
by adding support for its hidden__path__
change.Python3: Finally figured out proper chaining of exceptions, given proper context messages for exception raised during the handling of exceptions.
Corrected C++ memory leak for each closure variable taken, each time a function object was created.
Python3: Raising exceptions with tracebacks already attached, wasn't using always them, but producing new ones instead.
Some constants could cause errors, as they cannot be handled with the
marshal
module as expected, e.g.(int,)
.Standalone: Make sure to propagate
sys.path
to the Python instance used to check for standard library import dependencies. This is important for virtualenv environments, which needsite.py
to set the path, which is not executed in that mode.Windows: Added support for different path layout there, so using virtualenv should work there too.
The code object flag "optimized" (fast locals as opposed to locals dictionary) for functions was set wrongly to value for the parent, but for frames inside it, one with the correct value. This lead to more code objects than necessary and false
co_flags
values attached to the function.Options passed to
nuitka-python
could get lost.nuitka-python program.py argument1 argument2 ...
The above is supposed to compile program.py, execute it immediately and pass the arguments to it. But when Nuitka decides to restart itself, it would forget these options. It does so to e.g. disable hash randomization as it would affect code generation.
Raising tuples exception as exceptions was not compatible (Python2) or reference leaking (Python3).
- Running
2to3
is now avoided for tests that are already running on both Python2 and Python3. - Made XML based optimization tests work with Python3 too. Previously these were only working on Python2.
- Added support for ignoring messages that come from linking against self compiled Pythons.
- Added test case for threaded generators that tortures the fiber layer a bit and exposed issues on RHEL 5.
- Made reference count test of compiled functions generic. No more code duplication, and automatic detection of shared stuff. Also a more clear interface for disabling test cases.
- Added Python2 specific reference counting tests, so the other cases can be executed with Python3 directly, making debugging them less tedious.
- Really important removal of "variable references". They didn't solve any problem anymore, but their complexity was not helpful either. This allowed to make SSA usable finally, and removed a lot of code.
- Removed special code generation for parameter variables, and their dedicated classes, no more needed, as every variable access code is now optimized like this.
- Stop using C++ class methods at all. Now only the destructor of local
variables is actually supposed to do anything, and their are no methods
anymore. The unused
var_name
got removed,setVariableValue
is now done manually. - Moved assertions for the fiber layer to a common place in the header, so they are executed on all platforms in debug mode.
- As usual, also a bunch of cleanups for PyLint were applied.
- The
locals
built-in code now uses code generation for accessing local variable values instead having its own stuff.
The Python version 3.4 is now officially supported. There are a few problems open, that will be addressed in future releases, none of which will affect normal people though.
Major cleanup of Nuitka options.
- Windows specific stuff is now in a dedicated option group. This includes options for icon, disabling console, etc.
- There is now a dedicated group for controlling backend compiler choices and options.
Also pickup
g++44
automatically, which makes using Nuitka on CentOS5 more automatic.
This release represents a very important step ahead. Using SSA for real stuff will allow us to build the trust necessary to take the next steps. Using the SSA information, we could start implementing more optimizations.
This release is aiming at preparatory changes to enable optimization based on SSA analysis, introducing a variable registry, so that variables no longer trace their references to themselves.
Otherwise, MinGW64 support has been added, and lots of bug fixes were made to improve the compatibility.
- Using new variable registry, now properly detecting actual need for sharing
variables. Optimization may discover that it is unnecessary to share a
variable, and then it no longer is. This also allows
--debug
without it reporting unused variable warnings on Python3. - Scons startup has been accelerated, removing scans for unused tools, and avoiding making more than one gcc version check.
- Compatibility: In case of unknown encodings, Nuitka was not giving the name of the problematic encoding in the error message. Fixed in 0.5.3.3 already.
- Submodules with the same name as built-in modules were wrongly shadowed. Fixed in 0.5.3.2 already.
- Python3: Added implementations of
is_package
to the meta path based loader. - Python3.4: Added
find_spec
implementation to the meta path based loader for increased compatibility. - Python3: Corrections for
--debug
to work with Python3 and MSVC compiler more often. - Fixed crash with
--show-scons
when no compiler was found. Fixed in 0.5.3.5 already. - Standalone: Need to blacklist
lib2to3
from standard library as well. Fixed in 0.5.3.4 already. - Python3: Adapted to changes in
SyntaxError
on newer Python releases, there is now amsg
that can overridereason
. - Standalone Windows: Preserve
sys.executable
as it might be used to fork binaries. - Windows: The caching of Scons was not arch specific, and files could be
used again, even if changing the arch from
`x86
tox86_64
or back. - Windows: On 32 bit Python it can happen that with large number of generators
running concurrently (>1500), one cannot be started anymore. Raising an
MemoryError
now.
- Added support for MinGW64. Currently needs to be run with
PATH
environment properly set up. - Updated internal version of Scons to 2.3.2, which breaks support for VS 2008, but adds support for VS 2013 and VS 2012. The VS 2013 is now the recommended compiler.
- Added RPM package and repository for RHEL 7.
- The output of
--show-scons
now includes the used compiler, including the MSVC version. - Added option
--msvc
to select the MSVC compiler version to use, which overrides automatic selection of the latest. - Added option
-python-flag=no_warnings
to disable user and deprecation warnings at run time. - Repository for Ubuntu Raring was removed, no more supported by Ubuntu.
- Made technical and logical sharing decisions separate functions and implement them in a dedicated variable registry.
- The Scons file has seen a major cleanup.
This release is mostly a maintenance release. The Scons integrations has been heavily visited, as has been Python3 and esp. Python3.4 compatibility, and results from the now possible debug test runs.
Standalone should be even more practical now, and MinGW64 is an option for those cases, where MSVC is too slow.
This release is mostly a follow up, resolving points that have become possible to resolve after completing the C-ish evolution of Nuitka. So this is more of a service release.
- Improved mode
--improved
now sets error lines more properly than CPython does in many cases. - The
-python-flag=-S
mode now preservesPYTHONPATH
and therefore became usable with virtualenv.
- Line numbers of frames no longer get set unless an exception occurs, speeding up the normal path of execution.
- For standalone mode, using
--python-flag-S
is now always possible and yields less module usage, resulting in smaller binaries and faster compilation.
- Corrected an issue for frames being optimized away where in fact they are still necessary. Issue#140. Fixed in 0.5.2.1 already.
- Fixed handling of exception tests as side effects. These could be remainders of optimization, but didn't have code generation. Fixed in 0.5.2.1 already.
- Previously Nuitka only ever used the statement line as the line number for all the expression, even if it spawned multiple lines. Usually nothing important, and often even more correct, but sometimes not. Now the line number is most often the same as CPython in full compatibility mode, or better, see above. Issue#9.
- Python3.4: Standalone mode for Windows is working now.
- Standalone: Undo changes to
PYTHONPATH
orPYTHONHOME
allowing potentially forked CPython programs to run properly. - Standalone: Fixed import error when using PyQt and Python3.
- For our testing approach, the improved line number handling means we can undo lots of changes that are no more necessary.
- The compile library test has been extended to cover a third potential location
where modules may live, covering the
matplotlib
module as a result.
In Python2, the list contractions used to be re-formulated to be function calls that have no frame stack entry of their own right. This required some special handling, in e.g. closure taking, and determining variable sharing across functions.
This now got cleaned up to be properly in-lined in a
try
/finally
expression.The line number handling got simplified by pushing it into error exits only, removing the need to micro manage a line number stack which got removed.
Use
intptr_t
overunsigned long
to store fiber code pointers, increasing portability.
- Providing own Debian/Ubuntu repositories for all relevant distributions.
- Windows MSI files for Python 3.4 were added.
- Hosting of the web site was moved to metal server with more RAM and performance.
This release brings about structural simplification that is both a follow-up to C-ish, as well as results from a failed attempt to remove static "variable references" and be fully SSA based. It incorporates changes aimed at making this next step in Nuitka evolution smaller.
This is a major release, with huge changes to code generation that improve performance in a significant way. It is a the result of a long development period, and therefore contains a huge jump ahead.
- Added experimental support for Python 3.4, which is still work in progress.
- Added support for virtualenv on MacOS.
- Added support for virtualenv on Windows.
- Added support for MacOS X standalone mode.
- The code generation uses no header files anymore, therefore adding a module doesn't invalidate all compiled object files from caches anymore.
- Constants code creation is now distributed, and constants referenced in a module are declared locally. This means that changing a module doesn't affect the validity of other modules object files from caches anymore.
- C-ish code generation uses less C++ classes and generates more C-like code. Explicit temporary objects are now used for statement temporary variables.
- The constants creation code is no more in a single file, but distributed across all modules, with only shared values created in a single file. This means improved scalability. There are remaining bad modules, but more often, standalone mode is now fast.
- Exception handling no longer uses C++ exception, therefore has become much faster.
- Loops that only break are eliminated.
- Dead code after loops that do not break is now removed.
- The
try
/finally
andtry
/except
constructs are now eliminated, where that is possible. - The
try
/finally
part of the re-formulation forprint
statements is now only done when printing to a file, avoiding useless node tree bloat. - Tuples and lists are now generated with faster code.
- Locals and global variables are now access with more direct code.
- Added support for the anonymous
code
type built-in. - Added support for
compile
built-in. - Generators that statically return immediately, e.g. due to optimization results, are no longer using frame objects.
- The complex call helpers use no pseudo frames anymore. Previous code generation required to have them, but with C-ish code generation that is no more necessary, speeding up those kind of calls.
- Modules with only code that cannot raise, need not have a frame created for them. This avoids useless code size bloat because of them. Previously the frame stack entry was mandatory.
- Windows: The resource files were cached by Scons and re-used, even if the input changed. The could lead to corrupted incremental builds. Issue#129. Fixed in 0.5.1.1 already.
- Windows: For functions with too many local variables, the MSVC failed with an error "C1026: parser stack overflow, program too complex". The rewritten code generation doesn't burden the compiler as much. Issue#127.
- Compatibility: The timing deletion of nested call arguments was different from C++. This shortcoming has been addressed in the rewritten code generation. Issue#62.
- Compatibility: The
__future__
flags andCO_FREECELL
were not present in frame flags. These were then not always properly inherited toeval
andexec
in all cases. - Compatibility: Compiled frames for Python3 had
f_restricted
attribute, which is Python2 only. Removed it. - Compatibility: The
SyntaxError
of having acontinue
in a finally clause is now properly raised. - Python2: The
exec
statement with no locals argument provided, was preventing list contractions to take closure variables. - Python2: Having the ASCII encoding declared in a module wasn't working.
- Standalone: Included the
idna
encoding as well. Issue#135. - Standalone: For virtualenv, the file
orig-prefix.txt
needs to be present, now it's copied into the "dist" directory as well. Issue#126. Fixed in 0.5.1.1 already. - Windows: Handle cases, where Python and user program are installed on different volumes.
- Compatibility: Can now finally use
execfile
as an expression. Issue#5 is finally fixed after all this time thanks to C-ish code generation. - Compatibility: The order or call arguments deletion is now finally compatible. Issue#62 also is finally fixed. This too is thanks to C-ish code generation.
- Compatibility: Code object flags are now more compatible for Python3.
- Standalone: Removing "rpath" settings of shared libraries and extension modules included. This makes standalone binaries more robust on Fedora 20.
- Python2: Wasn't falsely rejecting
unicode
strings as values forint
andlong
variants with base argument provided. - Windows: For Python3.2 and 64 bits, global variable accesses could give false
NameError
exceptions. Fixed in 0.5.1.6 already. - Compatibility: Many
exec
andeval
details have become more correctly, the argument handling is more compatible, and e.g. future flags are now passed along properly. - Compatibility: Using
open
with no arguments is now giving the same error.
- Replying to email from the issue tracker works now.
- Added option name alias
--xml
for--dump-xml
. - Added option name alias
--python-dbg
for--python-debug
, which actually might make it a bit more clear that it is about using the CPython debug run time. - Remove option
--dump-tree
, it had been broken for a long time and unused in favor of XML dumps. - New digital art folder with 3D version of Nuitka logo. Thanks to Juan Carlos for creating it.
- Using "README.rst" instead of "README.txt" to make it look better on web pages.
- More complete whitelisting of missing imports in standard library. These should give no warnings anymore.
- Updated the Nuitka GUI to the latest version, with enhanced features.
- The builds of releases and update of the downloads page is now driven by Buildbot. Page will be automatically updated as updated binaries arrive.
- Temporary keeper variables and the nodes to handle them are now unified with normal temporary variables, greatly simplifying variable handling on that level.
- Less code is coming from templates, more is actually derived from the node tree instead.
- Releasing the references to temporary variables is now always explicit in the node tree.
- The publishing and preservation of exceptions in frames was turned into explicit nodes.
- Exception handling is now done with a single handle that checks with branches on the exception. This eliminates exception handler nodes.
- The
dir
built-in with no arguments is now re-formulated tolocals
orglobals
with their.keys()
attribute taken. - Dramatic amounts of cleanups to code generation specialties, that got done right for the new C-ish code generation.
- Warnings from MSVC are now error exits for
--debug
mode too, expanding the coverage of these tests. - The outputs with
python-dbg
can now also be compared, allowing to expand test coverage for reference counts. - Many of the basic tests are now executable with Python3 directly. This allows for easier debug.
- The library compilation test is now also executed with Python3.
This release would deserve more than a minor number increase. The C-ish code generation, is a huge body of work. In many ways, it lays ground to taking benefit of SSA results, that previously would not have been possible. In other ways, it's incomplete in not yet taking full advantage yet.
The release contains so many improvements, that are not yet fully realized, but as a compiler, it also reflects a stable and improved state.
The important changes are about making SSA even more viable. Many of the problematic cases, e.g. exception handlers, have been stream lined. A whole class of variables, temporary keepers, has been eliminated. This is big news in this domain.
For the standalone users, there are lots of refinements. There is esp. a lot of work to create code that doesn't show scalability issues. While some remain, the most important problems have been dealt with. Others are still in the pipeline.
More work will be needed to take full advantage. This has been explained in a separate post in greater detail.
This release brings corrections and major improvements to how standalone mode performs. Much of it was contributed via patches and bug reports.
- There was a crash when using
next
on a non-iterable. Fixed in 0.5.0.1 already. - Module names with special characters not allowed in C identifiers were not fully supported. Issue#118. Fixed in 0.5.0.1 already.
- Name mangling for classes with leading underscores was not removing them from
resulting attribute names. This broke at
__slots__
with private attributes for such classes. Issue#119. Fixed in 0.5.0.1 already. - Standalone on Windows might need "cp430" encoding. Issue#120. Fixed in 0.5.0.2 already.
- Standalone mode didn't work with
lxml.etree
due to lack of hard coded dependencies. When a shared library imports things, Nuitka cannot detect it easily. - Wasn't working on MacOS 64 bits due to using Linux 64 bits specific code. Issue#123. Fixed in 0.5.0.2 already.
- On MinGW the constants blob was not properly linked on some installations, this is now done differently (see below).
- Memory usages are now traced with
--show-progress
allowing us to trace where things go wrong.
- Standalone mode now includes standard library as bytecode by default. This is workaround scalability issues with many constants from many modules. Future releases are going to undo it.
- On Windows the constants blob is now stored as a resource, avoiding compilation via C code for MSVC as well. MinGW was changed to use the same code.
- Expanded test coverage for "standalone mode" demonstrating usage of "hex" encoding, PySide, and PyGtk packages.
This release is mostly an interim maintenance release for standalone. Major changes that provide optimization beyond that, termed "C-ish code generation" are delayed for future releases.
This release makes standalone practical which is an important point. Instead of hour long compilation, even for small programs, we are down to less than a minute.
The solution of the scalability issues with many constants from many modules will be top priority going forward. Since they are about how even single use constants are created all in one place, this will be easy, but as large changes are happening in "C-ish code generation", we are waiting for these to complete.
This release breaks interface compatibility, therefore the major version number change. Also "standalone mode" has seen significant improvements on both Windows, and Linux. Should work much better now.
But consider that this part of Nuitka is still in its infancy. As it is not the top priority of mine for Nuitka, which primarily is intended as an super compatible accelerator of Python, it will continue to evolve nearby.
There is also many new optimization based on structural improvements in the direction of actual SSA.
The "standalone mode" was not working on all Redhat, Fedora, and openSUSE platforms and gave warnings with older compilers. Fixed in 0.4.7.1 already.
The "standalone mode" was not including all useful encodings. Issue#116. Fixed in 0.4.7.2 already.
The "standalone mode" was defaulting to
--python-flag=-S
which disables the parsing of "site" module. That unfortunately made it necessary to reach some modules without modifyingPYTHONPATH
which conflicts with the "out-of-the-box" experience.The "standalone mode" is now handling packages properly and generally working on Windows as well.
The syntax error of having an all catching except clause and then a more specific one wasn't causing a
SyntaxError
with Nuitka.try: something() except: somehandling(): except TypeError: notallowed()
A corruption bug was identified, when re-raising exceptions, the top entry of the traceback was modified after usage. Depending on
malloc
this was potentially causing an endless loop when using it for output.
Windows: The "standalone" mode now properly detects used DLLs using Dependency Walker which it offers to download and extra for you.
It is used as a replacement to
ldd
on Linux when building the binary, and as a replacement ofstrace
on Linux when running the tests to check that nothing is loaded from the outside.
When iterating over
list
,set
, this is now automatically lowered totuples
avoiding the mutable container types.So the following code is now equivalent:
for x in [ a, b, c ]: ... # same as for x in (a, b, c): ...
For constants, this is even more effective, because for mutable constants, no more is it necessary to make a copy.
Python2: The iteration of large
range
is now automatically lowered toxrange
which is faster to loop over, and more memory efficient.Added support for the
xrange
built-in.The statement only expression optimization got generalized and now is capable of removing useless parts of operations, not only the whole thing when it has not side effects.
[a,b] # same as a b
This works for all container types.
Another example is
type
built-in operation with single argument. When the result is not used, it need not be called.type(a) # same as a
And another example
is
andis not
have no effect of their own as well, therefore:a is b # same as a b
Added proper handling of conditional expression branches in SSA based optimization. So far these branches were ignored, which only acceptable for temporary variables as created by tree building, but not other variable types. This is preparatory for introducing SSA for local variables.
- The option
--exe
is now ignored and creating an executable is the default behavior ofnuitka
, a new option--module
allows to produce extension modules. - The binary
nuitka-python
was removed, and is replaced bynuitka-run
with now only implies--execute
on top of whatnuitka
is. - Using dedicated Buildbot for continuous integration testing and release creation as well.
- The Downloads now offers MSI files for Win64 as well.
- Discontinued the support for cross compilation to Win32. That was too limited and the design choice is to have a running CPython instance of matching architecture at Nuitka compile time.
- Expanded test coverage for "standalone mode" demonstrating usage of "hex" encoding, and PySide package.
The "executable by default" interface change improves on the already high ease of use. The new optimization do not give all that much in terms of numbers, but are all signs of structural improvements, and it is steadily approaching the point, where the really interesting stuff will happen.
The progress for standalone mode is of course significant. It is still not quite there yet, but it is making quick progress now. This will attract a lot of attention hopefully.
As for optimization, the focus for it has shifted to making exception handlers work optimal by default (publish the exception to sys.exc_info() and create traceback only when necessary) and be based on standard branches. Removing special handling of exception handlers, will be the next big step. This release includes some correctness fixes stemming from that work already.
This release includes important new features, lots of polishing cleanups, and some important performance improvements as well.
- The RPM packages didn't build due to missing in-line copy of Scons. Fixed in 0.4.6.1 already.
- The recursion into modules and unfreezing them was not working for packages and modules anymore. Fixed in 0.4.6.2 already.
- The Windows installer was not including Scons. Fixed in 0.4.6.3 already.
- Windows: The immediate execution as performed by
nuitka --execute
was not preserving the exit code. Issue#26. - Python3.3: Packages without
__init.py__
were not properly embedding the name-space package as well. - Python3: Fix, modules and packages didn't add themselves to
sys.modules
which they should, happened only for programs. - Python3.3: Packages should set
__package
to their own name, not the one of their parents. - Python3.3: The
__qualname__
of nested classes was corrected. - For modules that recursed to other modules, an infinite loop could be triggered when comparing types with rich comparisons. Issue#115.
The "standalone" mode allows to compile standalone binaries for programs and run them without Python installation. The DLLs loaded by extension modules on Windows need to be added manually, on Linux these are determined automatically already.
To achieve running without Python installation, Nuitka learned to freeze bytecode as an alternative to compiling modules, as some modules need to be present when the CPython library is initialized.
New option
--python-flag
allows to specify flags to the compiler that the "python" binary normally would. So far-S
and-v
are supported, with sane aliasesno_site
andtrace_imports
.The recommended use of
--python-flag=-S
is to avoid dependency creep in standalone mode compilations, because thesite
module often imports many useless things that often don't apply to target systems.
- Faster frame stack handling for functions without
try
/except
(ortry
/finally
in Python3). This gives a speed boost to "PyStone" of ca. 2.5% overall. - Python2: Faster attribute getting and setting, handling special cases at compile time. This gives a minor speed boost to "PyStone" of ca. 0.5% overall.
- Python2: Much quicker calls of
__getattr__
and__setattr__
as this is now using the quicker call method avoiding temporary tuples. - Don't treat variables usages used in functions called directly by their owner as shared. This leads to more efficient code generation for contractions and class bodies.
- Create
unicode
constants directly from their UTF-8 string representation for Python2 as well instead of un-streaming. So far this was only done for Python3. Affects only program start-up. - Directly create
int
andlong
constants outside of2**31
and2**32-1
, but only limited according to actual platform values. Affects only program start-up. - When creating
set
values, no longer use a temporarytuple
value, but use a properly generated helper functions instead. This makes creating sets much faster. - Directly create
set
constants instead of un-streaming them. Affects only program start-up. - For correct line numbers in traceback, the current frame line number must be updated during execution. This was done more often than necessary, e.g. loops set the line number before loop entry, and at first statement.
- Module variables are now accessed even faster, the gain for "PyStone" is only 0.1% and mostly the result of leaner code.
- The "standalone mode" code (formerly known as "portable mode" has been redone and activated. This is a feature that a lot of people expect from a compiler naturally. And although the overall goal for Nuitka is of course acceleration, this kind of packaging is one of the areas where CPython needs improvement.
- Added package for Ubuntu 13.10 for download, removed packages for Ubuntu 11.04 and 11.10, no more supported.
- Added package for openSUSE 13.1 for download.
- Nuitka is now part of Arch and can be installed with
pacman -S nuitka
. - Using dedicated Buildbot for continuous integration testing. Not yet public.
- Windows: In order to speed up repeated compilation on a platform without
ccache
, added Scons level caching in the build directory. - Disabled hash randomization for inside Nuitka (but not in ultimately created
binaries) for a more stable output, because dictionary constants will not
change around. This makes the build results possible to cache for
ccache
and Scons as well.
- The
programs
tests cases now fail if module or directory recursion is not working, being executed in another directory. - Added test runner for packages, with initial test case for package with recursion and sub-packages.
- Made some test cases more strict by reducing
PYTHONPATH
provision. - Detect use of extra flags in tests that don't get consumed avoiding ineffective flags.
- Use
--execute
on Windows as well, the issue that prevented it has been solved after all.
- The generated code uses
const_
,var_
,par_
prefixes in the generated code and centralized the decision about these into single place. - Module variables no longer use C++ classes for their access, but instead accessor functions, leading to much less code generated per module variable and removing the need to trace their usage during code generation.
- The test runners now share common code in a dedicated module, previously they replicated it all, but that turned out to be too tedious.
- Massive general cleanups, many of which came from new contributor Juan Carlos Paco.
- Moved standalone and freezer related codes to dedicated package
nuitka.freezer
to not pollute thenuitka
package name space. - The code generation use variable identifiers and their accesses was cleaned up.
- Removed several not-so-special case identifier classes because they now behave more identical and all work the same way, so a parameters can be used to distinguish them.
- Moved main program, function object, set related code generation to dedicated modules.
This release marks major technological progress with the introduction of the much sought standalone mode and performance improvements from improved code generation.
The major break through for SSA optimization was not yet achieved, but this is again making progress in the direction of it. Harmonizing variables of different kinds was an important step ahead.
Also very nice is the packaging progress, Nuitka was accepted into Arch after being in Debian Testing for a while already. Hope is to see more of this kind of integration in the future.
This release includes progress on all fronts. The primary focus was to advance SSA optimization over older optimization code that was already in place. In this domain, there are mostly cleanups.
Another focus has been to enhance Scons with MSVC on Windows. Nuitka now finds an installed MSVC compiler automatically, properly handles architecture of Python and Windows. This improves usability a lot.
Then this is also very much about bug fixes. There have been several hot fixes for the last release, but a complicated and major issue forced a new release, and many other small issues.
And then there is performance. As can be seen in the performance graph, this release is the fastest so far. This came mainly from examining the need for comparison slots for compiled types.
And last, but not least, this also expands the base of supported platforms, adding Gentoo, and self compiled Python to the mix.
Support Nuitka being installed to a path that contains spaces and handle main programs with spaces in their paths. Issue#106. Fixed in 0.4.5.1 already.
Support Python being installed to a path that contains spaces. Issue#106. Fixed in 0.4.5.2 already.
Windows: User provided constants larger than 65k didn't work with MSVC. Issue#108. Fixed in 0.4.5.3 already.
Windows: The option
--windows-disable-console
was not effective with MSVC. Issue#107. Fixed in 0.4.5.3 already.Windows: For some users, Scons was detecting their MSVC installation properly already from registry, but it didn't honor the target architecture. Issue#99. Fixed in 0.4.5.3 already.
When creating Python modules, these were marked as executable ("x" bit), which they are of course not. Fixed in 0.4.5.3 already.
Python3.3: On architectures where
Py_ssize_t
is not the same aslong
this could lead to errors. Fixed in 0.4.5.3 already.Code that was using nested mutable constants and changed the nested ones was not executing correctly. Issue#112.
Python2: Due to list contractions being re-formulated as functions,
del
was rejected for the variables assigned in the contraction. Issue#111.[ expr(x) for x in iterable() ] del x # Should work, was gave an unjustified SyntaxError.
Compiled types when used in Python comparison now work. Code like this will work:
def f(): pass assert type(f) == types.FunctionType
This of course also works for
in
operator, and is another step ahead in compatibility, and surprising too. And best of all, this works even if the checking code is not compiled with Nuitka.Windows: Detecting MSVC installation from registry, if no compiler is already present in PATH.
Windows: Now options
--mingw
to force compilation with MinGW.
- Rich comparisons (
==
,<
, and the like) are now faster than ever before due to a full implementation of its own in Nuitka that eliminates a bit of the overhead. In the future, we will aim at giving it type hints to make it even faster. This gives a minor speed boost to PyStone of ca. 0.7% overall. - Integer comparisons are now treated preferably, as they are in CPython, which gives 1.3% speed boost to CPython.
- The SSA based analysis is now used to provide variable scopes for temporary variables as well as reference count needs.
- Replaced "value friend" based optimization code with SSA based optimization,
which allowed to remove complicated and old code that was still used mainly in
optimization of
or
andand
expressions. - Delayed declaration of temp variables and their reference type is now performed based on information from SSA, which may given more accurate results. Not using "variable usage" profiles for this anymore.
- The Scons interface and related code got a massive overhaul, making it more consistent and better documented. Also updated the internal copy to 2.3.0 for the platforms that use it, mostly Windows.
- Stop using
os.system
andsubprocess.call(..., shell = True)
as it is not really portable at all, usesubprocess.call(..., shell = False)
instead. - As usual lots of cleanups related to line length issues and PyLint.
- Added support for Gentoo Linux.
- Added support for self compiled Python versions with and without debug enabled. Issue#110
- Added use of Nuitka fonts for headers in manuals.
- Does not install in-line copy of Scons only on systems where it is not going to be used, that is mostly non-Windows, and Linux where it is not already present. This makes for cleaner RPM packages.
While the SSA stuff is not yet bearing performance fruits, it starts to carry weight. Taking over the temporary variable handling now also means we can apply the same stuff to local variables later.
To make up for the delay in SSA driven performance improvements, there is more traditional code acceleration for rich comparisons, making it significant, and the bug fixes make Nuitka more compatible than ever.
So give this a roll, it's worth it. And feel free to join the mailing list or make a donation to support Nuitka.
This release incorporates very many bug fixes, most of which were already part of hot fixes, usability improvements, documentation improvements, new logo, simpler Python3 on Windows, warnings for recursion options, and so on. So it's mostly a consolidation release.
- When targeting Python 3.x, Nuitka was using "python" to run Scons to run it under Python 2.x, which is not good enough on systems, where that is already Python3. Improved to only do the guessing where necessary (i.e. when using the in-line copy of Scons) and then to prefer "python2". Issue#95. Fixed in 0.4.4.1 already.
- When using Nuitka created binaries inside a "virtualenv", created programs
would instantly crash. The attempt to load and patch
inspect
module was not making sure thatsite
module was already imported, but inside the "virtualenv", it cannot be found unless. Issue#96. Fixed in 0.4.4.1 already. - The option
--recurse-directory
to include plugin directories was broken. Issue#97. Fixed in 0.4.4.2 already. - Python3: Files with "BOM" marker causes the compiler to crash. Issue#98. Fixed in 0.4.4.2 already.
- Windows: The generated code for
try
/return
/finally
was working with gcc (and therefore MinGW), but not with MSVC, causing crashes. Issue#102. Fixed in 0.4.4.2 already. - The option
--recurse-all
did not recurse to package__init__.py
files in casefrom x.y import z
syntax was used. Issue#100. Fixed in 0.4.4.2 already. - Python3 on MacOS: Corrected link time error. Fixed in 0.4.4.2 already.
- Python3.3 on Windows: Fixed crash with too many arguments to a kwonly argument using function. Fixed in 0.4.4.2 already.
- Python3.3 on Windows: Using "yield from" resulted in a link time error. Fixed in 0.4.4.2 already.
- Windows: Added back XML manifest, found a case where it is needed to prevent clashes with binary modules.
- Windows: Generators only worked in the main Python threads. Some unusual threading modules therefore failed.
- Using
sys.prefix
to find the Python installation instead of hard coded paths. Issue#103.
Windows: Python3 finds Python2 installation to run Scons automatically now.
Nuitka itself runs under Python3 just fine, but in order to build the generated C++ code into binaries, it uses Scons which still needs Python2.
Nuitka will now find the Python2 installation searching Windows registry instead of requiring hard coded paths.
Windows: Python2 and Python3 find their headers now even if Python is not installed to specific paths.
The installation path now is passed on to Scons which then uses it.
Better error checking for
--recurse-to
and--recurse-not-to
arguments, tell the user not to use directory paths.Added a warning for
--recurse-to
arguments that end up having no effect to the final result.
- Import mechanism got cleaned up, stopped using "PyImport_ExtendInittab". It
does not handle packages, and the
sys.meta_path
based importer is now well proven. - Moved some of the constraint collection code mess into proper places. It still remains a mess.
- Added
LICENSE.txt
file with Apache License 2.0 text to make it more immediately obvious which license Nuitka is under. - Added section about Nuitka license to the "User Manual".
- Added Nuitka Logo to the distribution.
- Use Nuitka Logo as the bitmap in the Windows installer.
- Use Nuitka Logo in the documentation ("User Manual" and "Developer Manual").
- Enhanced documentation to number page numbers starting after table of contents, removed header/footer from cover pages.
This release is mostly the result of improvements made based on the surge of users after Europython 2013. Some people went to extents and reported their experience very detailed, and so I could aim at making e.g. their misconceptions about how recursion options work, more obvious through warnings and errors.
This release is not addressing performance improvements. The next release will be able to focus on that. I am taking my claim of full compatibility very serious, so any time it's broken, it's the highest priority to restore it.
This release marks the point, where Nuitka for the first time supports all major current Python versions and all major features. It adds Python 3.3 support and it adds support for threading. And then there is a massive amount of fixes that improve compatibility even further.
Aside of that, there is major performance work. One side is the optimization of call performance (to CPython non-compiled functions) and to compiled functions, both. This gave a serious improvement to performance.
Then of course, we are making other, long term performance progress, as in "--experimental" mode, the SSA code starts to optimize unused code away. That code is not yet ready for prime time yet, but the trace structure will hold.
Python3.3 support.
The test suite of CPython3.3 passes now too. The
yield from
is now supported, but the improved argument parsing error messages are not implemented yet.Tracing user provided constants, now Nuitka warns about too large constants produced during optimization.
Line numbers of expressions are now updates as evaluation progresses. This almost corrects.
Finally improves Issue#9. Now only expression parts that cannot raise, do not update, which can still cause difference, but much less often, and then definitely useless.
Experimental support for threads.
Threading appears to work just fine in the most cases. It's not as optimal as I wanted it to be, but that's going to change with time.
Previous corrections for
==
,!=
, and<=
, caused a performance regression for these operations in case of handling identical objects.For built-in objects of sane types (not
float
), these operations are now accelerated again. The overreaching acceleration of>=
was still there (bug, see below) and has been adapted too.Calling non-compiled Python functions from compiled functions was slower than in CPython. It is now just as fast.
Calling compiled functions without keyword arguments has been accelerated with a dedicated entry point that may call the implementation directly and avoid parameter parsing almost entirely.
Making calls to compiled and non-compiled Python functions no longer requires to build a temporary tuple and therefore is much faster.
Parameter parsing code is now more compact, and re-uses error raises, or creates them on the fly, instead of hard coding it. Saves binary size and should be more cache friendly.
Corrected false optimization of
a >= a
on C++ level.When it's not done during Nuitka compile time optimization, the rich comparison helper still contained short cuts for
>=
. This is now the same for all the comparison operators.Calling a function with default values, not providing it, and not providing a value for a value without default, was not properly detecting the error, and instead causing a run time crash.
def f(a, b = 2): pass f(b = 2)
This now properly raises the
TypeError
exception.Constants created with
+
could become larger than the normally enforced limits. Not as likely to become huge, but still potentially an issue.The
vars
built-in, when used on something without__dict__
attribute, was givingAttributeError
instead ofTypeError
.When re-cursing to modules at compile time, script directory and current directory were used last, while at run time, it was the other way around, which caused overloaded standard library modules to not be embedded. Corrects Issue#94.
Thanks for the patch to James Michael DuPont.
Super without arguments was not raising the correct
RuntimeError
exception in functions that cannot be methods, butUnboundLocalError
instead.def f(): super() # Error, cannot refer to first argument of f
Generators no longer use
raise StopIteration
for return statements, because that one is not properly handled intry
/except
clauses, where it's not supposed to trigger, whiletry
/finally
should be honored.Exception error message when throwing non-exceptions into generators was not compatible.
The use of
return
with value in generators is aSyntaxError
before Python3.3, but that was not raised.Variable names of the "__var" style need to be mangled. This was only done for classes, but not for functions contained in classes, there they are now mangled too.
Python3: Exceptions raised with causes were not properly chaining.
Python3: Specifying the file encoding corrupted line numbers, making them all of by one.
For containers (
tuple
,list
,set
,dict
) defined on the source code level, Nuitka immediately created constant references from them.For function calls, class creations, slice objects, this code is now re-used, and its dictionaries and tuples, may now become constants immediately, reducing noise in optimization steps.
The parameter parsing code got cleaned up. There were a lot of relics from previously explored paths. And error raises were part of the templates, but now are external code.
Global variable management moved to module objects and out of "Variables" module.
Make sure, nodes in the tree are not shared by accident.
This helped to find a case of duplicate use in the complex call helpers functions. Code generation will now notice this kind of duplication in debug mode.
The complex call helper functions were manually taking variable closure, which made these functions inconsistent to other functions, e.g. no variable version was allocated to assignments.
Removing the manual setting of variables allowed a huge reduction of code volume, as it became more generic code.
Converting user provided constants to create containers into constants immediately, to avoid noise from doing this in optimization.
The
site
module is now imported explicitly in the__main__
module, so it can be handled by the recursion code as well. This will help portable mode.Many line length 80 changes, improved comments.
- The CPython3.3 test suite was added, and run with both Python3.2 and Python3.3, finding new bugs.
- The
doctest
to code generation didn't successfully handle all tests, most notably, "test_generators.py" was giving aSyntaxError
and therefore not actually active. Correcting that improved the coverage of generator testing.
The portable code is still delayed.
Support for Python3.3 was a higher priority, but the intention is to get it into shape for Europython still.
Added notes about it being disabled it in the "User Manual" documentation.
This release is in preparation for Europython 2013. Wanted to get this much out, as it changes the status slides quite a bit, and all of that was mostly done in my Cyprus holiday a while ago.
The portable code has not seen progress. The idea here is to get this into a development version later.
This release expands the reach of Nuitka substantially, as new platforms and compilers are now supported. A lot of polish has been applied. Under the hood there is the continued and in-progress effort to implement SSA form in Nuitka.
Support for new compiler: Microsoft Visual C++.
You can now use Visual Studio 2008 or Visual Studio 2010 for compiling under Windows.
Support for NetBSD.
Nuitka works for at least NetBSD 6.0, older versions may or may not work. This required fixing bugs in the generic "fibers" implementation.
Support for Python3 under Windows too.
Nuitka uses Scons to build the generated C++ files. Unfortunately it requires Python2 to execute, which is not readily available to call from Python3. It now guesses the default installation paths of CPython 2.7 or CPython 2.6 and it will use it for running Scons instead. You have to install it to
C:\Python26
orC:\Python27
for Nuitka to be able to find it.Enhanced Python 3.3 compatibility.
The support the newest version of Python has been extended, improving compatibility for many minor corner cases.
Added warning when a user compiles a module and executes it immediately when that references
__name__
.Because very likely the intention was to create an executable. And esp. if there is code like this:
if __name__ == "__main__": main()
In module mode, Nuitka will optimize it away, and nothing will happen on execution. This is because the command
nuitka --execute module
is behavioral more like
python -c "import module"
and that was a trap for new users.
All Linux architectures are now supported. Due to changes in how evaluation order is enforced, we don't have to implement for specific architectures anymore.
Dictionary creation was not fully compatible.
As revealed by using Nuitka with CPython3.3, the order in which dictionaries are to be populated needs to be reversed, i.e. CPython adds the last item first. We didn't observe this before, and it's likely the new dictionary implementation that finds it.
Given that hash randomization makes dictionaries item order undetermined anyway, this is more an issue of testing.
Evaluation order for arguments of calls was not effectively enforced. It is now done in a standards compliant and therefore fully portable way. The compilers and platforms so far supported were not affected, but the newly supported Visual Studio C++ compiler was.
Using a
__future__
import inside a function was giving an assertion, instead of the proper syntax error.Python3: Do not set the attributes
sys.exc_type
,sys.exc_value
,sys.exc_traceback
.Python3: Annotations of function worked only as long as their definition was not referring to local variables.
Calls with no positional arguments are now using the faster call methods.
The generated C++ code was using the
()
constant at call site, when doing calls that use no positional arguments, which is of course useless.For Windows now uses OS "Fibers" for Nuitka "Fibers".
Using threads for fibers was causing only overhead and with this API, MSVC had less issues too.
- Accepting Donations via Paypal, please support funding travels, website, etc.
- The "User Manual" has been updated with new content. We now do support Visual Studio, documented the required LLVM version for clang, Win64 and modules may include modules too, etc. Lots of information was no longer accurate and has been updated.
- The Changelog has been improved for consistency, wordings, and styles.
- Nuitka is now available on the social code platforms as well
- Removed "clean-up.sh", which is practically useless, as tests now clean up
after themselves reasonably, and with
git clean -dfx
working better. - Removed "create-environment.sh" script, which was only setting the
PATH
variable, which is not necessary. - Added
check-with-pylint --emacs
option to make output its work with Emacs compilation mode, to allow easier fixing of warnings from PyLint. - Documentation is formatted for 80 columns now, source code will gradually aim at it too. So far 90 columns were used, and up to 100 tolerated.
Removed useless manifest and resource file creation under Windows.
Turns out this is no longer needed at all. Either CPython, MinGW, or Windows improved to no longer need it.
PyLint massive cleanups and annotations bringing down the number of warnings by a lot.
Avoid use of strings and built-ins as run time pre-computed constants that are not needed for specific Python versions, or Nuitka modes.
Do not track needed tuple, list, and dict creation code variants in context, but e.g. in
nuitka.codegen.TupleCodes
module instead.Introduced an "internal" module to host the complex call helper functions, instead of just adding it to any module that first uses it.
- Added basic tests for order evaluation, where there currently were None.
- Added support for "2to3" execution under Windows too, so we can run tests for Python3 installations too.
The release is clearly major step ahead. The new platform support triggered a whole range of improvements, and means this is truly complete now.
Also there is very much polish in this release, reducing the number of warnings, updated documentation, the only thing really missing is visible progress with optimization.
This release comes with many bug fixes, some of which are severe. It also contains new features, like basic Python 3.3 support. And the performance diagrams got expanded.
Support for FreeBSD.
Nuitka works for at least FreeBSD 9.1, older versions may or may not work. This required only fixing some "Linuxisms" in the build process.
New option for warning about compile time detected exception raises.
Nuitka can now warn about exceptions that will be raised at run time.
Basic Python3.3 support.
The test suite of CPython3.2 passes and fails in a compatible way. New feature
yield from
is not yet supported, and the improved argument parsing error messages are not implemented yet.
Nuitka already supported compilation of "main directories", i.e. directories with a "__main__.py" file inside. The resulting binary name was "__main__.exe" though, but now it is "directory.exe"
# ls directory __main__.py # nuitka --exe directory # ls directory directory.exe
This makes this usage more obvious, and fixes the older issue Issue#49 for this feature.
Evaluation order of binary operators was not enforced.
Nuitka already enforces evaluation order for just about everything. But not for binary operators it seems. Corrects Issue#61.
Providing an
# coding: no-exist
was crashing under Python2, and ignored under Python3, now it does the compatible thing for both.Global statements on the compiler level are legal in Python, and were not handled by Nuitka, they now are.
global a # Not in a function, but on module level. Pointless but legal! a = 1
Effectively these statements can be ignored. Corrects part of Issue#65.
Future imports are only legal when they are at the start of the file. This was not enforced by Nuitka, making it accept code, which CPython would reject. It now properly raises a syntax error. Corrects part of Issue#65.
Raising exceptions from context was leaking references.
raise ValueError() from None
Under CPython3.2 the above is not allowed (it is acceptable starting CPython3.3), and was also leaking references to its arguments. Corrects Issue#76.
Importing the module that became
__main__
through the module name, didn't recurse to it.This also gives a warning. PyBench does it, and then stumbles over the non-found "pybench" module. Of course, programmers should use
sys.modules[ "__main__" ]
to access main module code. Not only because the duplicated modules don't share data. Corrects Issue#68.Compiled method
repr
leaked references when printed.When printing them, they would not be freed, and subsequently hold references to the object (and class) they belong to. This could trigger bugs for code that expects
__del__
to run at some point. Corrects Issue#81.The
super
built-in leaked references to given object.This was added, because Python3 needs it. It supplies the arguments to
super
automatically, whereas for Python2 the programmer had to do it. And now it turns out that the object lost a reference, causing similar issues as above, preventing__del__
to run. Corrects Issue#81.The
raise
statement didn't enforce type of third argument.This Python2-only form of exception raising now checks the type of the third argument before using it. Plus, when it's None (which is also legal), no reference to None is leaked.
Python3 built-in exceptions were strings instead of exceptions.
A gross mistake that went uncaught by test suites. I wonder how. Them being strings doesn't help their usage of course, fixed. Corrects Issue#82.
The
-nan
andnan
both exist and make a difference.A older story continued. There is a sign to
nan
, which can be copied away and should be present. This is now also supported by Nuitka. Corrects Issue#75.Wrong optimization of
a == a
,a != a
,a <= a
on C++ level.While it's not done during Nuitka optimization, the rich comparison helpers still contained short cuts for
==
,!=
, and<=
.The
sys.executable
fornuitka-python --python-version 3.2
was stillpython
.When determining the value for
sys.executable
the CPython library code looks at the nameexec
had received. It waspython
in all cases, but now it depends on the running version, so it propagates.Keyword only functions with default values were loosing references to defaults.
def f(*, a = X()) pass f() f() # Can crash, X() should already be released.
This is now corrected. Of course, a Python3 only issue.
Pressing CTRL-C didn't generate
KeyboardInterrupt
in compiled code.Nuitka never executes "pending calls". It now does, with the upside, that the solution used, appears to be suitable for threading in Nuitka too. Expect more to come out of this.
For
with
statements withreturn
,break
, orcontinue
to leave their body, the__exit__
was not called.with a: # This called a.__enter__(). return 2 # This didn't call a.__exit__(None, None, None).
This is of course quite huge, and unfortunately wasn't covered by any test suite so far. Turns out, the re-formulation of
with
statements, was wrongly usingtry/except/else
, but these ignore the problematic statements. Onlytry/finally
does. The enhanced re-formulation now does the correct thing. Corrects Issue#59.Starting with Python3, absolute imports are now the default.
This was already present for Python3.3, and it turns out that all of Python3 does it.
Constants are now much less often created with
pickle
module, but created directly.This esp. applies for nested constants, now more values become
is
identical instead of only==
identical, which indicates a reduced memory usage.a = ("something_special",) b = "something_special" assert a[0] is b # Now true
This is not only about memory efficiency, but also about performance. Less memory usage is more cache friendly, and the "==" operator will be able to shortcut dramatically in cases of identical objects.
Constants now created without
pickle
usage, coverfloat
,list
, anddict
, which is enough for PyStone to not use it at all, which has been added support for as well.Continue statements might be optimized away.
A terminal
continue
in a loop, was not optimized away:while 1: something continue # Now optimized away
The trailing
continue
has no effect and can therefore be removed.while 1: something
Loops with only break statements are optimized away.
while 1: break
A loop immediately broken has of course no effect. Loop conditions are re-formulated to immediate "if ... : break" checks. Effectively this means that loops with conditions detected to be always false to see the loop entirely removed.
- Added tests for the found issues.
- Running the programs test suite (i.e. recursion) for Python3.2 and Python3.2 as well, after making adaptation so that the absolute import changes are now covered.
- Running the "CPython3.2" test suite with Python3.3 based Nuitka works and found a few minor issues.
The Downloads page now offers RPMs for RHEL6, CentOS6, F17, F18, and openSUSE 12.1, 12.2, 12.3. This large coverage is thanks to openSUSE build service and "ownssh" for contributing an RPM spec file.
The page got improved with logos for the distributions.
Added "ownssh" as contributor.
Revamped the "User Manual" in terms of layout, structure, and content.
This release is the result of much validation work. The amount of fixes the largest of any release so far. New platforms, basic Python3.3 support, consolidation all around.
This release is the first follow-up with a focus on optimization. The major highlight is progress towards SSA form in the node tree.
Also a lot of cleanups have been performed, for both the tree building, which is now considered mostly finished, and will be only reviewed. And for the optimization part there have been large amounts of changes.
Python 3.3 experimental support
- Now compiles many basic tests. Ported the dictionary quick access and update code to a more generic and useful interface.
- Added support for
__qualname__
to classes and functions. - Small compatibility changes. Some exceptions changed, absolute imports are now default, etc.
- For comparison tests, the hash randomization is disabled.
Python 3.2 support has been expanded.
The Python 3.2 on Ubuntu is not providing a helper function that was used by Nuitka, replaced it with out own code.
Default values were not "is" identical.
def defaultKeepsIdentity(arg = "str_value"): print arg is "str_value" defaultKeepsIdentity()
This now prints "True" as it does with CPython. The solution is actually a general code optimization, see below. Issue#55
Usage of
unicode
built-in with more than one argument could corrupt the encoding argument string.An implementation error of the
unicode
was releasing references to arguments converted to default encoding, which could corrupt it.Assigning Python3 function annotations could cause a segmentation fault.
Improved propagation of exception raise statements, eliminating more code. They are now also propagated from all kinds of expressions. Previously this was more limited. An assertion added will make sure that all raises are propagated. Also finally, raise expressions are converted into raise statements, but without any normalization.
# Now optimizing: raise TypeError, 1/0 # into (minus normalization): raise ZeroDivisionError, "integer division or modulo by zero" # Now optimizing: (1/0).something # into (minus normalization): raise ZeroDivisionError, "integer division or modulo by zero" # Now optimizing: function(a, 1/0).something # into (minus normalization), notice the side effects of first checking # function and a as names to be defined, these may be removed only if # they can be demonstrated to have no effect. function a raise ZeroDivisionError, "integer division or modulo by zero"
There is more examples, where the raise propagation is new, but you get the idea.
Conditional expression nodes are now optimized according to the truth value of the condition, and not only for compile time constants. This covers e.g. container creations, and other things.
# This was already optimized, as it's a compile time constant. a if ("a",) else b a if True else b # These are now optimized, as their truth value is known. a if (c,) else b a if not (c,) else b
This is simply taking advantage of infrastructure that now exists. Each node kind can overload "getTruthValue" and benefit from it. Help would be welcome to review which ones can be added.
Function creations only have side effects, when their defaults or annotations (Python3) do. This allows to remove them entirely, should they be found to be unused.
Code generation for constants now shares element values used in tuples.
The general case is currently too complex to solve, but we now make sure constant tuples (as e.g. used in the default value for the compiled function), and string constants share the value. This should reduce memory usage and speed up program start-up.
- Optimization was initially designed around visitors that each did one thing, and did it well. It turns out though, that this approach is unnecessary, and constraint collection, allows for the most consistent results. All remaining optimization has been merged into constraint collection.
- The names of modules containing node classes were harmonized to always be plural. In the beginning, this was used to convey the information that only a single node kind would be contained, but that has long changed, and is unimportant information.
- The class names of nodes were stripped from the "CPython" prefix. Originally the intent was to express strict correlation to CPython, but with increasing amounts of re-formulations, this was not used at all, and it's also not important enough to dominate the class name.
- The re-formulations performed in tree building have moved out of the "Building" module, into names "ReformulationClasses" e.g., so they are easier to locate and review. Helpers for node building are now in a separate module, and generally it's much easier to find the content of interest now.
- Added new re-formulation of
print
statements. The conversion to strings is now made explicit in the node tree.
- Added test to cover default value identity.
- The upload of Nuitka to PyPI has been repaired and now properly displays project information again.
The quicker release is mostly a consolidation effort, without actual performance progress. The progress towards SSA form matter a lot on the outlook front. Once this is finished, standard compiler algorithms can be added to Nuitka which go beyond the current peephole optimization.
This release brings massive progress on all fronts. The big highlight is of course: Full Python3.2 support. With this release, the test suite of CPython3.2 is considered passing when compiled with Nuitka.
Then lots of work on optimization and infrastructure. The major goal of this release was to get in shape for actual optimization. This is also why for the first time, it is tested that some things are indeed compile time optimized to spot regressions easier. And we are having performance diagrams, even if weak ones:
- Python3.2 is now fully supported.
- Fully correct
metaclass =
semantics now correctly supported. It had been working somewhat previously, but now all the corner cases are covered too. - Keyword only parameters.
- Annotations of functions return value and their arguments.
- Exception causes, chaining, automatic deletion of exception handlers
as
values. - Added support for starred assigns.
- Unicode variable names are also supported, although it's of course ugly, to find a way to translate these to C++ ones.
- Fully correct
Checking compiled code with
instance(some_function, types.FunctionType)
as "zope.interfaces" does, was causing compatibility problems. Now this kind of check passes for compiled functions too. Issue#53The frame of modules had an empty locals dictionary, which is not compatible to CPython which puts the globals dictionary there too. Also discussed in Issue#53
For nested exceptions and interactions with generator objects, the exceptions in "sys.exc_info()" were not always fully compatible. They now are.
The
range
builtin was not raising exceptions if given arguments appeared to not have side effects, but were still illegal, e.g.range([], 1, -1)
was optimized away if the value was not used.Don't crash on imported modules with syntax errors. Instead, the attempted recursion is simply not done.
Doing a
del
on__defaults
and__module__
of compiled functions was crashing. This was noticed by a Python3 test for__kwdefaults__
that exposed this compiled functions weakness.Wasn't detecting duplicate arguments, if one of them was not a plain arguments. Star arguments could collide with normal ones.
The
__doc__
of classes is now only set, where it was in fact specified. Otherwise it only polluted the name space oflocals()
.When
return
from the tried statements of atry/finally
block, was overridden, by the final block, a reference was leaked. Example code:try: return 1 finally: return 2
Raising exception instances with value, was leaking references, and not raising the
TypeError
error it is supposed to do.When raising with multiple arguments, the evaluation order of them was not enforced, it now is. This fixes a reference leak when raising exceptions, where building the exception was raising an exception.
- Optimizing attribute access to compile time constants for the first time. The old registry had no actual user yet.
- Optimizing subscript and slices for all compile time constants beyond constant values, made easy by using inheritance.
- Built-in references now convert to strings directly, e.g. when used in a print statement. Needed for the testing approach "compiled file contains only prints with constant value".
- Optimizing calls to constant nodes directly into exceptions.
- Optimizing built-in
bool
for arguments with known truth value. This would be creations of tuples, lists, and dictionaries. - Optimizing
a is b
anda is not b
based on aliasing interface, which at this time effectively is limited to telling thata is a
is true anda is not a
is false, but this will expand. - Added support for optimizing
hasattr
,getattr
, andsetattr
built-ins as well. Thehasattr
was needed for theclass
re-formulation of Python3 anyway. - Optimizing
getattr
with string argument and no default to simple attribute access. - Added support for optimizing
isinstance
built-in. - Was handling "BreakException" and "ContinueException" in all loops that used
break
orcontinue
instead of only where necessary. - When catching "ReturnValueException", was raising an exception where a normal return was sufficient. Raising them now only where needed, which also means, function need not catch them ever.
- The handling of classes for Python2 and Python3 have been re-formulated in
Python more completely.
- The calling of the determined "metaclass" is now in the node tree, so this call may possible to in-line in the future. This eliminated some static C++ code.
- Passing of values into dictionary creation function is no longer using hard coded special parameters, but temporary variables can now have closure references, making this normal and visible to the optimization.
- Class dictionary creation functions are therefore no longer as special as they used to be.
- There is no class creation node anymore, it's merely a call to
type
or the metaclass detected.
- Re-formulated complex calls through helper functions that process the star
list and dict arguments and do merges, checks, etc.
- Moves much C++ code into the node tree visibility.
- Will allow optimization to eliminate checks and to compile time merge, once in-line functions and loop unrolling are supported.
- Added "return None" to function bodies without a an aborting statement at the end, and removed the hard coded fallback from function templates. Makes it explicit in the node tree and available for optimization.
- Merged C++ classes for frame exception keeper with frame guards.
- The exception is now saved in the compiled frame object, making it potentially more compatible to start with.
- Aligned module and function frame guard usage, now using the same class.
- There is now a clear difference in the frame guard classes. One is for generators and one is for functions, allowing to implement their different exception behavior there.
- The optimization registries for calls, subscripts, slices, and attributes have
been replaced with attaching them to nodes.
- The ensuing circular dependency has been resolved by more local imports for created nodes.
- The package "nuitka.transform.optimization.registries" is no more.
- New per node methods "computeNodeCall", "computeNodeSubscript", etc. dispatch the optimization process to the nodes directly.
- Use the standard frame guard code generation for modules too.
- Added a variant "once", that avoids caching of frames entirely.
- The variable closure taking has been cleaned up.
- Stages are now properly numbered.
- Python3 only stage is not executed for Python2 anymore.
- Added comments explaining things a bit better.
- Now an early step done directly after building a tree.
- The special code generation used for unpacking from iterators and catching
"StopIteration" was cleaned up.
- Now uses template, Generator functions, and proper identifiers.
- The
return
statements in generators are now re-formulated intoraise StopIteration
for generators, because that's what they really are. Allowed to remove special handling ofreturn
nodes in generators. - The specialty of CPython2.6 yielding non-None values of lambda generators, was so far implemented in code generation. This was moved to tree building as a re-formulation, making it subject to normal optimization.
- Mangling of attribute names in functions contained in classes, has been moved into the early tree building. So far it was done during code generation, making it invisible to the optimization stages.
- Removed tags attribute from node classes. This was once intended to make up for non-inheritance of similar node kinds, but since we have function references, the structure got so clean, it's no more needed.
- Introduced new package
nuitka.tree
, where the building of node trees, and operations on them live, as well as recursion and variable closure. - Removed
nuitka.transform
and move its former childrennuitka.optimization
andnuitka.finalization
one level up. The deeply nested structure turned out to have no advantage. - Checks for Python version was sometimes "> 300", where of course ">= 300" is the only thing that makes sense.
- Split out helper code for exception raising from the handling of exception objects.
- The complete CPython3.2 test suite was adapted (no
__code__
, no__closure__
, etc.) and is now passing, but only without "--debug", because otherwise some of the generated C++ triggers (harmless) warnings. - Added new test suite designed to prove that expressions that are known to be compile time constant are indeed so. This works using the XML output done with "--dump-xml" and then searching it to only have print statements with constant values.
- Added new basic CPython3.2 test "Functions32" and "ParameterErrors32" to cover keyword only parameter handling.
- Added tests to cover generator object and exception interactions.
- Added tests to cover
try/finally
andreturn
in one or both branches correctly handling the references. - Added tests to cover evaluation order of arguments when raising exceptions.
- Changed my email from GMX over to Gmail, the old one will still continue to work. Updated the copyright notices accordingly.
- Uploaded Nuitka to PyPI as well.
This release marks a milestone. The support of Python3 is here. The re-formulation of complex calls, and the code generation improvements are quite huge. More re-formulation could be done for argument parsing, but generally this is now mostly complete.
The 0.3.x series had a lot releases. Many of which brought progress with
re-formulations that aimed at making optimization easier or possible. Sometimes
small things like making "return None" explicit. Sometimes bigger things, like
making class creations normal functions, or getting rid of or
and
and
. All of this was important ground work, to make sure, that optimization
doesn't deal with complex stuff.
So, the 0.4.x series begins with this. The focus from now on can be almost
purely optimization. This release contains already some of it, with frames being
optimized away, with the assignment keepers from the or
and and
re-formulation being optimized away. This will be about achieving goals from the
"ctypes" plan as discussed in the developer manual.
Also the performance page will be expanded with more benchmarks and diagrams as I go forward. I have finally given up on "codespeed", and do my own diagrams.
This release brings about changes on all fronts, bug fixes, new features. Also very importantly Nuitka no longer uses C++11 for its code, but mere C++03. There is new re-formulation work, and re-factoring of functions.
But the most important part is this: Mercurial unit tests are working. Nearly. With the usual disclaimer of me being wrong, all remaining errors are errors of the test, or minor things. Hope is that these unit tests can be added as release tests to Nuitka. And once that is done, the next big Python application can come.
Local variables were released when an exception was raised that escaped the local function. They should only be released, after another exception was raised somewhere. Issue#39.
Identifiers of nested tuples and lists could collide.
a = ((1, 2), 3) b = ((1,), 2, 3)
Both tuples had the same name previously, not the end of the tuple is marked too. Fixed in 0.3.24.1 already.
The
__name__
when used read-only in modules in packages was optimized to a string value that didn't contain the package name.Exceptions set when entering compiled functions were unset at function exit.
Compiled frames support. Before, Nuitka was creating frames with the standard CPython C/API functions, and tried its best to cache them. This involved some difficulties, but as it turns out, it is actually possible to instead provide a compatible type of our own, that we have full control over.
This will become the base of enhanced compatibility. Keeping references to local variables attached to exception tracebacks is something we may be able to solve now.
Enhanced Python3 support, added support for
nonlocal
declarations and many small corrections for it.Writable
__defaults__
attribute for compiled functions, actually changes the default value used at call time. Not supported is changing the amount of default parameters.
- Keep the functions along with the module and added "FunctionRef" node kind to point to them.
- Reformulated
or
andand
operators with the conditional expression construct which makes the "short-circuit" branch. - Access
self
in methods from the compiled function object instead of pointer to context object, making it possible to access the function object. - Removed "OverflowCheck" module and its usage, avoids one useless scan per function to determine the need for "locals dictionary".
- Make "compileTree" of "MainControl" module to only do what the name says and moved the rest out, making the top level control clearer.
- Don't export module entry points when building executable and not modules. These exports cause MinGW and MSVC compilers to create export libraries.
- More efficient code for conditional expressions in conditions:
if a if b else c
See above, this code is now the typical pattern for each ``or`` and ``and``,
so this was much needed now.
The remaining uses of C++11 have been removed. Code generated with Nuitka and complementary C++ code now compile with standard C++03 compilers. This lowers the Nuitka requirements and enables at least g++ 4.4 to work with Nuitka.
The usages of the GNU extension operation
a ?: b
have replaced with standard C++ constructs. This is needed to support MSVC which doesn't have this.Added examples for the typical use cases to the "User Manual".
The "compare_with_cpython" script has gained an option to immediately remove the Nuitka outputs (build directory and binary) if successful. Also the temporary files are now put under "/var/tmp" if available.
Debian package improvements, registering with "doc-base" the "User Manual" so it is easier to discover. Also suggest "mingw32" package which provides the cross compiler to Windows.
Partial support for MSVC (Visual Studio 2008 to be exact, the version that works with CPython2.6 and CPython2.7).
All basic tests that do not use generators are working now, but those will currently cause crashes.
Renamed the
--g++-only
option to--c++-only
.The old name is no longer correct after clang and MSVC have gained support, and it could be misunderstood to influence compiler selection, rather than causing the C++ source code to not be updated, so manual changes will the used. This solves Issue#47.
Catch exceptions for
continue
,break
, andreturn
only where needed fortry
/finally
and loop constructs.
- Added CPython3.2 test suite as "tests/CPython32" from 3.2.3 and run it with CPython2.7 to check that Nuitka gives compatible error messages. It is not expected to pass yet on Python3.2, but work will be done towards this goal.
- Make CPython2.7 test suite runner also execute the generated "doctest" modules.
- Enabled tests for default parameters and their reference counts.
This release marks an important point. The compiled frames are exciting new technology, that will allow even better integration with CPython, while improving speed. Lowering the requirements to C++03 means, we will become usable on Android and with MSVC, which will make adoption of Nuitka on Windows easier for many.
Structurally the outstanding part is the function as references cleanup. This was a blocker for value propagation, because now functions references can be copied, whereas previously this was duplicating the whole function body, which didn't work, and wasn't acceptable. Now, work can resume in this domain.
Also very exciting when it comes to optimization is the remove of special code
for or
and and
operators, as these are now only mere conditional
expressions. Again, this will make value propagation easier with two special
cases less.
And then of course, with Mercurial unit tests running compiled with Nuitka, an important milestone has been hit.
For a while now, the focus will be on completing Python3 support, XML based optimization regression tests, benchmarks, and other open ends. Once that is done, and more certainty about Mercurial tests support, I may call it a 0.4 and start with local type inference for actual speed gains.
This release contains progress on many fronts, except performance.
The extended coverage from running the CPython 2.7 and CPython 3.2 (partially) test suites shows in a couple of bug fixes and general improvements in compatibility.
Then there is a promised new feature that allows to compile whole packages.
Also there is more Python3 compatibility, the CPython 3.2 test suite now
succeeds up to "test_builtin.py", where it finds that str
doesn't support
the new parameters it has gained, future releases will improve on this.
And then of course, more re-formulation work, in this case, class definitions are now mere simple functions. This and later function references, is the important and only progress towards type inference.
The compiled method type can now be used with
copy
module. That means, instances with methods can now be copied too. Issue#40. Fixed in 0.3.23.1 already.The
assert
statement as of Python2.7 creates theAssertionError
object from a given value immediately, instead of delayed as it was with Python2.6. This makes a difference for the form with 2 arguments, and if the value is a tuple. Issue#41. Fixed in 0.3.23.1 already.Sets written like this didn't work unless they were predicted at compile time:
{ value }
This apparently rarely used Python2.7 syntax didn't have code generation yet and crashed the compiler. Issue#42. Fixed in 0.3.23.1 already.
For Python2, the default encoding for source files is
ascii
, and it is now enforced by Nuitka as well, with the sameSyntaxError
.Corner cases of
exec
statements with nested functions now give properSyntaxError
exceptions under Python2.The
exec
statement with a tuple of length 1 as argument, now also gives aTypeError
exception under Python2.For Python2, the
del
of a closure variable is aSyntaxError
.
- Added support creating compiled packages. If you give Nuitka a directory with
an "__init__.py" file, it will compile that package into a ".so" file. Adding
the package contents with
--recurse-dir
allows to compile complete packages now. Later there will be a cleaner interface likely, where the later is automatic. - Added support for providing directories as main programs. It's OK if they contain a "__main__.py" file, then it's used instead, otherwise give compatible error message.
- Added support for optimizing the
super
built-in. It was already working correctly, but not optimized on CPython2. But for CPython3, the variant without any arguments required dedicated code. - Added support for optimizing the
unicode
built-in under Python2. It was already working, but will become the basis for thestr
built-in of Python3 in future releases. - For Python3, lots of compatibility work has been done. The Unicode issues
appear to be ironed out now. The
del
of closure variables is allowed and supported now. Built-ins likeord
andchr
work more correctly and attributes are now interned strings, so that monkey patching classes works.
Migrated "bin/benchmark.sh" to Python as "misc/run-valgrind.py" and made it a bit more portable that way. Prefers "/var/tmp" if it exists and creates temporary files in a secure manner. Triggered by the Debian "insecure temp file" bug.
Migrated "bin/make-dependency-graph.sh" to Python as "misc/make-dependency-graph.py" and made a more portable and powerful that way.
The filtering is done a more robust way. Also it creates temporary files in a secure manner, also triggered by the Debian "insecure temp file" bug.
And it creates SVG files and no longer PostScript as the first one is more easily rendered these days.
Removed the "misc/gist" git sub-module, which was previously used by "misc/make-doc.py" to generate HTML from "User Manual" and "Developer Manual".
These are now done with Nikola, which is much better at it and it integrates with the web site.
Lots of formatting improvements to the change log, and manuals:
- Marking identifiers with better suited ReStructured Text markup.
- Added links to the bug tracker all Issues.
- Unified wordings, quotation, across the documents.
The creation of the class dictionaries is now done with normal function bodies, that only needed to learn how to throw an exception when directly called, instead of returning
NULL
.Also the assignment of
__module__
and__doc__
in these has become visible in the node tree, allowing their proper optimization.These re-formulation changes allowed to remove all sorts of special treatment of
class
code in the code generation phase, making things a lot simpler.There was still a declaration of
PRINT_ITEMS
and uses of it, but no definition of it.Code generation for "main" module and "other" modules are now merged, and no longer special.
The use of raw strings was found unnecessary and potentially still buggy and has been removed. The dependence on C++11 is getting less and less.
- Updated CPython2.6 test suite "tests/CPython26" to 2.6.8, adding tests for recent bug fixes in CPython. No changes to Nuitka were needed in order to pass, which is always good news.
- Added CPython2.7 test suite as "tests/CPython27" from 2.7.3, making it public for the first time. Previously a private copy of some age, with many no longer needed changes had been used by me. Now it is up to par with what was done before for "tests/CPython26", so this pending action is finally done.
- Added test to cover Python2 syntax error of having a function with closure variables nested inside a function that is an overflow function.
- Added test "BuiltinSuper" to cover
super
usage details. - Added test to cover
del
on nested scope as syntax error. - Added test to cover
exec
with a tuple argument of length 1. - Added test to cover
barry_as_FLUFL
future import to work. - Removed "Unicode" from known error cases for CPython3.2, it's now working.
This release brought forward the most important remaining re-formulation changes needed for Nuitka. Removing class bodies, makes optimization yet again simpler. Still, making function references, so they can be copied, is missing for value propagation to progress.
Generally, as usual, a focus has been laid on correctness. This is also the first time, I am release with a known bug though: That is Issue#39 which I believe now, may be the root cause of the mercurial tests not yet passing.
The solution will be involved and take a bit of time. It will be about "compiled frames" and be a (invasive) solution. It likely will make Nuitka faster too. But this release includes lots of tiny improvements, for Python3 and also for Python2. So I wanted to get this out now.
As usual, please check it out, and let me know how you fare.
This release is the one that completes the Nuitka "sun rise phase".
All of Nuitka is now released under Apache License 2.0 which is a very liberal license, and compatible with basically all Free Software licenses there are. It's only asking to allow integration, of what you send back, and patent grants for the code.
In the first phase of Nuitka development, I wanted to keep control over Nuitka, so it wouldn't repeat mistakes of other projects. This is no longer a concern for me, it's not going to happen anymore.
I would like to thank Debian Legal team, for originally bringing to my attention, that this license will be better suited, than any copyright assignment could be.
- The compiled functions could not be used with
multiprocessing
orcopy.copy
. Issue#19. Fixed in 0.3.22.1 already. - In-place operations for slices with not both bounds specified crashed the compiler. Issue#36. Fixed in 0.3.22.1 already.
- Cyclic imports could trigger an endless loop, because module import expressions became the parent of the imported module object. Issue#37. Fixed in 0.3.22.2 already.
- Modules named
proc
orfunc
could not be compiled to modules or embedded due to a collision with identifiers of CPython2.7 includes. Issue#38. Fixed in 0.3.22.2 already.
- The fix for Issue#19 also makes pickling of compiled functions available. As it is the case for non-compiled functions in CPython, no code objects are stored, only names of module level variables.
Using the Apache License 2.0 for all of Nuitka now.
Speedcenter has been re-activated, but is not yet having a lot of benchmarks yet, subject to change.
Update
We have given up on speedcenter meanwhile, and generate static pages with graphs instead.
- Changed the "CPython26" tests to no longer disable the parts that relied on copying of functions to work, as Issue#19 is now supported.
- Extended in-place assignment tests to cover error cases of Issue#36.
- Extended compile library test to also try and compile the path where
numpy
lives. This is apparently another path, where Debian installs some modules, and compiling this would have revealed Issue#36 sooner.
The release contains bug fixes, and the huge step of changing the license. It is made in preparation to PyCON EU.
This release is a continuation of the trend of previous releases, and added more re-formulations of Python that lower the burden on code generation and optimization.
It also improves Python3 support substantially. In fact this is the first release to not only run itself under Python3, but for Nuitka to compile itself with Nuitka under Python3, which previously only worked for Python2. For the common language subset, it's quite fine now.
- List contractions produced extra entries on the call stack, after they became functions, these are no more existent. That was made possible my making frame stack entries an optional element in the node tree, left out for list contractions.
- Calling a compiled function in an exception handler cleared the exception on return, it no longer does that.
- Reference counter handling with generator
throw
method is now correct. - A module "builtins" conflicted with the handling of the Python
builtins
module. Those now use different identifiers.
New
metaclass
syntax for theclass
statement works, and the old__metaclass__
attribute is properly ignored.# Metaclass syntax in Python3, illegal in Python2 class X(metaclass = Y): pass
# Metaclass syntax in Python2, no effect in Python3 class X: __metaclass__ = Y
Note
The way to make a use of a metaclass in a portable way, is to create a based class that has it and then inherit from it. Sad, isn' it. Surely, the support for
__metaclass__
could still live.# For Python2/3 compatible source, we create a base class that has the # metaclass used and doesn't require making a choice. CPythonNodeMetaClassBase = NodeCheckMetaClass("CPythonNodeMetaClassBase", (object,), {})
The
--dump-xml
option works with Nuitka running under Python3. This was not previously supported.Python3 now also has compatible parameter errors and compatible exception error messages.
Python3 has changed scope rules for list contractions (assignments don't affect outside values) and this is now respected as well.
Python3 has gained support for recursive programs and stand alone extension modules, these are now both possible as well.
Avoid frame stack entries for functions that cannot raise exceptions, i.e. where they would not be used.
This avoids overhead for the very simple functions. And example of this can be seen here:
def simple(): return 7
Optimize
len
built-in for non-constant, but known length values.An example can be seen here:
# The range isn't constructed at compile time, but we still know its # length. len(range(10000000)) # The string isn't constructed at compile time, but we still know its # length. len("*" * 1000) # The tuple isn't constructed, instead it's known length is used, and # side effects are maintained. len((a(), b()))
This new optimization applies to all kinds of container creations and the
range
built-in initially.Optimize conditions for non-constant, but known truth values.
At this time, known truth values of non-constants means
range
built-in calls with know size and container creations.An example can be seen here:
if (a,): print "In Branch"
It's clear, that the tuple will be true, we just need to maintain the side effect, which we do.
Optimize
or
andand
operators for known truth values.See above for what has known truth values currently. This will be most useful to predict conditions that need not be evaluated at all due to short circuit nature, and to avoid checking against constant values. Previously this could not be optimized, but now it can:
# The access and call to "something()" cannot possibly happen 0 and something() # Can be replaced with "something()", as "1" is true. If it had a side effect, it # would be maintained. 1 and something() # The access and call to "something()" cannot possibly happen, the value is already # decided, it's "1". 1 or something() # Can be replaced with "something()", as "0" is false. If it had a side effect, it # would be maintained. 0 or something()
Optimize print arguments to become strings.
The arguments to
print
statements are now converted to strings at compile time if possible.print 1
becomes:
print "1"
Combine print arguments to single ones.
When multiple strings are printed, these are now combined.
print "1+1=", 1+1
becomes:
print "1+1= 2"
- Enhanced Python3 support, enabling support for most basic tests.
- Check files with PyLint in deterministic (alphabetical) order.
- Frame stack entries are now part of the node tree instead of part of the template for every function, generator, class or module.
- The
try
/except
/else
has been re-formulated to use an indicator variable visible in the node tree, that tells if a handler has been executed or not. - Side effects are now a dedicated node, used in several optimization to maintain the effect of an expression with known value.
- Expanded and adapted basic tests to work for Python3 as well.
- Added reference count tests for generator functions
throw
,send
, andclose
methods. - Cover calling a function with
try
/except
in an exception handler twice. No test was previously doing that.
This release offers enhanced compatibility with Python3, as well as the solution to many structural problems. Calculating lengths of large non-constant values at compile time, is technically a break through, as is avoiding lengthy calculations. The frame guards as nodes is a huge improvement, making that costly operational possible to be optimized away.
There still is more work ahead, before value propagation will be safe enough to enable, but we are seeing the glimpse of it already. Not for long, and looking at numbers will make sense.
This releases contains some really major enhancements, all heading towards enabling value propagation inside Nuitka. Assignments of all forms are now all simple and explicit, and as a result, now it will be easy to start tracking them.
Contractions have become functions internally, with statements use temporary variables, complex unpacking statement were reduced to more simple ones, etc.
Also there are the usual few small bug fixes, and a bunch of organizational improvements, that make the release complete.
- The built-in
next
could causes a program crash when iterating past the end of an iterator. Issue#34. Fixed in 0.3.20.1 already. - The
set
constants could cause a compiler error, as that type was not considered in the "mutable" check yet. Fixed in 0.3.20.2 already. - Performance regression. Optimize expression for exception types caught as well again, this was lost in last release.
- Functions that contain
exec
, are supposed to have a writable locals. But when removing thatexec
statement as part of optimization, this property of the function could get lost. - The so called "overflow functions" are once again correctly handled. These
once were left behind in some refactoring and had not been repaired until
now. An overflow function is a nested function with an
exec
or a star import. - The syntax error for
return
outside of a function, was not given, instead the code returned at run time. Fixed to raise aSyntaxError
at compile time.
Avoid
tuple
objects to be created when catching multiple exception types, instead call exception match check function multiple times.Removal of dead code following
break
,continue
,return
, andraise
. Code that follows these statements, or conditional statements, where all branches end with it.Note
These may not actually occur often in actual code, but future optimization may produce them more frequently, and their removal may in turn make other possible optimization.
Detect module variables as "read only" after all writes have been detected to not be executed as removed. Previously the "read only indicator" was determined only once and then stayed the same.
Expanded conditional statement optimization to detect cases, where condition is a compile time constant, not just a constant value.
Optimize away assignments from a variable to the same variable, they have no effect. The potential side effect of accessing the variable is left intact though, so exceptions will be raised still.
Note
An exception is where
len = len
actually does have an impact, because that variable becomes assignable. The "compile itself" test of Nuitka found that to happen withlong
from thenuitka.__past__
module.Created Python3 variant of quick
unicode
string access, there was no such thing in the CPython C/API, but we make the distinction in the source code, so it makes sense to have it.Created an optimized implementation for the built-in
iter
with 2 parameters as well. This allows for slightly more efficient code to be created with regards to reference handling, rather than using the CPython C/API.For all types of variable assigned in the generated code, there are now methods that accept already taken references or not, and the code generator picks the optimal variant. This avoids the drop of references, that e.g. the local variable will insist to take.
Don't use a "context" object for generator functions (and generator expressions) that don't need one. And even if it does to store e.g. the given parameter values, avoid to have a "common context" if there is no closure taken. This avoids useless
malloc
calls and speeds up repeated generator object creation.
- Changed the Scons build file database to reside in the build directory as opposed to the current directory, not polluting it anymore. Thanks for the patch go to Michael H Kent, very much appreciated.
- The
--experimental
option is no longer available outside of checkouts of git, and even there not on stable branches (master
,hotfix/...
). It only pollutes--help
output as stable releases have no experimental code options, not even development version will make a difference. - The binary "bin/Nuitka.py" has been removed from the git repository. It was deprecated a while ago, not part of the distribution and served no good use, as it was a symbolic link only anyway.
- The
--python-version
option is applied at Nuitka start time to re-launch Nuitka with the given Python version, to make sure that the Python run time used for computations and link time Python versions are the same. The allowed values are now checked (2.6, 2.7 and 3.2) and the user gets a nice error with wrong values. - Added
--keep-pythonpath
alias for--execute-with-pythonpath
option, probably easier to remember. - Support
--debug
with clang, so it can also be used to check the generated code for all warnings, and perform assertions. Didn't report anything new. - The contents environment variable
CXX
determines the default C++ compiler when set, so that checking withCXX=g++-4.7 nuitka-python ...
has become supported. - The
check-with-pylint
script now has a real command line option to control the display ofTODO
items.
Changed complex assignments, i.e. assignments with multiple targets to such using a temporary variable and multiple simple assignments instead.
a = b = c
_tmp = c b = _tmp a = _tmp
In CPython, when one assignment raises an exception, the whole thing is aborted, so the complexity of having multiple targets is no more needed, now that we have temporary variables in a block.
All that was really needed, was to evaluate the complete source expression only once, but that made code generation contain ugly loops that are no more needed.
Changed unpacking assignments to use temporary variables. Code like this:
a, b = c
Is handled more like this:
_tmp_iter = iter(c) _tmp1 = next(_tmp_iter) _tmp2 = next(_tmp_iter) if not finished(_tmp_iter): raise ValueError("too many values to unpack") a = _tmp1 b = _tmp2
In reality, not really
next
is used, as it wouldn't raise the correct exception for unpacking, and thefinished
check is more condensed into it.Generally this cleanup allowed that the
AssignTargetTuple
and associated code generation was removed, and in the future value propagation may optimize thesenext
anditer
calls away where possible. At this time, this is not done yet.Exception handlers assign caught exception value through assignment statement.
Previously the code generated for assigning from the caught exception was not considered part of the handler. It now is the first statement of an exception handler or not present, this way it may be optimized as well.
Exception handlers now explicitly catch more than one type.
Catching multiple types worked by merits of the created tuple object working with the Python C/API function called, but that was not explicit at all. Now every handler has a tuple of exceptions it catches, which may only be one, or if None, it's all.
Contractions are now functions as well.
Contractions (list, dict, and set) are now re-formulated as function bodies that contain for loops and conditional statements. This allowed to remove a lot of special code that dealt with them and will make these easier to understand for optimization and value propagation.
Global is handled during tree building.
Previously the global statement was its own node, which got removed during the optimization phase in a dedicated early optimization that applied its effect, and then removed the node.
It was determined, that there is no reason to not immediately apply the effect of the global variable and take closure variables and add them to the provider of that
global
statement, allowing to remove the node class.Read only module variable detection integrated to constraint collection.
The detection of read only module variables was so far done as a separate step, which is no more necessary as the constraint collection tracks the usages of module variables anyway, so this separate and slow step could be removed.
Added test to cover order of calls for complex assignments that unpack, to see that they make a fresh iterator for each part of a complex assignment.
Added test that unpacks in an exception catch. It worked, due to the generic handling of assignment targets by Nuitka, and I didn't even know it can be done, example:
try: raise ValueError(1,2) except ValueError as (a,b): print "Unpacking caught exception and unpacked", a, b
Will assign
a=1
andb=2
.Added test to cover return statements on module level and class level, they both must give syntax errors.
Cover exceptions from accessing unassigned global names.
Added syntax test to show that star imports do not allow other names to be imported at the same time as well.
Python3 is now also running the compile itself test successfully.
The progress made towards value propagation and type inference is very significant, and makes those appears as if they are achievable.
This time there are a few bug fixes and some really major cleanups, lots of new optimization and preparations for more. And then there is a new compiler clang and a new platform supported. MacOS X appears to work mostly, thanks for the patches from Pete Hunt.
- The use of a local variable name as an expression was not covered and lead to a compiler crash. Totally amazing, but true, nothing in the test suite of CPython covered this. Issue#30. Fixed in release 0.3.19.1 already.
- The use of a closure variable name as an expression was not covered as well. And in this case corrupted the reference count. Issue#31. Fixed in release 0.3.19.1 already.
- The
from x import *
attempted to respect__all__
but failed to do so. Issue#32. Fixed in release 0.3.19.2 already. - The
from x import *
didn't give aSyntaxError
when used on Python3. Fixed in release 0.3.19.2 already. - The syntax error messages for "global for function argument name" and "duplicate function argument name" are now identical as well.
- Parameter values of generator function could cause compilation errors when used in the closure of list contractions. Fixed.
- Added support for disabling the console for Windows binaries. Thanks for the patch go to Michael H Kent.
- Enhanced Python3 support for syntax errors, these are now also compatible.
- Support for MacOS X was added.
- Support for using the clang compiler was added, it can be enforced via
--clang
option. Currently this option is mainly intended to allow testing the "MacOS X" support as good as possible under Linux.
Enhanced all optimization that previously worked on "constants" to work on "compile time constants" instead. A "compile time constant" can currently also be any form of a built-in name or exception reference. It is intended to expand this in the future.
Added support for built-ins
bin
,oct
, andhex
, which also can be computed at compile time, if their arguments are compile time constant.Added support for the
iter
built-in in both forms, one and two arguments. These cannot be computed at compile time, but now will execute faster.Added support for the
next
built-in, also in its both forms, one and two arguments. These also cannot be computed at compile time, but now will execute faster as well.Added support for the
open
built-in in all its form. We intend for future releases to be able to track file opens for including them into the executable if data files.Optimize the
__debug__
built-in constant as well. It cannot be assigned, yet code can determine a mode of operation from it, and apparently some code does. When compiling the mode is decided.Optimize the
Ellipsis
built-in constant as well. It falls in the same category asTrue
,False
,None
, i.e. names of built-in constants that a singletons.Added support for anonymous built-in references, i.e. built-ins which have names that are not normally accessible. An example is
type(None)
which is not accessible from anywhere. Other examples of such names arecompiled_method_or_function
.Having these as represented internally, and flagged as "compile time constants", allows the compiler to make more compile time optimization and to generate more efficient C++ code for it that won't e.g. call the
type
built-in withNone
as an argument.All built-in names used in the program are now converted to "built-in name references" in a first step. Unsupported built-ins like e.g.
zip
, for which Nuitka has no own code or understanding yet, remained as "module variables", which made access to them slow, and difficult to recognize.Added optimization for module attributes
__file__
,__doc__
and__package__
if they are read only. It's the same as__name__
.Added optimization for slices and subscripts of "compile time constant" values. These will play a more important role, once value propagation makes them more frequent.
- Created a "change log" from the previous release announcements. It's as ReStructured Text and converted to PDF for the release as well, but I chose not to include that in Debian, because it's so easy to generate the PDF on that yourself.
- The posting of release announcements is now prepared by a script that converts the ReStructured Text to HTML and adds it to Wordpress as a draft posting or updates it, until it's release time. Simple, sweet and elegant.
Split out the
nuitka.nodes.Nodes
module into many topic nodes, so that there are nownuitka.nodes.BoolNodes
ornuitka.nodes.LoopNodes
to host nodes of similar kinds, so that it is now cleaner.Split
del
statements into their own node kind, and use much simpler node structures for them. The following blocks are absolutely the same:del a, b.c, d
del a del b.c del d
So that's now represented in the node tree. And even more complex looking cases, like this one, also the same:
del a, (b.c, d)
This one gives a different parse tree, but the same bytecode. And so Nuitka need no longer concern itself with this at all, and can remove the tuple from the parse tree immediately. That makes them easy to handle. As you may have noted already, it also means, there is no way to enforce that two things are deleted or none at all.
Turned the function and class builder statements into mere assignment statements, where defaults and base classes are handled by wrapping expressions.
Previously they are also kind of assignment statements too, which is not needed. Now they were reduced to only handle the
bases
for classes and thedefaults
for functions and make optional.Refactored the decorator handling to the tree building stage, presenting them as function calls on "function body expression" or class body expression".
This allowed to remove the special code for decorators from code generation and C++ templates, making decorations easy subjects for future optimization, as they practically are now just function calls.
@some_classdecorator class C: @staticmethod def f(): pass
It's just a different form of writing things. Nothing requires the implementation of decorators, it's just functions calls with function bodies before the assignment.
The following is only similar:
class C: def f(): pass f = staticmethod(f) C = some_classdecorator(C)
It's only similar, because the assignment to an intermediate value of
C
andf
is not done, and if an exception was raised by the decoration, that name could persist. For Nuitka, the function and class body, before having a name, are an expression, and so can of course be passed to decorators already.The in-place assignments statements are now handled using temporary variable blocks
Adding support for scoped temporary variables and references to them, it was possible to re-formulate in-place assignments expressions as normal look-ups, in-place operation call and then assignment statement. This allowed to remove static templates and will yield even better generated code in the future.
The for loop used to have has a "source" expression as child, and the iterator over it was only taken at the code generation level, so that step was therefore invisible to optimization. Moved it to tree building stage instead, where optimization can work on it then.
Tree building now generally allows statement sequences to be
None
everywhere, and pass statements are immediately eliminated from them immediately. Empty statement sequences are now forbidden to exist.Moved the optimization for
__name__
to compute node of variable references, where it doesn't need anything complex to replace with the constant value if it's only read.Added new bases classes and mix-in classes dedicated to expressions, giving a place for some defaults.
Made the built-in code more reusable.
- Added some more diagnostic tests about complex assignment and
del
statements. - Added syntax test for star import on function level, that must fail on Python3.
- Added syntax test for duplicate argument name.
- Added syntax test for global on a function argument name.
The decorator and building changes, the assignment changes, and the node cleanups are all very important progress for the type inference work, because they remove special casing the that previously would have been required. Lambdas and functions now really are the same thing right after tree building. The in-place assignments are now merely done using standard assignment code, the built functions and classes are now assigned to names in assignment statements, much more consistency there.
Yet, even more work will be needed in the same direction. There may e.g. be work
required to cover with
statements as well. And assignments will become no
more complex than unpacking from a temporary variable.
For this release, there is only minimal progress on the Python3 front, despite the syntax support, which is only miniscule progress. The remaining tasks appear all more or less difficult work that I don't want to touch now.
There are still remaining steps, but we can foresee that a release may be done that finally actually does type inference and becomes the effective Python compiler this project is all about.
This time there are a few bug fixes, major cleanups, more Python3 support, and even new features. A lot things in this are justifying a new release.
- The man pages of
nuitka
andnuitka-python
had no special layout for the option groups and broken whitespace for--recurse-to
option. Also--g++-only
was only partially bold. Released as 0.3.18.1 hot fix already. - The command line length improvement we made to Scons for Windows was not portable to Python2.6. Released as 0.3.18.2 hot fix already.
- Code to detect already considered packages detection was not portable to
Windows, for one case, there was still a use of
/
instead of using ajoinpath
call. Released as 0.3.18.3 already. - A call to the range built-in with no arguments would crash the compiler, see Issue#29. Released as 0.3.18.4 already.
- Compatibility Fix: When rich comparison operators returned false value other
False
, for comparison chains, these would not be used, butFalse
instead, see . - The support for
__import__
didn't cover keyword arguments, these were simply ignored. See Issue#28. Fixed, but no warning is given yet.
- A new option has been added, one can now specify
--recurse-directory
and Nuitka will attempt to embed these modules even if not obviously imported. This is not yet working perfect yet, but will receive future improvements. - Added support for the
exec
built-in of Python3, this enables us to run one more basic test,GlobalStatement.py
with Python3. The testExecEval.py
nearly works now.
- The no arguments
range()
call now optimized into the static CPython exception it raises. - Parts of comparison chains with constant arguments are now optimized away.
Simplified the
CPythonExpressionComparison
node, it now always has only 2 operands.If there are more, the so called "comparison chain", it's done via
and
with assignments to temporary variables, which are expressed by a new node typeCPythonExpressionTempVariableRef
. This allowed to removeexpression_temps
from C++ code templates and generation, reducing the overall complexity.When executing a module (
--execute
but not--exe
), no longer does Nuitka import it into itself, instead a new interpreter is launched with a fresh environment.The calls to the variadic
MAKE_TUPLE
were replaced with calls theMAKE_TUPLExx
(wherexx
is the number of arguments), that are generated on a as-needed basis. This gives more readable code, because noEVAL_ORDERED_xx
is needed at call site anymore.Many node classes have moved to new modules in
nuitka.nodes
and grouped by theme. That makes them more accessible.The choosing of the debug python has moved from Scons to Nuitka itself. That way it can respect the
sys.abiflags
and works with Python3.The replacing of
.py
in filenames was made more robust. No longer isstr.replace
used, but instead proper means to assure that having.py
as other parts of the filenames won't be a trouble.Module recursion was changed into its own module, instead of being hidden in the optimization that considers import statements.
As always, some PyLint work, and some minor
TODO
were solved.
- Added more information to the "Developer Manual", e.g. documenting the tree
changes for
assert
to become a conditional statement with a raise statement, etc. - The Debian package is as of this version verified to be installable and functional on to Ubuntu Natty, Maverick, Oneiric, and Precise.
- Added support to specify the binary under test with a
NUITKA
environment, so the test framework can run with installed version of Nuitka too. - Made sure the test runners work under Windows as well. Required making them
more portable. And a workaround for
os.execl
not propagating exit codes under Windows. See Issue#26 for more information. - For windows target the MinGW library is now linked statically. That means
there is no requirement for MinGW to be in the
PATH
or even installed to execute the binary.
- The
basic
,programs
,syntax
, andreflected
were made executable under Windows. Occasionally this meant to make the test runners more portable, or to work around limitations. - Added test to cover return values of rich comparisons in comparison chains, and order of argument evaluation for comparison chains.
- The
Referencing.py
test was made portable to Python3. - Cover no arguments
range()
exception as well. - Added test to demonstrate that
--recurse-directory
actually works. This is using an__import__
that cannot be predicted at run time (yet). - The created source package is now tested on pbuilder chroots to be pass installation and the basic tests, in addition to the full tests during package build time on these chroots. This will make sure, that Nuitka works fine on Ubuntu Natty and doesn't break without notice.
This releases contains many changes. The "temporary variable ref" and "assignment expression" work is ground breaking. I foresee that it will lead to even more simplifications of code generation in the future, when e.g. in-place assignments can be reduced to assignments to temporary variables and conditional statements.
While there were many improvements related to Windows support and fixing portability bugs, or the Debian package, the real focus is the optimization work, which will ultimately end with "value propagation" working.
These are the real focus. The old comparison chain handling was a big wart. Working, but no way understood by any form of analysis in Nuitka. Now they have a structure which makes their code generation based on semantics and allows for future optimization to see through them.
Going down this route is an important preparatory step. And there will be more work like this needed. Consider e.g. handling of in-place assignments. With an "assignment expression" to a "temporary variable ref", these become the same as user code using such a variable. There will be more of these to find.
So, that is where the focus is. The release now was mostly aiming at getting
involved fixes out. The bug fixed by comparison chain reworking, and the
__import__
related one, were not suitable for hot fix releases, so that is
why the 0.3.19 release had to occur now. But with plugin support, with this
comparison chain cleanup, with improved Python3 support, and so on, there was
plenty of good stuff already, also worth to get out.
This is to inform you about the new stable release of Nuitka. This time there
are a few bug fixes, and the important step that triggered the release: Nuitka
has entered Debian Unstable. So you if want, you will get stable Nuitka releases
from now on via apt-get install nuitka
.
The release cycle was too short to have much focus. It merely includes fixes, which were available as hot fixes, and some additional optimization and node tree cleanups, as well as source cleanups. But not much else.
- Conditional statements with both branches empty were not optimized away in all cases, triggering an assertion of code generation. Issue#16. Released as 0.3.17a hot fix already.
- Nuitka was considering directories to contain packages that had no "__init__.py" which could lead to errors when it couldn't find the package later in the compilation process. Released as 0.3.17a hot fix already.
- When providing
locals()
toexec
statements, this was not making thelocals()
writable. The logic to detect the case that default value is used (None) and be pessimistic about it, didn't consider the actual valuelocals()
. Released as 0.3.17b hot fix already. - Compatibility Fix: When no defaults are given, CPython uses
None
forfunc.func_defaults
, but Nuitka had been usingNone
.
- If the condition of assert statements can be predicted, these are now optimized in a static raise or removed.
- For built-in name references, there is now dedicated code to look them up, that doesn't check the module level at all. Currently these are used in only a few cases though.
- Cleaner code is generated for the simple case of
print
statements. This is not only faster code, it's also more readable.
Removed the
CPythonStatementAssert
node.It's not needed, instead at tree building, assert statements are converted to conditional statements with the asserted condition result inverted and a raise statement with
AssertionError
and the assertion argument.This allowed to remove code and complexity from the subsequent steps of Nuitka, and enabled existing optimization to work on assert statements as well.
Moved built-in exception names and built-in names to a new module
nuitka.Builtins
instead of having in other places. This was previously a bit spread-out and misplaced.Added cumulative
tags
to node classes for use in checks. Use it annotate which node kinds to visit in e.g. per scope finalization steps. That avoids kinds and class checks.New node for built-in name loopups, which allowed to remove tricks played with adding module variable lookups for
staticmethod
when adding them for__new__
or module variable lookups forstr
when predicting the result oftype('a')
, which was unlikely to cause a problem, but an importantTODO
item still.
The "Download" page is now finally updated for releases automatically.
This closes Issue#7 completely. Up to this release, I had to manually edit that page, but now mastered the art of upload via XMLRCP and a Python script, so that don't loose as much time with editing, checking it, etc.
The Debian package is backportable to Ubuntu Natty, Maverick, Oneiric, I expect to make a separate announcement with links to packages.
Made sure the test runners worth with bare
python2.6
as well.
- Added some tests intended for type inference development.
This releases contains not as much changes as others, mostly because it's the intended base for a Debian upload.
The exec
fix was detected by continued work on the branch
feature/minimize_CPython26_tests_diff
branch, but that work is now complete.
It is being made pretty (many git rebase iterations) with lots of Issues being added to the bug tracker and referenced for each change. The intention is to have a clean commits repository with the changed made.
But of course, the real excitement is the "type inference" work. It will give a huge boost to Nuitka. With this in place, new benchmarks may make sense. I am working on getting it off the ground, but also to make us more efficient.
So when I learn something. e.g. assert
is not special, I apply it to the
develop
branch immediately, to keep the differences as small as possible,
and to immediately benefit from such improvements.
This is to inform you about the new stable release of Nuitka. This time there
are a few bug fixes, lots of very important organisational work, and yet again
improved compatibility and cleanups. Also huge is the advance in making
--deep
go away and making the recursion of Nuitka controllable, which means
a lot for scalability of projects that use a lot of packages that use other
packages, because now you can choose which ones to embed and which ones one.
The release cycle had a focus on improving the quality of the test scripts, the packaging, and generally to prepare the work on "type inference" in a new feature branch.
I have also continued to work towards CPython3.2 compatibility, and this
version, while not there, supports Python3 with a large subset of the basic
tests programs running fine (of course via 2to3
conversion) without
trouble. There is still work to do, exceptions don't seem to work fully yet,
parameter parsing seems to have changed, etc. but it seems that CPython3.2 is
going to work one day.
And there has been a lot of effort, to address the Debian packaging to be cleaner and more complete, addressing issues that prevented it from entering the Debian repository.
- Fixed the handling of modules and packages of the same name, but with different casing. Problem showed under Windows only. Released as 0.3.16a hot fix already.
- Fixed an error where the command line length of Windows was exceeded when many modules were embedded, Christopher Tott provided a fix for it. Released as 0.3.16a hot fix already.
- Fix, avoid to introduce new variables for where built-in exception references are sufficient. Released as 0.3.16b hot fix already.
- Fix, add the missing
staticmethod
decorator to__new__
methods before resolving the scopes of variables, this avoids the use of that variable before it was assigned a scope. Released as 0.3.16b hot fix already.
Enhanced compatibility again, provide enough
co_varnames
in the code objects, so that slicing them up tocode_object.co_argcount
will work. They are needed byinspect
module and might be used by some decorators as well.New options to control the recursion:
--recurse-none
(do not warn about not-done recursions)--recurse-all
(recurse to all otherwise warned modules)--recurse-to
(confirm to recurse to those modules)--recurse-not-to
(confirm to not recurse to those modules)
- The optimization of constant conditional expressions was not done yet. Added this missing constant propagation case.
- Eliminate near empty statement sequences (only contain a pass statement) in more places, giving a cleaner node structure for many constructs.
- Use the pickle "protocol 2" on CPython2 except for
unicode
strings where it does not work well. It gives a more compressed and binary representation, that is generally more efficient to un-stream as well. Also use the cPickle protocol, the use ofpickle
was not really necessary anymore.
- Added a "Developer Manual" to the release. It's incomplete, but it details some of the existing stuff, coding rules, plans for "type inference", etc.
- Improved the
--help
output to usemetavar
where applicable. This makes it more readable for some options. - Instead of error message, give help output when no module or program file name was given. This makes Nuitka help out more convenient.
- Consistently use
#!/usr/bin/env python
for all scripts, this was previously only done for some of them. - Ported the PyLint check script to Python as well, enhancing it on the way to
check the exit code, and to only output changes things, as well as making the
output of warnings for
TODO
items optional. - All scripts used for testing, PyLint checking, etc. now work with Python3 as
well. Most useful on Arch Linux, where it's also already the default for
Python
. - The help output of Nuitka was polished a lot more. It is now more readable and uses option groups to combine related options together.
- Make the tests run without any dependence on
PATH
to contain the executables of Nuitka. This makes it easier to use. - Add license texts to 3rd party file that were missing them, apply
licensecheck
results to cleanup Nuitka. Also removed own copyright statement from in-line copy of Scons, it had been added by accident only. - Release the tests that I own as well as the Debian packaging I created under "Apache License 2.0" which is very liberal, meaning every project will be able to use it.
- Don't require copyright assignment for contributions anymore, instead only "Apache License 2.0", the future Nuitka license, so that the code won't be a problem when changing the license of all of Nuitka to that license.
- Give contributors listed in the "User Manual" an exception to the GPL terms until Nuitka is licensed under "Apache License 2.0" as well.
- Added an
--experimental
option which can be used to control experimental features, like the one currently being added onfeature/ctypes_annotation
, where "type inference" is currently only activated when that option is given. For this stable release, it does nothing. - Check the static C++ files of Nuitka with
cppcheck
as well. Didn't find anything. - Arch Linux packages have been contributed, these are linked for download, but the stable package may lag behind a bit.
- Changed
not
boolean operation to become a normal operator. Changedand
andor
boolean operators to a new base class, and making their interface more similar to that of operations. - Added cumulative
tags
to node classes for use in checks. Use it annotate which node kinds to visit in e.g. per scope finalization steps. That avoids kinds and class checks. - Enhanced the "visitor" interface to provide more kinds of callbacks, enhanced the way "each scope" visiting is achieved by generalizing is as "child has not tag 'closure_taker'" and that for every "node that has tag 'closure_taker'".
- Moved
SyntaxHighlighting
module tonuitka.gui
package where it belongs. - More white listing work for imports. As recursion is now the default, and leads to warnings for non-existent modules, the CPython tests gave a lot of good candidates for import errors that were white listed.
- Consistently use
nuitka
in test scripts, as there isn't aNuitka.py
on all platforms. The later is scheduled for removal. - Some more PyLint cleanups.
Make sure the basic tests pass with CPython or else fail the test. This is to prevent false positives, where a test passes, but only because it fails in CPython early on and then does so with Nuitka too. For the syntax tests we make sure they fail.
The basic tests can now be run with
PYTHON=python3.2
and use2to3
conversion in that case. Also the currently not passing tests are not run, so the passing tests continue to do so, with this run from the release test scriptcheck-release
.Include the syntax tests in release tests as well.
Changed many existing tests so that they can run under CPython3 too. Of course this is via
2to3
conversion.Don't fail if the CPython test suites are not there.
Currently they remain largely unpublished, and as such are mostly only available to me (exception,
feature/minimize_CPython26_tests_diff
branch references the CPython2.6 tests repository, but that remains work in progress).For the compile itself test: Make the presence of the Scons in-line copy optional, the Debian package doesn't contain it.
Also make it more portable, so it runs under Windows too, and allow to choose the Python version to test. Check this test with both CPython2.6 and CPython2.7 not only the default Python.
Before releasing, test that the created Debian package builds fine in a minimal Debian
unstable
chroot, and passes all the tests included in the package (basics
,syntax
,programs
,reflected
). Also many other Debian packaging improvements.
The "git flow" was used again in this release cycle and proved to be useful not
only for hot fix, but also for creating the branch feature/ctypes_annotation
and rebasing it often while things are still flowing.
The few hot fixes didn't require a new release, but the many organizational improvements and the new features did warrant the new release, because of e.g. the much better test handling in this release and the improved recursion control.
The work on Python3 support has slowed down a bit. I mostly only added some bits for compatibility, but generally it has slowed down. I wanted to make sure it doesn't regress by accident, so running with CPython3.2 is now part of the normal release tests.
What's still missing is more "hg" completeness. Only the co_varnames
work
for inspect
was going in that direction, and this has slowed down. It was
more important to make Nuitka's recursion more accessible with the new options,
so that was done first.
And of course, the real excitement is the "type inference" work. It will give a
huge boost to Nuitka, and I am happy that it seems to go well. With this in
place, new benchmarks may make sense. I am working on getting it off the ground,
so other people can work on it too. My idea of ctypes
native calls may
become true sooner than expected. To support that, I would like to add more
tools to make sure we discover changes earlier on, checking the XML
representations of tests to discover improvements and regressions more clearly.
This time there are many bug fixes, some important scalability work, and again improved compatibility and cleanups.
The release cycle had a focus on fixing the bug reports I received. I have also
continued to look at CPython3 compatibility, and this is the first version to
support Python3 somewhat, at least some of the basic tests programs run (of
course via 2to3
conversion) without trouble. I don't know when, but it seems
that it's going to work one day.
Also there has an effort to make the Debian packaging cleaner, addressing all kinds of small issues that prevented it from entering the Debian repository. It's still not there, but it's making progress.
- Fixed a packaging problem for Linux and x64 platform, the new
swapFiber.S
file for the fiber management was not included. Released as 0.3.15a hot fix already. - Fixed an error where optimization was performed on removed unreachable code, which lead to an error. Released as 0.3.15b hot fix already.
- Fixed an issue with
__import__
and recursion not happening in any case, because when it did, it failed due to not being ported to new internal APIs. Released as 0.3.15c hot fix already. - Fixed
eval()
andlocals()
to be supported in generator expressions and contractions too. Released as 0.3.15d hot fix already. - Fixed the Windows batch files
nuitka.bat
andnuitka-python.bat
to not output therem
statements with the copyright header. Released as 0.3.15d hot fix already. - Fixed re-raise with
raise
, but without a current exception set. Released as 0.3.15e hot fix already. - Fixed
vars()
call on the module level, needs to be treated asglobals()
. Released as 0.3.15e hot fix already. - Fix handling of broken new lines in source files. Read the source code in "universal line ending mode". Released as 0.3.15f hot fix already.
- Fixed handling of constant module attribute
__name__
being replaced. Don't replace local variables of the same name too. Released as 0.3.15g hot fix already. - Fixed assigning to
True
,False
orNone
. There was this oldTODO
, and some code has compatibility craft that does it. Released as 0.3.15g hot fix already. - Fix constant dictionaries not always being recognized as shared. Released as 0.3.15g hot fix already.
- Fix generator function objects to not require a return frame to exist. In finalize cleanup it may not.
- Fixed non-execution of cleanup codes that e.g. flush
sys.stdout
, by addingPy_Finalize()
. - Fix
throw()
method of generator expression objects to not check arguments properly. - Fix missing fallback to subscript operations for slicing with non-indexable objects.
- Fix, in-place subscript operations could fail to apply the update, if the intermediate object was e.g. a list and the handle just not changed by the operation, but e.g. the length did.
- Fix, the future spec was not properly preserving the future division flag.
- The optimization scales now much better, because per-module optimization only require the module to be reconsidered, but not all modules all the time. With many modules recursed into, this makes a huge difference in compilation time.
- The creation of dictionaries from constants is now also optimized.
- As a new feature functions now have the
func_defaults
and__defaults__
attribute. It works only well for non-nested parameters and is not yet fully integrated into the parameter parsing. This improves the compatibility somewhat already though. - The names
True
,False
andNone
are now converted to constants only when they are read-only module variables. - The
PYTHONPATH
variable is now cleared when immediately executing a compiled binary unless--execute-with-pythonpath
is given, in which case it is preserved. This allows to make sure that a binary is in fact containing everything required.
- The help output of Nuitka was polished a lot more. It is now more readable and uses option groups to combine related options together.
- The in-line copy of Scons is not checked with PyLint anymore. We of course don't care.
- Program tests are no longer executed in the program directory, so failed module inclusions become immediately obvious.
- The basic tests can now be run with
PYTHON=python3.2
and use2to3
conversion in that case.
- Moved
tags
to a separate module, make optimization emit only documented tags, checked against the list of allowed ones. - The Debian package has seen lots of improvements, to make it "lintian clean", even in pedantic mode. The homepage of Nuitka is listed, a watch file can check for new releases, the git repository and the gitweb are referenced, etc.
- Use
os.path.join
in more of the test code to achieve more Windows portability for them. - Some more PyLint cleanups.
- There is now a
Crasher
test, for tests that crashed Nuitka previously. - Added a program test where the imported module does a
sys.exit()
and make sure it really doesn't continue after theSystemExit
exception that creates. - Cover the type of
__builtins__
in the main program and in imported modules in tests too. It's funny and differs between module and dict in CPython2. - Cover a final
print
statement without newline in the test. Must still receive a newline, which only happens whenPy_Finalize()
is called. - Added test with functions that makes a
raise
without an exception set. - Cover the calling of
vars()
on module level too. - Cover the use of eval in contractions and generator expressions too.
- Cover
func_defaults
and__default__
attributes for a function too. - Added test function with two
raise
in an exception handler, so that one becomes dead code and removed without the crash.
The "git flow" was really great in this release cycle. There were many hot fix releases being made, so that the bugs could be addressed immediately without requiring the overhead of a full release. I believe that this makes Nuitka clearly one of the best supported projects.
This quick turn-around also encourages people to report more bugs, which is only good. And the structure is there to hold it. Of course, the many bug fixes meant that there is not as much new development, but that is not the priority, correctness is.
The work on Python3 is a bit strange. I don't need Python3 at all. I also believe it is that evil project to remove cruft from the Python core and make developers of all relevant Python software, add compatibility cruft to their software instead. Yet, I can't really stop to work on it. It has that appeal of small fixups here and there, and then something else works too.
Python3 work is like when I was first struggling with Nuitka to pass the
CPython2 unit tests for a first time. It's fun. And then it finds real actual
bugs that apply to CPython2 too. Not doing Py_Finalize
(but having to), the
slice operations shortcomings, the bug of subscript in-place, and so on. There
is likely more things hidden, and the earlier Python3 is supported, the more
benefit from increased test covered.
What's missing is more "hg" completeness. I think only the raise
without
exception set and the func_defaults
issue were going into its direction, but
it won't be enough yet.
This is to inform you about the new stable release of Nuitka. This time again many organizational improvements, some bug fixes, much improved compatibility and cleanups.
This release cycle had a focus on packaging Nuitka for easier consumption, i.e. automatic packaging, making automatic uploads, improvement documentation, and generally cleaning things up, so that Nuitka becomes more compatible and ultimately capable to run the "hg" test suite. It's not there yet, but this is a huge jump for usability of Nuitka and its compatibility, again.
Then lots of changes that make Nuitka approach Python3 support, the generated C++ for at least one large example is compiling with this new release. It won't link, but there will be later releases.
And there is a lot of cleanup going on, geared towards compatibility with line numbers in the frame object.
The main module was using
__main__
in tracebacks, but it must be<module>
. Released as 0.3.14a hot fix already.Workaround for "execfile cannot be used as an expression". It wasn't possible to use
execfile
in an expression, only as a statement.But then there is crazy enough code in e.g. mercurial that uses it in a lambda function, which made the issue more prominent. The fix now allows it to be an expression, except on the class level, which wasn't seen yet.
The in-line copy of Scons was not complete enough to work for "Windows" or with
--windows-target
for cross compile. Fixed.Cached frames didn't release the "back" frame, therefore holding variables of these longer than CPython does, which could cause ordering problems. Fixed for increased compatibility.
Handle "yield outside of function" syntax error in compiled source correctly. This one was giving a Nuitka backtrace, now it gives a
SyntaxError
as it needs to.Made syntax/indentation error output absolutely identical to CPython.
Using the frame objects
f_lineno
may fix endless amounts bugs related to traceback line numbers.
- Guesses the location of the MinGW compiler under Windows to default install
location, so it need not be added to
PATH
environment variable. Removes the need to modifyPATH
environment just for Nuitka to find it. - Added support for "lambda generators". You don't want to know what it is. Lets just say, it was the last absurd language feature out there, plus that didn't work. It now works perfect.
- You can now download a Windows installer and a Debian package that works on Debian Testing, current Ubuntu and Mint Linux.
- New release scripts give us the ability to have hot fix releases as download packages immediately. That means the "git flow" makes even more beneficial to the users.
- Including the generated "README.pdf" in the distribution archives, so it can be read instead of "README.txt". The text file is fairly readable, due to the use of ReStructured Text, but the PDF is even nicer to read, due to e.g. syntax highlighting of the examples.
- Renamed the main binaries to
nuitka
andnuitka-python
, so that there is no dependency on case sensitive file systems. - For Windows there are batch files
nuitka.bat
andnuitka-python.bat
to make Nuitka directly executable without finding thePython.exe
, which the batch files can tell from their own location. - There are now man pages of
nuitka
andnuitka-python
with examples for the most common use cases. They are of course included in the Debian package. - Don't strip the binary when executing it to analyse compiled binary with
valgrind
. It will give better information that way, without changing the code.
- Implemented
swapcontext
alike (swapFiber
) for x64 to achieve 8 times speedup for Generators. It doesn't do useless syscalls to preserve signal masks. Now Nuitka is faster at frame switching than CPython on x64, which is already good by design.
Using the frame objects to store current line of execution avoids the need to store it away in helper code at all. It ought to also help a lot with threading support, and makes Nuitka even more compatible, because now line numbers will be correct even outside tracebacks, but for mere stack frame dumps.
Moved the
for_return
detection from code generation to tree building where it belongs. Yield statements used as return statements need slightly different code for Python2.6 difference. That solved an oldTODO
.Much Python3 portability work. Sometimes even improving existing code, the Python compiler code had picked up a few points, where the latest Nuitka didn't work with Python3 anymore, when put to actual compile.
The test covered only syntax, but e.g. meta classes need different code in CPython3, and that's now supported. Also helper code was made portable in more places, but not yet fully. This will need more work.
Cleaned up uses of debug defines, so they are now more consistent and in one place.
Some more PyLint cleanups.
- The tests are now executed by Python scripts and cover
stderr
output too. Before we only checkedstdout
. This unveiled a bunch of issues Nuitka had, but went unnoticed so far, and triggered e.g. the frame line number improvements. - Separate syntax tests.
- The scripts to run the tests now are all in pure Python. This means, no more MinGW shell is needed to execute the tests.
The Debian package, Windows installer, etc. are now automatically updated and uploaded. From here on, there can be such packages for the hot fix releases too.
The exception tracebacks are now correct by design, and better covered.
The generator performance work showed that the approach taken by Nuitka is in fact fast. It was fast on ARM already, but it's nice to see that it's now also fast on x64. Programs using generators will be affected a lot by this.
Overall, this release brings Nuitka closer to usability. Better binary names, man pages, improved documentation, issue tracker, etc. all there now. I am in fact now looking for a sponsor for the Debian package to upload it into Debian directly.
Update
The upload to Debian happened for 0.3.18 and was done by Yaroslav Halchenko.
What's missing is more "hg" completeness. The frame release issue helped it, but
inspect.getargs()
doesn't work yet, and is a topic for a future
release. Won't be easy, as func_defaults
will be an invasive change too.
This is to inform you about the new stable release of Nuitka. This time it contains mostly organisational improvements, some bug fixes, improved compatibility and cleanups.
It is again the result of working towards compilation of a real program
(Mercurial). This time, I have added support for proper handling of compiled
types by the inspect
module.
- Fix for "Missing checks in parameter parsing with star list, star dict and positional arguments". There was whole in the checks for argument counts, now the correct error is given. Fixed in 0.3.13a already.
- The simple slice operations with 2 values, not extended with 3 values, were not applying the correct order for evaluation. Fixed in 0.3.13a already.
- The simple slice operations couldn't handle
None
as the value for lower or upper index. Fixed in 0.3.11a already. - The in-place simple slice operations evaluated the slice index expressions twice, which could cause problems if they had side effects. Fixed in 0.3.11a already.
- Run time patching the
inspect
module so it accepts compiled functions, compiled methods, and compiled generator objects. Thetest_inspect
test of CPython is nearly working unchanged with this. - The generator functions didn't have
CO_GENERATOR
set in their code object, setting it made compatible with CPython in this regard too. The inspect module will therefore return correct value forinspect.isgeneratorfunction()
too.
- Slice indexes that are
None
are now constant propagated as well. - Slightly more efficient code generation for dual star arg functions, removing useless checks.
- Moved the Scons, static C++ files, and assembler files to new package
nuitka.build
where also nowSconsInterface
module lives. - Moved the Qt dialog files to
nuitka.gui
- Moved the "unfreezer" code to its own static C++ file.
- Some PyLint cleanups.
- New test
Recursion
to cover recursive functions. - New test
Inspection
to cover the patching ofinspect
module. - Cover
execfile
on the class level as well inExecEval
test. - Cover evaluation order of simple slices in
OrderCheck
too.
There is a new issue tracker available under http://bugs.nuitka.net
Please register and report issues you encounter with Nuitka. I have put all the known issues there and started to use it recently. It's Roundup based like http://bugs.python.org is, so people will find it familiar.
The
setup.py
is now apparently functional. The source releases for download are made it with, and it appears the binary distributions work too. We may now build a windows installer. It's currently in testing, we will make it available when finished.
The new source organisation makes packaging Nuitka really easy now. From here, we can likely provide "binary" package of Nuitka soon. A windows installer will be nice.
The patching of inspect
works wonders for compatibility for those programs
that insist on checking types, instead of doing duck typing. The function call
problem, was an issue found by the Mercurial test suite.
For the "hg.exe" to pass all of its test suite, more work may be needed, this is the overall goal I am currently striving for. Once real world programs like Mercurial work, we can use these as more meaningful benchmarks and resume work on optimization.
This release is mostly the result of working towards compilation of a real
programs (Mercurial) and to merge and finalize the frame stack work. Now Nuitka
has a correct frame stack at all times, and supports func_code
and
gi_code
objects, something previously thought to be impossible.
Actually now it's only the "bytecode" objects that won't be there. And not
attributes of func_code
are meaningful yet, but in theory can be supported.
Due to the use of the "git flow" for Nuitka, most of the bugs listed here were already fixed in on the stable release before this release. This time there were 5 such hot fix releases, sometimes fixing multiple bugs.
In case of syntax errors in the main program, an exception stack was giving that included Nuitka code. Changed to make the same output as CPython does. Fixed in 0.3.12a already.
The star import (
from x import *
) didn't work for submodules. Providing*
as the import list to the respective code allowed to drop the complex lookups we were doing before, and to simply trust CPython C/API to do it correctly. Fixed in 0.3.12 already.The absolute import is not the default of CPython 2.7 it seems. A local
posix
package shadows the standard library one. Fixed in 0.3.12 already.In
--deep
mode, a module may contain a syntax error. This is e.g. true of "PyQt" withport_v3
included. These files contain Python3 syntax and fail to be imported in Python2, but that is not to be considered an error. These modules are now skipped with a warning. Fixed in 0.3.12b already.The code to import modules wasn't using the
__import__
built-in, which prevented__import__
overriding code to work. Changed import to use the built-in. Fixed in 0.3.12c already.The code generated for the
__import__
built-in with constant values was doing relative imports only. It needs to attempt relative and absolut imports. Fixed in 0.3.12c already.The code of packages in "__init__.py" believed it was outside of the package, giving problems for package local imports. Fixed in 0.3.12d already.
It appears that "Scons", which Nuitka uses internally and transparent to you, to execute the compilation and linking tasks, was sometimes not building the binaries or shared libraries, due to a false caching. As a workaround, these are now erased before doing the build. Fixed in 0.3.12d already.
The use of
in
andnot in
in comparison chains (e.g.a < b < c
is one), wasn't supported yet. The use of these in comparison chainsa in b in c
is very strange.Only in the
test_grammar.py
it was ever used I believe. Anyway, it's supported now, solving thisTODO
and reducing the difference. Fixed in 0.3.12e already.The order of evaluation for
in
andnot in
operators wasn't enforced in a portable way. Now it is correct on "ARM" too. Fixed in 0.3.12e already.
- The built-ins
GeneratorExit
andStopIteration
are optimized to their Python C/API names where possible as well.
- The
__file__
attribute of modules was the relative filename, but for absolute filenames these become a horrible mess at least on Linux. - Added assertion helpers for sane frame and code objects and use them.
- Make use of
assertObject
in more places. - Instead of using
os.path.sep
all over, added a helperUtils.joinpath
that hides this and usingos.path.join
. This gives more readable code. - Added traces to the "unfreezer" guarded by a define. Helpful in analyzing import problems.
- Some PyLint cleanups removing dead code, unused variables, useless pass statement, etc.
- New tests to cover
SyntaxError
andIndentationError
from--deep
imports and in main program. - New test to cover evaluation order of
in
andnot in
comparisons. - New test to cover package local imports made by the "__init__.py" of the package.
- Drop "compile_itself.sh" in favor of the new "compile_itself.py", because the later is more portable.
- The logging output is now nicer, and for failed recursions, outputs the line that is having the problem.
The frame stack work and the func_code
are big for compatibility.
The func_code
was also needed for "hg" to work. For Mercurial to pass all of
its test suite, more work will be needed, esp. the inspect
module needs to
be run-time patched to accept compiled functions and generators too.
Once real world programs like Mercurial work, we can use these as more meaningful benchmarks and resume work on optimization.
This is to inform you about the new release of Nuitka many bug fixes, and
substantial improvements especially in the organizational area. There is a new
"User Manual" (PDF), with much improved content, a
sys.meta_path
based import mechanism for --deep
mode, git flow goodness.
This release is generally also the result of working towards compilation of a real programs (Mercurial) and to get things work more nicely on Windows by default. Thanks go to Liu Zhenhai for helping me with this goal.
Due to the use of the "git flow", most of the bugs listed here were already fixed in on the stable release before this release. And there were many of these.
The order of evaluation for base classes and class dictionaries was not enforced.
Apparently nothing in the CPython test suite did that, I only noticed during debugging that Nuitka gave a different error than CPython did, for a class that had an undefined base class, because both class body and base classes were giving an error. Fixed in 0.3.11a already.
Method objects didn't hold a reference to the used class.
The effect was only noticed when
--python-debug
was used, i.e. the debug version of Python linked, because then the garbage collector makes searches. Fixed in 0.3.11b already.Set
sys.executable
on Linux as well. On Debian it is otherwise/usr/bin/python
which might be a different version of Python entirely. Fixed in 0.3.11c already.Embedded modules inside a package could hide package variables of the same name. Learned during PyCON DE about this corner case. Fixed in 0.3.11d already.
Packages could be duplicated internally. This had no effect on generated code other than appearing twice in the list if frozen modules. Fixed in 0.3.11d already.
When embedding modules from outside current directory, the look-up failed. The embedding only ever worked for the compile itself and programs test cases, because they are all in the current directory then. Fixed in 0.3.11e already.
The check for ARM target broke Windows support in the Scons file. Fixed in 0.3.11f already.
The star import from external modules failed with an error in
--deep
mode. Fixed in 0.3.11g already.Modules with a parent package could cause a problem under some circumstances. Fixed in 0.3.11h already.
One call variant, with both list and dict star arguments and keyword arguments, but no positional parameters, didn't have the required C++ helper function implemented. Fixed in 0.3.11h already.
The detection of the CPU core count was broken on my hexacore at least. Gave 36 instead of 6, which is a problem for large programs. Fixed in 0.3.11h already.
The in-line copy of Scons didn't really work on Windows, which was sad, because we added it to simplify installation on Windows precisely because of this.
Cleaning up the build directory from old sources and object files wasn't portable to Windows and therefore wasn't effective there.
From imports where part of the imported were found modules and parts were not, didn't work. Solved by the feature branch
meta_path_import
that was merged for this release.Newer MinGW gave warnings about the default visibility not being possible to apply to class members. Fixed by not setting this default visibility anymore on Windows.
The
sys.executable
gave warnings on Windows because of backslashes in the path. Using a raw string to prevent such problems.The standard library path was hard coded. Changed to run time detection.
- Version checks on Python runtime now use a new define
PYTHON_VERSION
that makes it easier. I don't likePY_VERSION_HEX
, because it is so unreadable. Makes some of the checks a lot more safe. - The
sys.meta_path
based import from themeta_path_import
feature branch allowed the cleanup the way importing is done. It's a lot less code now. - Removed some unused code. We will aim at making Nuitka the tool to detect dead code really.
- Moved
nuitka.Nodes
tonuitka.nodes.Nodes
, that is what the package is intended for, the split will come later.
- New tests for import variants that previously didn't work: Mixed imports. Imports from a package one level up. Modules hidden by a package variable, etc.
- Added test of function call variant that had no test previously. Only found it when compiling "hg". Amazing how nothing in my tests, CPython tests, etc. used it.
- Added test to cover the partial success of import statements.
- Added test to cover evaluation order of class definitions.
Migrated the "README.txt" from org-mode to ReStructured Text, which allows for a more readable document, and to generate a nice "User Manual" in PDF form.
The amount of information in "README.txt" was increased, with many more subjects are now covered, e.g. "git flow" and how to join Nuitka development. It's also impressive to see what code blocks and syntax highlighting can do for readability.
The Nuitka git repository has seen multiple hot fixes.
These allowed to publish bug fixes immediately after they were made, and avoided the need for a new release just to get these out. This really saves me a lot of time too, because I can postpone releasing the new version until it makes sense because of other things.
Then there was a feature branch
meta_path_import
that lived until being merged todevelop
to improve the import code, which is now released onmaster
as stable. Getting that feature right took a while.And there is the feature branch
minimize_CPython26_tests_diff
which has some success already in documenting the required changes to the "CPython26" test suite and in reducing the amount of differences, while doing it. We have a frame stack working there, albeit in too ugly code form.The release archives are now built using
setuptools
. You can now also download a zip file, which is probably more Windows friendly. The intention is to work on that to makesetup.py
produce a Nuitka install that won't rely on any environment variables at all. Right nowsetup.py
won't even allow any other options thansdist
to be given.Ported "compile_itself.sh" to "compile_itself.py", i.e. ported it to Python. This way, we can execute it easily on Windows too, where it currently still fails. Replacing
diff
,rm -rf
, etc. is a challenge, but it reduces the dependency on MSYS tools on Windows.The compilation of standard library is disabled by default, but
site
ordist
packages are now embedded. To include even standard library, there is a--really-deep
option that has to be given in addition to--deep
, which forces this.
Again, huge progress. The improved import mechanism is very beautiful. It appears that little is missing to compile real world programs like "hg" with Nuitka. The next release cycle will focus on that and continue to improve the Windows support which appears to have some issues.
This is to inform you about the new release of Nuitka with some bug fixes and portability work.
This release is generally cleaning up things, and makes Nuitka portable to ARM Linux. I used to host the Nuitka homepage on that machine, but now that it's no longer so, I can run heavy compile jobs on it. To my surprise, it found many portability problems. So I chose to fix that first, the result being that Nuitka now works on ARM Linux too.
- The order of slice expressions was not correct on x86 as well, and I found that with new tests only. So the porting to ARM revealed a bug category, I previously didn't consider.
- The use of
linux2
in the Scons file is potentially incompatible with Linux 3.0, although it seems that at least on Debian thesys.platform
was changed back tolinux2
. Anyway, it's probably best to allow just anything that starts withlinux
these days. - The
print
statement worked like aprint
function, i.e. it first evaluated all printed expressions, and did the output only then. That is incompatible in case of exceptions, where partial outputs need to be done, and so that got fixed.
- Function calls now each have a dedicated helper function, avoiding in some
cases unnecessary work. We will may build further on this and in-line
PyObject_Call
differently for the special cases.
Moved many C++ helper declarations and in-line implementations to dedicated header files for better organisation.
Some dependencies were removed and consolidated to make the dependency graph sane.
Multiple decorators were in reverse order in the node tree. The code generation reversed it back, so no bug, yet that was a distorted tree.
Finding this came from the ARM work, because the "reversal" was in fact just the argument evaluation order of C++ under x86/x64, but on ARM that broke. Correcting it highlighted this issue.
The deletion of slices, was not using
Py_ssize
for indexes, disallowing some kinds of optimization, so that was harmonized.The function call code generation got a general overhaul. It is now more consistent, has more helpers available, and creates more readable code.
PyLint is again happier than ever.
- There is a new basic test
OrderChecks
that covers the order of expression evaluation. These problems were otherwise very hard to detect, and in some cases not previously covered at all. - Executing Nuitka with Python3 (it won't produce correct Python3 C/API code) is now part of the release tests, so non-portable code of Nuitka gets caught.
- Support for ARM Linux. I will make a separate posting on the challenges of this. Suffice to say now, that C++ leaves way too much things unspecified.
- The Nuitka git repository now uses "git flow". The new git policy will be detailed in another separate posting.
- There is an unstable
develop
branch in which the development occurs. For this release ca. 40 commits were done to this branch, before merging it. I am also doing more fine grained commits now. - Unlike previously, there is
master
branch for the stable release. - There is a script "make-dependency-graph.sh" (Update: meanwhile it was renamed to "make-dependency-graph.py") to produce a dependency graphs of Nuitka. I detected a couple of strange things through this.
- The Python3
__pycache__
directories get removed too by the cleanup script.
We only have "PyStone" now, and on a new machine, so the numbers cannot be compared to previous releases:
python 2.6:
Pystone(1.1) time for 50000 passes = 0.48 This machine benchmarks at 104167 pystones/second
Nuitka 0.3.11 (driven by python 2.6):
Pystone(1.1) time for 50000 passes = 0.19 This machine benchmarks at 263158 pystones/second
So this a speedup factor of 258%, last time on another machine it was 240%. Yet it only proves that the generated and compiled are more efficient than bytecode, but Nuitka doesn't yet do the relevant optimization. Only once it does, the factor will be significantly higher.
Overall, there is quite some progress. Nuitka is a lot cleaner now, which will help us later only. I wanted to get this out, mostly because of the bug fixes, and of course just in case somebody attempts to use it on ARM.
This new release is major milestone 2 work, enhancing practically all areas of Nuitka. The focus was roundup and breaking new grounds with structural optimization enhancements.
Exceptions now correctly stack.
When you catch an exception, there always was the exception set, but calling a new function, and it catching the exception, the values of
sys.exc_info()
didn't get reset after the function returned.This was a small difference (of which there are nearly none left now) but one that might effect existing code, which affects code that calls functions in exception handling to check something about it.
So it's good this is resolved now too. Also because it is difficult to understand, and now it's just like CPython behaves, which means that we don't have to document anything at all about it.
Using
exec
in generator functions got fixed up. I realized that this wouldn't work while working on other things. It's obscure yes, but it ought to work.Lambda generator functions can now be nested and in generator functions. There were some problems here with the allocation of closure variables that got resolved.
List contractions could not be returned by lambda functions. Also a closure issue.
When using a mapping for globals to
exec
oreval
that had a side effect on lookup, it was evident that the lookup was made twice. Correcting this also improves the performance for the normal case.
Statically raised as well as predicted exceptions are propagated upwards, leading to code and block removal where possible, while maintaining the side effects.
This is brand new and doesn't do everything possible yet. Most notable, the matching of raised exception to handlers is not yet performed.
Built-in exception name references and creation of instances of them are now optimized as well, which leads to faster exception raising/catching for these cases.
More kinds of calls to built-ins are handled, positional parameters are checked and more built-ins are covered.
Notable is that now checks are performed if you didn't potentially overload e.g. the
len
with your own version in the module. Locally it was always detected already. So it's now also safe.All operations and comparisons are now simulated if possible and replaced with their result.
In the case of predictable true or false conditions, not taken branches are removed.
Empty branches are now removed from most constructs, leading to sometimes cleaner code generated.
- Removed the lambda body node and replaced it with function body. This is a great win for the split into body and builder. Regular functions and lambda functions now only differ in how the created body is used.
- Large cleanup of the operation/comparison code. There is now only use of a simulator function, which exists for every operator and comparison. This one is then used in a prediction call, shared with the built-in predictions.
- Added a
Tracing
module to avoid future imports ofprint_function
, which annoyed me many times by causing syntax failures for when I quickly added a print statement, not noting it must have the braces. - PyLint is happier than ever.
Enhanced
OverflowFunctions
test to cover even deeper nesting of overflow functions taking closure from each level. While it's not yet working, this makes clearer what will be needed. Even if this code is obscure, I would like to be that correct here.Made
Operators
test to cover the `` operator as well.Added to
ListContractions
the case where a contraction is returned by a lambda function, but still needs to leak its loop variable.Enhanced
GeneratorExpressions
test to cover lambda generators, which is really crazy code:def y(): yield((yield 1),(yield 2))
Added to
ExecEval
a case where theexec
is inside a generator, to cover that too.Activated the testing of
sys.exc_info()
inExceptionRaising
test. This was previously commented out, and now I added stuff to illustrate all of the behavior of CPython there.Enhanced
ComparisonChains
test to demonstrate that the order of evaluations is done right and that side effects are maintained.Added
BuiltinOverload
test to show that overloaded built-ins are actually called and not the optimized version. So code like this has to print 2 lines:from __builtin__ import len as _len def len(x): print x return _len(x) print len(range(9))
- Changed "README.txt" to no longer say that "Scons" is a requirement. Now that
it's included (patched up to work with
ctypes
on Windows), we don't have to say that anymore. - Documented the status of optimization and added some more ideas.
- There is now an option to dump the node tree after optimization as XML. Not currently use, but is for regression testing, to identify where new optimization and changes have an impact. This make it more feasible to be sure that Nuitka is only becoming better.
- Executable with Python3 again, although it won't do anything, the necessary code changes were done.
It's nice to see, that I some long standing issues were resolved, and that structural optimization has become almost a reality.
The difficult parts of exception propagation are all in place, now it's only details. With that we can eliminate and predict even more of the stupid code of "pybench" at compile time, achieving more infinite speedups.
This is about the new release of Nuitka which some bug fixes and offers a good speed improvement.
This new release is major milestone 2 work, enhancing practically all areas of Nuitka. The main focus was on faster function calls, faster class attributes (not instance), faster unpacking, and more built-ins detected and more thoroughly optimizing them.
- Exceptions raised inside with statements had references to the exception and traceback leaked.
- On Windows the binaries
sys.executable
pointed to the binary itself instead of the Python interpreter. Changed, because some code usessys.executable
to know how to start Python scripts. - There is a bug (fixed in their repository) related to C++ raw strings and C++ "trigraphs" that affects Nuitka, added a workaround that makes Nuitka not emit "trigraphs" at all.
- The check for mutable constants was erroneous for tuples, which could lead to assuming a tuple with only mutable elements to be not mutable, which is of course wrong.
This time there are so many new optimization, it makes sense to group them by the subject.
- The code to add a traceback is now our own, which made it possible to use frames that do not contain line numbers and a code object capable of lookups.
- Raising exceptions or adding to tracebacks has been made way faster by reusing a cached frame objects for the task.
- The class used for saving exceptions temporarily (e.g. used in
try
/finally
code, or with statement) has been improved so it doesn't make a copy of the exception with a C++new
call, but it simply stores the exception properties itself and creates the exception object only on demand, which is more efficient. - When catching exceptions, the addition of tracebacks is now done without exporting and re-importing the exception to Python, but directly on the exception objects traceback, this avoids a useless round trip.
- Uses of PyObject_Call provide
NULL
as the dictionary, instead of an empty dictionary, which is slightly faster for function calls. - There are now dedicated variants for complex function calls with
*
and**
arguments in all forms. These can take advantage of easier cases. For example, a merge with star arguments is only needed if there actually were any of these. - The check for non-string values in the
**
arguments can now be completely short-cut for the case of a dictionary that has never had a string added. There is now code that detects this case and skips the check, eliminating it as a performance concern.
Reversed the order in which parameters are checked.
Now the keyword dictionary is iterated first and only then the positional arguments after that is done. This iteration is not only much faster (avoiding repeated lookups for each possible parameter), it also can be more correct, in case the keyword argument is derived from a dictionary and its keys mutate it when being compared.
Comparing parameter names is now done with a fast path, in which the pointer values are compare first. This can avoid a call to the comparison at all, which has become very likely due to the interning of parameter name strings, see below.
Added a dedicated call to check for parameter equality with rich equality comparison, which doesn't raise an exception.
Unpacking of tuples is now using dedicated variants of the normal unpacking code instead of rolling out everything themselves.
- The class type (in executables, not yet for extension modules) is changed to a faster variant of our own making that doesn't consider the restricted mode a possibility. This avoids very expensive calls, and makes accessing class attributes in compiled code and in non-compiled code faster.
- Access to attributes (but not of instances) got in-lined and therefore much faster. Due to other optimization, a specific step to intern the string used for attribute access is not necessary with Nuitka at all anymore. This made access to attributes about 50% faster which is big of course.
- The bug for mutable tuples also caused non-mutable tuples to be considered as mutable, which lead to less efficient code.
- The constant creation with the g++ bug worked around, can now use raw strings
to create string constants, without resorting to un-pickling them as a work
around. This allows us to use
PyString_FromStringAndSize
to create strings again, which is obviously faster, and had not been done, because of the confusion caused by the g++ bug. - For string constants that are usable as attributes (i.e. match the identifier regular expression), these are now interned, directly after creation. With this, the check for identical value of pointers for parameters has a bigger chance to succeed, and this saves some memory too.
- For empty containers (set, dict, list, tuple) the constants created are now are not unstreamed, but created with the dedicated API calls, saving a bit of code and being less ugly.
- For mutable empty constant access (set, dict, list) the values are no longer
made by copying the constant, but instead with the API functions to create new
ones. This makes code like
a = []
a tiny bit faster. - For slice indices the code generation now takes advantage of creating a C++
Py_ssize_t
from constant value if possible. Before it was converting the integer constant at run time, which was of course wasteful even if not (very) slow.
- The creation of iterators got our own code. This avoids a function call and is otherwise only a small gain for anything but sequence iterators. These may be much faster to create now, as it avoids another call and repeated checks.
- The next on iterator got our own code too, which has simpler code flow, because it avoids the double check in case of NULL returned.
- The unpack check got simlar code to the next iterator, it also has simpler code flow now and avoids double checks.
Added support for the
list
,tuple
,dict
,str
,float
andbool
built-ins along with optimizing their use with constant parameter.Added support for the
int
andlong
built-ins, based on a new "call spec" object, that detects parameter errors at compile time and raises appropriate exceptions as required, plus it deals with keyword arguments just as well.So, to Nuitka it doesn't matter now it you write
int(value) ``or ``int(x = value)
anymore. Thebase
parameter of these built-ins is also supported.The use of this call spec mechanism will the expanded, currently it is not applied to the built-ins that take only one parameter. This is a work in progress as is the whole built-ins business as not all the built-ins are covered yet.
- In 0.3.8 per module global classes were introduced, but the
IMPORT_MODULE
kept using the old universal class, this got resolved and the old class is now fully gone. - Using
assertObject
in more cases, and in more places at all, catches errors earlier on. - Moved the addition to tracebacks into the
_PythonException
class, where it works directly on the contained traceback. This is cleaner as it no longer requires to export exceptions to Python, just to add a traceback entry. - Some
PyLint
cleanups were done, reducing the number of reports a bit, but there is still a lot to do. - Added a
DefaultValueIdentifier
class that encapsulates the access to default values in the parameter parsing more cleanly. - The module
CodeTemplatesListContractions
was renamed toCodeTemplatesContractions
to reflect the fact that it deals with all kinds of contractions (also set and dict contractions), not just list contractions. - Moved the with related template to its own module
CodeTemplatesWith
, so its easier to find. - The options handling for g++ based compilers was cleaned up, so that g++ 4.6 and MinGW are better supported now.
- Documented more aspects of the Scons build file.
- Some more generated code white space fixes.
- Moved some helpers to dedicated files. There is now
calling.hpp
for function calls, animporting.cpp
for import related stuff. - Moved the manifest generation to the scons file, which now produces ready to use executables.
- Added a improved version of "pybench" that can cope with the "0 ms" execution time that Nuitka has for some if its sub-tests.
- Reference counting test for with statement was added.
- Micro benchmarks to demonstrate try finally performance when an exception travels through it.
- Micro benchmark for with statement that eats up exceptions raised inside the block.
- Micro benchmarks for the read and write access to class attributes.
- Enhanced
Printing
test to cover the trigraphs constant bug case. Output is required to make the error detectable. - Enhanced
Constants
test to cover repeated mutation of mutable tuple constants, this covers the bug mentioned.
- Added a credits section to the "README.txt" where I give credit to the people who contributed to Nuitka, and the projects it is using. I will make it a separate posting to cite these.
- Documented the requirements on the compiler more clearly, document the fact that we require scons and which version of Python (2.6 or 2.7).
- The is now a codespeed implementation up and running with historical data for up to Nuitka 0.3.8 runs of "PyStone" and with pybench. It will be updated for 0.3.9 once I have the infrastructure in place to do that automatically.
- The cleanup script now also removes .so files.
- The handling of options for g++ got improved, so it's the same for g++ and MinGW compilers, plus adequate errors messages are given, if the compiler version is too low.
- There is now a
--unstriped
option that just keeps the debug information in the file, but doesn't keep the assertions. This will be helpful when looking at generated assembler code from Nuitka to not have the distortions that--debug
causes (reduced optimization level, assertions, etc.) and instead a clear view.
This is to inform you about the new release of Nuitka with some real news and a slight performance increase. The significant news is added "Windows Support". You can now hope to run Nuitka on Windows too and have it produce working executables against either the standard Python distribution or a MinGW compiled Python.
There are still some small things to iron out, and clearly documentation needs
to be created, and esp. the DLL hell problem of msvcr90.dll
vs. msvcrt.dll
, is not yet fully resolved, but appears to be not as harmful,
at least not on native Windows.
I am thanking Khalid Abu Bakr for making this possible. I was surprised to see
this happen. I clearly didn't make it easy. He found a good way around
ucontext
, identifier clashes, and a very tricky symbol problems where the
CPython library under Windows exports less than under Linux. Thanks a whole lot.
Currently the Windows support is considered experimental and works with MinGW 4.5 or higher only.
Otherwise there have been the usual round of performance improvements and more cleanups. This release is otherwise milestone 2 work only, which will have to continue for some time more.
- Lambda generators were not fully compatible, their simple form could yield an extra value. The behavior for Python 2.6 and 2.7 is also different and Nuitka now mimics both correctly, depending on the used Python version
- The given parameter count cited in the error message in case of too many parameters, didn't include the given keyword parameters in the error message.
- There was an
assert False
right after warning about not found modules in the--deep
mode, which was of course unnecessary.
When unpacking variables in assignments, the temporary variables are now held in a new temporary class that is designed for the task specifically.
This avoids the taking of a reference just because the
PyObjectTemporary
destructor insisted on releasing one. The new classPyObjectTempHolder
hands the existing reference over and releases only in case of exceptions.When unpacking variable in for loops, the value from the iterator may be directly assigned, if it's to a variable.
In general this would be possible for every assignment target that cannot raise, but the infrastructure cannot tell yet, which these would be. This will improve with more milestone 3 work.
Branches with only
pass
inside are removed,pass
statements are removed before the code generation stage. This makes it easier to achieve and decide empty branches.There is now a global variable class per module. It appears that it is indeed faster to roll out a class per module accessing the
module *
rather than having one class and use amodule **
, which is quite disappointing from the C++ compiler.Also
MAKE_LIST
andMAKE_TUPLE
have gained special cases for the 0 arguments case. Even when the size of the variadic template parameters should be known to the compiler, it seems, it wasn't eliminating the branch, so this was a speedup measured with valgrind.Empty tried branches are now replaced when possible with
try
/except
statements,try
/finally
is simplified in this case. This gives a cleaner tree structure and less verbose C++ code which the compiler threw away, but was strange to have in the first place.In conditions the
or
andand
were evaluated with Python objects instead of with C++ bool, which was unnecessary overhead.List contractions got more clever in how they assign from the iterator value.
It now uses a
PyObjectTemporary
if it's assigned to multiple values, aPyObjectTempHolder
if it's only assigned once, to something that could raise, or aPyObject *
if an exception cannot be raised. This avoids temporary references completely for the common case.
- The
if
,for
, andwhile
statements had always emptyelse
nodes which were then also in the generated C++ code as empty branches. No harm to performance, but this got cleaned up. - Some more generated code white space fixes.
The CPython 2.7 test suite now also has the
doctests
extracted to static tests, which improves test coverage for Nuitka again.This was previously only done for CPython 2.6 test suite, but the test suites are different enough to make this useful, e.g. to discover newly changed behavior like with the lambda generators.
Added Shed Skin 0.7.1 examples as benchmarks, so we can start to compare Nuitka performance in these tests. These will be the focus of numbers for the 0.4.x release series.
Added a micro benchmark to check unpacking behavior. Some of these are needed to prove that a change is an actual improvement, when its effect can go under in noise of in-line vs. no in-line behavior of the C++ compiler.
Added "pybench" benchmark which reveals that Nuitka is for some things much faster, but there are still fields to work on. This version needed changes to stand the speed of Nuitka. These will be subject of a later posting.
- There is now a "tests/benchmarks/micro" directory to contain tiny benchmarks that just look at a single aspect, but have no other meaning, e.g. the "PyStone" extracts fall into this category.
- There is now a
--windows-target
option that attempts a cross-platform build on Linux to Windows executable. This is using "MingGW-cross-env" cross compilation tool chain. It's not yet working fully correctly due to the DLL hell problem with the C runtime. I hope to get this right in subsequent releases. - The
--execute
option uses wine to execute the binary if it's a cross-compile for windows. - Native windows build is recognized and handled with MinGW 4.5, the VC++ is not supported yet due to missing C++0x support.
- The basic test suite ran with Windows so far only and some adaptations were necessary. Windows new lines are now ignored in difference check, and addresses under Windows are upper case, small things.
python 2.6:
Pystone(1.1) time for 50000 passes = 0.65 This machine benchmarks at 76923.1 pystones/second
Nuitka 0.3.8 (driven by python 2.6):
Pystone(1.1) time for 50000 passes = 0.27 This machine benchmarks at 185185 pystones/second
This is a 140% speed increase of 0.3.8 compared to CPython, up from 132% compared to the previous release.
This is about the new release with focus on performance and cleanups. It
indicates significant progress with the milestone this release series really is
about as it adds a compiled_method
type.
So far functions, generator function, generator expressions were compiled
objects, but in the context of classes, functions were wrapped in CPython
instancemethod
objects. The new compiled_method
is specifically designed
for wrapping compiled_function
and therefore more efficient at it.
- When using
Python
orNuitka.py
to execute some script, the exit code in case of "file not found" was not the same as CPython. It should be 2, not 1. - The exit code of the created programs (
--deep
mode) in case of an uncaught exception was 0, now it an error exit with value 1, like CPython does it. - Exception tracebacks created inside
with
statements could contain duplicate lines, this was corrected.
Global variable assignments now also use
assign0
where no reference exists.The assignment code for module variables is actually faster if it needs not drop the reference, but clearly the code shouldn't bother to take it on the outside just for that. This variant existed, but wasn't used as much so far.
The instance method objects are now Nuitka's own compiled type too. This should make things slightly faster by itself.
Our new compiled method objects support dedicated method parsing code, where
self
is passed directly, allowing to make calls taking a fast path in parameter parsing.This avoids allocating/freeing a
tuple
object per method call, while reduced 3% ticks in "PyStone" benchmark, so that's significant.Solved a
TODO
ofBUILTIN_RANGE
to change it to pre-allocating the list in the final size as we normally do everywhere else. This was a tick reduction of 0.4% in "PyStone" benchmark, but the measurement method normalizes on loop speed, so it's not visible in the numbers output.Parameter variables cannot possibly be uninitialized at creation and most often they are never subject to a
del
statement. Adding dedicated C++ variable classes gave a big speedup, around 3% of "PyStone" benchmark ticks.Some abstract object operations were re-implemented, which allows to avoid function calls e.g. in the
ITERATOR_NEXT
case, this gave a few percent on "PyStone" as well.
- New package
nuitka.codegen
to contain all code generation related stuff, movednuitka.templates
tonuitka.codegen.templates
as part of that. - Inside the
nuitka.codegen
package theMainControl
module now longer reaches intoGenerator
for simple things, but goes throughCodeGeneration
for everything now. - The
Generator
module uses almost no tree nodes anymore, but instead gets information passed in function calls. This allows for a cleanup of the interface towardsCodeGeneration
. Gives a cleaner view on the C++ code generation, and generally furthers the goal of other than C++ language backends. - More "PyLint" work, many of the reported warnings have been addressed, but it's not yet happy.
- Defaults for
yield
andreturn
areNone
and these values are now already added (as constants) during tree building so that no such special cases need to be dealt with inCodeGeneration
and future analysis steps. - Parameter parsing code has been unified even further, now the whole entry
point is generated by one of the function in the new
nuitka.codegen.ParameterParsing
module. - Split variable, exception, built-in helper classes into separate header files.
- The exit codes of CPython execution and Nuitka compiled programs are now compared as well.
- Errors messages of methods are now covered by the
ParameterErrors
test as well.
A new script "benchmark.sh" (now called "run-valgrind.py") script now starts "kcachegrind" to display the valgrind result directly.
One can now use it to execute a test and inspect valgrind information right away, then improve it. Very useful to discover methods for improvements, test them, then refine some more.
The "check-release.sh" script needs to unset
NUITKA_EXTRA_OPTIONS
or else the reflection test will trip over the changed output paths.
python 2.6:
Pystone(1.1) time for 50000 passes = 0.65 This machine benchmarks at 76923.1 pystones/second
Nuitka 0.3.7 (driven by python 2.6):
Pystone(1.1) time for 50000 passes = 0.28 This machine benchmarks at 178571 pystones/second
This is a 132% speed of 0.3.7 compared to CPython, up from 109% compare to the previous release. This is a another small increase, that can be fully attributed to milestone 2 measures, i.e. not analysis, but purely more efficient C++ code generation and the new compiled method type.
One can now safely assume that it is at least twice as fast, but I will try and get the PyPy or Shedskin test suite to run as benchmarks to prove it.
No milestone 3 work in this release. I believe it's best to finish with milestone 2 first, because these are quite universal gains that we should have covered.
The major point this for this release is cleanup work, and generally bug fixes,
esp. in the field of importing. This release cleans up many small open ends of
Nuitka, closing quite a bunch of consistency TODO
items, and then aims at
cleaner structures internally, so optimization analysis shall become "easy". It
is a correctness and framework release, not a performance improvement at all.
Imports were not respecting the
level
yet. Code like this was not working, now it is:from .. import something
Absolute and relative imports were e.g. both tried all the time, now if you specify absolute or relative imports, it will be attempted in the same way than CPython does. This can make a difference with compatibility.
Functions with a "locals dict" (using
locals
built-in orexec
statement) were not 100% compatible in the way the locals dictionary was updated, this got fixed. It seems that directly updating a dict is not what CPython does at all, instead it only pushes things to the dictionary, when it believes it has to. Nuitka now does the same thing, making it faster and more compatible at the same time with these kind of corner cases.Nested packages didn't work, they do now. Nuitka itself is now successfully using nested packages (e.g.
nuitka.transform.optimizations
)
- The
--lto
option becomes usable. It's not measurably faster immediately, and it requires g++ 4.6 to be available, but then it at least creates smaller binaries and may provide more optimization in the future.
- Exceptions raised by pre-computed built-ins, unpacking, etc. are now transformed to raising the exception statically.
- There is now a
getVariableForClosure
that a variable provider can use. Before that it guessed fromgetVariableForReference
orgetVariableForAssignment
what might be the intention. This makes some corner cases easier. - Classes, functions and lambdas now also have separate builder and body nodes, which enabled to make getSameScopeNodes() really simple. Either something has children which are all in a new scope or it has them in the same scope.
- Twisted workarounds like
TransitiveProvider
are no longer needed, because class builder and class body were separated. - New packages
nuitka.transform.optimizations
andnuitka.transform.finalizations
, where the first wasnuitka.optimizations
before. There is also code innuitka.transform
that was previously in a dedicated module. This allowed to move a lot of displaced code. TreeBuilding
now has fast paths for all 3 forms, things that need a "provider", "node", and "source_ref"; things that need "node" and "source_ref"; things that need nothing at all, e.g. pass.- Variables now avoid building duplicated instances, but instead share one. Better for analysis of them.
- The Python 2.7 test suite is no longer run with Python 2.6 as it will just
crash with the same exception all the time, there is no
importlib
in 2.6, but every test is using that through test_support. - Nested packages are now covered with tests too.
- Imports of upper level packages are covered now too.
- Updated the "README.txt" with the current plan on optimization.
python 2.6:
Pystone(1.1) time for 50000 passes = 0.65 This machine benchmarks at 76923.1 pystones/second
Nuitka 0.3.6 (driven by python 2.6):
Pystone(1.1) time for 50000 passes = 0.31 This machine benchmarks at 161290 pystones/second
This is 109% for 0.3.6, but no change from the previous release. No surprise, because no new effective new optimization means have been implemented. Stay tuned for future release for actual progress.
This new release of Nuitka is an overall improvement on many fronts, there is no real focus this time, likely due to the long time it was in the making.
The major points are more optimization work, largely enhanced import handling and another improvement on the performance side. But there are also many bug fixes, more test coverage, usability and compatibility.
Something esp. noteworthy to me and valued is that many important changes were performed or at least triggered by Nicolas Dumazet, who contributed a lot of high quality commits as you can see from the gitweb history. He appears to try and compile Mercurial and Nuitka, and this resulted in important contributions.
- Nicolas found a reference counting bug with nested parameter calls. Where a
function had parameters of the form
a, (b,c)
it could crash. This got fixed and covered with a reference count test. - Another reference count problem when accessing the locals dictionary was corrected.
- Values
0.0
and-0.0
were treated as the same. They are not though, they have a different sign that should not get lost. - Nested contractions didn't work correctly, when the contraction was to iterate over another contraction which needs a closure. The problem was addressing by splitting the building of a contraction from the body of the contraction, so that these are now 2 nodes, making it easy for the closure handling to get things right.
- Global statements in function with local
exec()
would still use the value from the locals dictionary. Nuitka is now compatible to CPython with this too. - Nicolas fixed problems with modules of the same name inside different packages. We now use the full name including parent package names for code generation and look-ups.
- The
__module__
attribute of classes was only set after the class was created. Now it is already available in the class body. - The
__doc__
attribute of classes was not set at all. Now it is. - The relative import inside nested packages now works correctly. With Nicolas moving all of Nuitka to a package, the compile itself exposed many weaknesses.
- A local re-raise of an exception didn't have the original line attached but the re-raise statement line.
- Modules and packages have been unified. Packages can now also have code in "__init__.py" and then it will be executed when the package is imported.
- Nicolas added the ability to create deep output directory structures without
having to create them beforehand. This makes
--output-dir=some/deep/path
usable. - Parallel build by Scons was added as an option and enabled by default, which
enhances scalability for
--deep
compilations a lot. - Nicolas enhanced the CPU count detection used for the parallel build. Turned
out that
multithreading.cpu_count()
doesn't give us the number of available cores, so he contributed code to determine that. - Support for upcoming g++ 4.6 has been added. The use of the new option
--lto
has been been prepared, but right now it appears that the C++ compiler will need more fixes, before we can this feature with Nuitka. - The
--display-tree
feature got an overhaul and now displays the node tree along with the source code. It puts the cursor on the line of the node you selected. Unfortunately I cannot get it to work two-way yet. I will ask for help with this in a separate posting as we can really use a "python-qt" expert it seems. - Added meaningful error messages in the "file not found" case. Previously I just didn't care, but we sort of approach end user usability with this.
- Added optimization for the built-in
range()
which otherwise requires a module andbuiltin
module lookup, then parameter parsing. Now this is much faster with Nuitka and small ranges (less than 256 values) are converted to constants directly, avoiding run time overhead entirely. - Code for re-raise statements now use a simple re-throw of the exception where possible, and only do the hard work where the re-throw is not inside an exception handler.
- Constant folding of operations and comparisons is now performed if the operands are constants.
- Values of some built-ins are pre-computed if the operands are constants.
- The value of module attribute
__name__
is replaced by a constant unless it is assigned to. This is the first sign of upcoming constant propagation, even if only a weak one. - Conditional statement and/or their branches are eliminated where constant conditions allow it.
Nicolas moved the Nuitka source code to its own
nuitka
package. That is going to make packaging it a lot easier and allows cleaner code.Nicolas introduced a fast path in the tree building which often delegates (or should do that) to a function. This reduced a lot of the dispatching code and highlights more clearly where such is missing right now.
Together we worked on the line length issues of Nuitka. We agreed on a style and very long lines will vanish from Nuitka with time. Thanks for pushing me there.
Nicolas also did provide many style fixes and general improvements, e.g. using
PyObjectTemporary
in more places in the C++ code, or not usingstr.find
wherex in y
is a better choice.The node structure got cleaned up towards the direction that assigments always have an assignment as a child. A function definition, or a class definition, are effectively assignments, and in order to not have to treat this as special cases everywhere, they need to have assignment targets as child nodes.
Without such changes, optimization will have to take too many things into account. This is not yet completed.
Nicolas merged some node tree building functions that previously handled deletion and assigning differently, giving us better code reuse.
The constants code generation was moved to a
__constants.cpp
where it doesn't make __main__.cpp so much harder to read anymore.The module declarations have been moved to their own header files.
Nicolas cleaned up the scripts used to test Nuitka big time, removing repetitive code and improving the logic. Very much appreciated.
Nicolas also documented a things in the Nuitka source code or got me to document things that looked strange, but have reasons behind it.
Nicolas solved the
TODO
related to built-in module accesses. These will now be way faster than before.Nicolas also solved the
TODO
related to the performance of "locals dict" variable accesses.Generator.py no longer contains classes. The Contexts objects are supposed to contain the state, and as such the generator objects never made much sense.
Also with the help of Scons community, I figured out how to avoid having object files inside the
src
directory of Nuitka. That should also help packaging, now all build products go to the .build directory as they should.The vertical white space of the generated C++ got a few cleanups, trailing/leading new line is more consistent now, and there were some assertions added that it doesn't happen.
- The CPython 2.6 tests are now also run by CPython 2.7 and the other way around and need to report the same test failure reports, which found a couple of issues.
- Now the test suite is run with and without
--debug
mode. - Basic tests got extended to cover more topics and catch more issues.
- Program tests got extended to cover code in packages.
- Added more exec scope tests. Currently inlining of exec statements is disabled though, because it requires entirely different rules to be done right, it has been pushed back to the next release.
- The
g++-nuitka
script is no more. With the help of the Scons community, this is now performed inside the scons and only once instead of each time for every C++ file. - When using
--debug
, the generated C++ is compiled with-Wall
and-Werror
so that some form of bugs in the generated C++ code will be detected immediately. This found a few issues already. - There is a new git merge policy in place. Basically it says, that if you submit me a pull request, that I will deal with it before publishing anything new, so you can rely on the current git to provide you a good base to work on. I am doing more frequent pre-releases already and I would like to merge from your git.
- The "README.txt" was updated to reflect current optimization status and plans. There is still a lot to do before constant propagation can work, but this explains things a bit better now. I hope to expand this more and more with time.
- There is now a "misc/clean-up.sh" script that prints the commands to erase all the temporary files sticking around in the source tree. That is for you if you like me, have other directories inside, ignored, that you don't want to delete.
- Then there is now a script that prints all source filenames, so you can more easily open them all in your editor.
- And very important, there is now a "check-release.sh" script that performs all the tests I think should be done before making a release.
- Pylint got more happy with the current Nuitka source. In some places, I added comments where rules should be granted exceptions.
python 2.6:
Pystone(1.1) time for 50000 passes = 0.65 This machine benchmarks at 76923.1 pystones/second
Nuitka 0.3.5 (driven by python 2.6):
Pystone(1.1) time for 50000 passes = 0.31 This machine benchmarks at 161290 pystones/second
This is 109% for 0.3.5, up from 91% before.
Overall this release is primarily an improvement in the domain of compatibility and contains important bug and feature fixes to the users. The optimization framework only makes a first showing of with the framework to organize them. There is still work to do to migrate optimization previously present
It will take more time before we will see effect from these. I believe that even
more cleanups of TreeBuilding
, Nodes
and CodeGeneration
will be
required, before everything is in place for the big jump in performance
numbers. But still, passing 100% feels good. Time to rejoice.
This new release of Nuitka has a focus on re-organizing the Nuitka generated source code and a modest improvement on the performance side.
For a long time now, Nuitka has generated a single C++ file and asked the C++
compiler to translate it to an executable or shared library for CPython to
load. This was done even when embedding many modules into one (the "deep"
compilation mode, option --deep
).
This was simple to do and in theory ought to allow the compiler to do the most optimization. But for large programs, the resulting source code could have exponential compile time behavior in the C++ compiler. At least for the GNU g++ this was the case, others probably as well. This is of course at the end a scalability issue of Nuitka, which now has been addressed.
So the major advancement of this release is to make the --deep
option
useful. But also there have been a performance improvements, which end up giving
us another boost for the "PyStone" benchmark.
- Imports of modules local to packages now work correctly, closing the small compatibility gap that was there.
- Modules with a "-" in their name are allowed in CPython through dynamic imports. This lead to wrong C++ code created. (Thanks to Li Xuan Ji for reporting and submitting a patch to fix it.)
- There were warnings about wrong format used for
Ssize_t
type of CPython. (Again, thanks to Li Xuan Ji for reporting and submitting the patch to fix it.) - When a wrong exception type is raised, the traceback should still be the one of the original one.
- Set and dict contractions (Python 2.7 features) declared local variables for global variables used. This went unnoticed, because list contractions don't generate code for local variables at all, as they cannot have such.
- Using the
type()
built-in to create a new class could attribute it to the wrong module, this is now corrected.
- Uses Scons to execute the actual C++ build, giving some immediate improvements.
- Now caches build results and Scons will only rebuild as needed.
- The direct use of
__import__()
with a constant module name as parameter is also followed in "deep" mode. With time, non-constants may still become predictable, right now it must be a real CPython constant string.
- Added optimization for the built-ins
ord()
andchr()
, these require a module and built-in module lookup, then parameter parsing. Now these are really quick with Nuitka. - Added optimization for the
type()
built-in with one parameter. As above, using from builtin module can be very slow. Now it is instantaneous. - Added optimization for the
type()
built-in with three parameters. It's rarely used, but providing our own variant, allowed to fix the bug mentioned above.
- Using scons is a big cleanup for the way how C++ compiler related options are applied. It also makes it easier to re-build without Nuitka, e.g. if you were using Nuitka in your packages, you can easily build in the same way than Nuitka does.
- Static helpers source code has been moved to ".hpp" and ".cpp" files, instead of being in ".py" files. This makes C++ compiler messages more readable and allows us to use C++ mode in Emacs etc., making it easier to write things.
- Generated code for each module ends up in a separate file per module or package.
- Constants etc. go to their own file (although not named sensible yet, likely going to change too)
- Module variables are now created by the
CPythonModule
node only and are unique, this is to make optimization of these feasible. This is a pre-step to module variable optimization.
- Added "ExtremeClosure" from my Python quiz, it was not covered by existing tests.
- Added test case for program that imports a module with a dash in its name.
- Added test case for main program that starts with a dash.
- Extended the built-in tests to cover
type()
as well.
There is now a new environment variable
NUITKA_SCONS
which should point to the directory with theSingleExe.scons
file for Nuitka. The scons file could be named better, because it is actually one and the same who builds extension modules and executables.There is now a new environment variable
NUITKA_CPP
which should point to the directory with the C++ helper code of Nuitka.The script "create-environment.sh" can now be sourced (if you are in the top level directory of Nuitka) or be used with eval. In either case it also reports what it does.
Update
The script has become obsolete now, as the environment variables are no longer necessary.
To cleanup the many "Program.build" directories, there is now a "clean-up.sh" script for your use. Can be handy, but if you use git, you may prefer its clean command.
Update
The script has become obsolete now, as Nuitka test executions now by default delete the build results.
python 2.6:
Pystone(1.1) time for 50000 passes = 0.65 This machine benchmarks at 76923.1 pystones/second
Nuitka 0.3.4:
Pystone(1.1) time for 50000 passes = 0.34 This machine benchmarks at 147059 pystones/second
This is 91% for 0.3.4, up from 80% before.
This release of Nuitka continues the focus on performance. It also cleans up a few open topics. One is "doctests", these are now extracted from the CPython 2.6 test suite more completely. The other is that the CPython 2.7 test suite is now passed completely. There is some more work ahead though, to extract all of the "doctests" and to do that for both versions of the tests.
This means an even higher level of compatibility has been achieved, then there is performance improvements, and ever cleaner structure.
- Generator functions tracked references to the common and the instance context independently, now the common context is not released before the instance contexts are.
- Generator functions didn't check the arguments to
throw()
the way they are in CPython, now they are. - Generator functions didn't trace exceptions to "stderr" if they occurred while closing unfinished ones in "del".
- Generator functions used the slightly different wordings for some error messages.
- Extended call syntax with
**
allows that to use a mapping, and it is now checked if it really is a mapping and if the contents has string keys. - Similarly, extended call syntax with
*
allows a sequence, it is now checked if it really is a sequence. - Error message for duplicate keyword arguments or too little arguments now describe the duplicate parameter and the callable the same way CPython does.
- Now checks to the keyword argument list first before considering the parameter counts. This is slower in the error case, but more compatible with CPython.
- The "locals()" built-in when used in the class scope (not in a method) now is correctly writable and writes to it change the resulting class.
- Name mangling for private identifiers was not always done entirely correct.
- Exceptions didn't always have the correct stack reported.
- The pickling of some tuples showed that "cPickle" can have non-reproducible results, using "pickle" to stream constants now
- Access to instance attributes has become faster by writing specific code for the case. This is done in JIT way, attempting at run time to optimize attribute access for instances.
- Assignments now often consider what's cheaper for the other side, instead of taking a reference to a global variable, just to have to release it.
- The function call code built argument tuples and dictionaries as constants, now that is true for every tuple usage.
- The static helper classes, and the prelude code needed have been moved to separate C++ files and are now accessed "#include". This makes the code inside C++ files as opposed to a Python string and therefore easier to read and or change.
- The generator functions and generator expressions have the attribute "gi_running" now. These indicate if they are currently running.
- The script to extract the "doctests" from the CPython test suite has been rewritten entirely and works with more doctests now. Running these tests created increased the test coverage a lot.
- The Python 2.7 test suite has been added.
- One can now run multiple "compare_with_cpython" instances in parallel, which enables background test runs.
- There is now a new environment variable "NUITKA_INCLUDE" which needs to point to the directory Nuitka's C++ includes live in. Of course the "create-environment.sh" script generates that for you easily.
python 2.6:
Pystone(1.1) time for 50000 passes = 0.65 This machine benchmarks at 76923.1 pystones/second
Nuitka 0.3.3:
Pystone(1.1) time for 50000 passes = 0.36 This machine benchmarks at 138889 pystones/second
This is 80% for 0.3.3, up from 66% before.
This release of Nuitka continues the focus on performance. But this release also revisits the topic of feature parity. Before, feature parity had been reached "only" with Python 2.6. This is of course a big thing, but you know there is always more, e.g. Python 2.7.
With the addition of set contractions and dict contractions in this very release, Nuitka is approaching Python support for 2.7, and then there are some bug fixes.
- Calling a function with
**
and using a non-dict for it was leading to wrong behavior. Now a mapping is good enough as input for the**
parameter and it's checked. - Deeply nested packages "package.subpackage.module" were not found and gave a warning from Nuitka, with the consequence that they were not embedded in the executable. They now are.
- Some error messages for wrong parameters didn't match literally. For example "function got multiple..." as opposed to "function() got multiple..." and alike.
- Files that ended in line with a "#" but without a new line gave an error from "ast.parse". As a workaround, a new line is added to the end of the file if it's "missing".
- More correct exception locations for complex code lines. I noted that the current line indication should not only be restored when the call at hand failed, but in any case. Otherwise sometimes the exception stack would not be correct. It now is - more often. Right now, this has no systematic test.
- Re-raised exceptions didn't appear on the stack if caught inside the same function, these are now correct.
- For
exec
the globals argument needs to have "__builtins__" added, but the check was performed with the mapping interface. That is not how CPython does it, and so e.g. the mapping could use a default value for "__builtins__" which could lead to incorrect behavior. Clearly a corner case, but one that works fully compatible now.
- The local and shared local variable C++ classes have a flag "free_value" to indicate if an "PY_DECREF" needs to be done when releasing the object. But still the code used "Py_XDECREF" (which allows for "NULL" values to be ignored.) when the releasing of the object was done. Now the inconsistency of using "NULL" as "object" value with "free_value" set to true was removed.
- Tuple constants were copied before using them without a point. They are immutable anyway.
- Improved more of the indentation of the generated C++ which was not very good for contractions so far. Now it is. Also assignments should be better now.
- The generation of code for contractions was made more general and templates split into multiple parts. This enabled reuse of the code for list contractions in dictionary and set contractions.
- The with statement has its own template now and got cleaned up regarding indentation.
- There is now a script to extract the "doctests" from the CPython test suite and it generates Python source code from them. This can be compiled with Nuitka and output compared to CPython. Without this, the doctest parts of the CPython test suite is mostly useless. Solving this improved test coverage, leading to many small fixes. I will dedicate a later posting to the tool, maybe it is useful in other contexts as well.
- Reference count tests have been expanded to cover assignment to multiple assignment targets, and to attributes.
- The deep program test case, now also have a module in a sub-package to cover this case as well.
The gitweb interface might be considered an alternative to downloading the source if you want to provide a pointer, or want to take a quick glance at the source code. You can already download with git, follow the link below to the page explaining it.
The "README.txt" has documented more of the differences and I consequently updated the Differences page. There is now a distinction between generally missing functionality and things that don't work in
--deep
mode, where Nuitka is supposed to create one executable.I will make it a priority to remove the (minor) issues of
--deep
mode in the next release, as this is only relatively little work, and not a good difference to have. We want these to be empty, right? But for the time being, I document the known differences there.
python 2.6:
Pystone(1.1) time for 50000 passes = 0.65 This machine benchmarks at 76923.1 pystones/second
Nuitka 0.3.2:
Pystone(1.1) time for 50000 passes = 0.39 This machine benchmarks at 128205 pystones/second
This is 66% for 0.3.2, slightly up from the 58% of 0.3.1 before. The optimization done were somewhat fruitful, but as you can see, they were also more cleanups, not the big things.
This release of Nuitka continues the focus on performance and contains only cleanups and optimization. Most go into the direction of more readable code, some aim at making the basic things faster, with good results as to performance as you can see below.
Constants in conditions of conditional expressions (
a if cond else d
),if
/elif
orwhile
are now evaluated totrue
orfalse
directly. Before there would be temporary python object created from it which was then checked if it had a truth value.All of that is obviously overhead only. And it hurts the typically
while 1:
infinite loop case badly.Do not generate code to catch
BreakException
orContinueException
unless abreak
orcontinue
statement being in atry: finally:
block inside that loop actually require this.Even while uncaught exceptions are cheap, it is still an improvement worthwhile and it clearly improves the readability for the normal case.
The compiler more aggressively prepares tuples, lists and dicts from the source code as constants if their contents is "immutable" instead of building at run time. An example of a "mutable" tuple would be
({},)
which is not safe to share, and therefore will still be built at run time.For dictionaries and lists, copies will be made, under the assumption that copying a dictionary will always be faster, than making it from scratch.
The parameter parsing code was dynamically building the tuple of argument names to check if an argument name was allowed by checking the equivalent of
name in argument_names
. This was of course wasteful and now a pre-built constant is used for this, so it should be much faster to call functions with keyword arguments.There are new templates files and also actual templates now for the
while
andfor
loop code generation. And I started work on having a template for assignments.
Do not generate code for the else of
while
andfor
loops if there is no such branch. This uncluttered the generated code somewhat.The indentation of the generated C++ was not very good and whitespace was often trailing, or e.g. a real tab was used instead of "t". Some things didn't play well together here.
Now much of the generated C++ code is much more readable and white space cleaner. For optimization to be done, the humans need to be able to read the generated code too. Mind you, the aim is not to produce usable C++, but on the other hand, it must be possible to understand it.
To the same end of readability, the empty
else {}
branches are avoided forif
,while
andfor
loops. While the C++ compiler can be expected to remove these, they seriously cluttered up things.The constant management code in
Context
was largely simplified. Now the code is using theConstant
class to find its way around the problem that dicts, sets, etc. are not hashable, or thatcomplex
is not being ordered; this was necessary to allow deeply nested constants, but it is also a simpler code now.The C++ code generated for functions now has two entry points, one for Python calls (arguments as a list and dictionary for parsing) and one where this has happened successfully. In the future this should allow for faster function calls avoiding the building of argument tuples and dictionaries all-together.
For every function there was a "traceback adder" which was only used in the C++ exception handling before exit to CPython to add to the traceback object. This was now in-lined, as it won't be shared ever.
python 2.6:
Pystone(1.1) time for 50000 passes = 0.65 This machine benchmarks at 76923.1 pystones/second
Nuitka 0.3.1:
Pystone(1.1) time for 50000 passes = 0.41 This machine benchmarks at 121951 pystones/second
This is 58% for 0.3.1, up from the 25% before. So it's getting somewhere. As always you will find its latest version here.
This release 0.3.0 is the first release to focus on performance. In the 0.2.x series Nuitka achieved feature parity with CPython 2.6 and that was very important, but now it is time to make it really useful.
Optimization has been one of the main points, although I was also a bit forward looking to Python 2.7 language constructs. This release is the first where I really started to measure things and removed the most important bottlenecks.
- Added option to control
--debug
. With this option the C++ debug information is present in the file, otherwise it is not. This will give much smaller ".so" and ".exe" files than before. - Added option
--no-optimization
to disable all optimization. It enables C++ asserts and compiles with less aggressive C++ compiler optimization, so it can be used for debugging purposes. - Support for Python 2.7 set literals has been added.
Fast global variables: Reads of global variables were fast already. This was due to a trick that is now also used to check them and to do a much quicker update if they are already set.
Fast
break
/continue
statements: To make sure these statements execute the finally handlers if inside a try, these used C++ exceptions that were caught bytry
/finally
inwhile
orfor
loops.This was very slow and had very bad performance. Now it is checked if this is at all necessary and then it's only done for the rare case where a
break
/continue
really is inside the tried block. Otherwise it is now translated to a C++break
/continue
which the C++ compiler handles more efficiently.Added
unlikely()
compiler hints to all errors handling cases to allow the C++ compiler to generate more efficient branch code.The for loop code was using an exception handler to make sure the iterated value was released, using
PyObjectTemporary
for that instead now, which should lead to better generated code.Using constant dictionaries and copy from them instead of building them at run time even when contents was constant.
- Merged some bits from the CPython 2.7 test suite that do not harm 2.6, but
generally it's a lot due to some
unittest
module interface changes. - Added CPython 2.7 tests
test_dictcomps.py
andtest_dictviews.py
which both pass when using Python 2.7. - Added another benchmark extract from "PyStone" which uses a while loop with break.
python 2.6:
Pystone(1.1) time for 50000 passes = 0.65 This machine benchmarks at 76923.1 pystones/second
Nuitka 0.3.0:
Pystone(1.1) time for 50000 passes = 0.52 This machine benchmarks at 96153.8 pystones/second
That's a 25% speedup now and a good start clearly. It's not yet in the range of
where i want it to be, but there is always room for more. And the
break
/continue
exception was an important performance regression fix.
This release 0.2.4 is likely the last 0.2.x release, as it's the one that achieved feature parity with CPython 2.6, which was the whole point of the release series, so time to celebrate. I have stayed away (mostly) from any optimization, so as to not be premature.
From now on speed optimization is going to be the focus though. Because right now, frankly, there is not much of a point to use Nuitka yet, with only a minor run time speed gain in trade for a long compile time. But hopefully we can change that quickly now.
- The use of exec in a local function now adds local variables to scope it is in.
- The same applies to
from module_name import *
which is now compiled correctly and adds variables to the local variables.
- Raises
UnboundLocalError
when deleting a local variable withdel
twice. - Raises
NameError
when deleting a global variable withdel
twice. - Read of to uninitialized closure variables gave
NameError
, butUnboundLocalError
is correct and raised now.
- There is now a dedicated pass over the node tree right before code generation starts, so that some analysis can be done as late as that. Currently this is used for determining which functions should have a dictionary of locals.
- Checking the exported symbols list, fixed all the cases where a
static
was missing. This reduces the "module.so" sizes. - With gcc the "visibility=hidden" is used to avoid exporting the helper classes. Also reduces the "module.so" sizes, because classes cannot be made static otherwise.
- Added "DoubleDeletions" to cover behaviour of
del
. It seems that this is not part of the CPython test suite. - The "OverflowFunctions" (those with dynamic local variables) now has an interesting test, exec on a local scope, effectively adding a local variable while a closure variable is still accessible, and a module variable too. This is also not in the CPython test suite.
- Restored the parts of the CPython test suite that did local star imports or exec to provide new variables. Previously these have been removed.
- Also "test_with.py" which covers PEP 343 has been reactivated, the with statement works as expected.
This new release is marking a closing in on feature parity to CPython 2.6 which is an important mile stone. Once this is reached, a "Nuitka 0.3.x" series will strive for performance.
- Generator functions no longer leak references when started, but not finished.
- Yield can in fact be used as an expression and returns values that the
generator user
send()
to it.
Generator functions already worked quite fine, but now they have the
throw()
,send()
andclose()
methods.Yield is now an expression as is ought to be, it returns values put in by
send()
on the generator user.Support for extended slices:
x = d[:42, ..., :24:, 24, 100] d[:42, ..., :24:, 24, 100] = "Strange" del d[:42, ..., :24:, 24, 100]
- The "test_contextlib" is now working perfectly due to the generator functions
having a correct
throw()
. Added that test back, so context managers are now fully covered. - Added a basic test for "overflow functions" has been added, these are the ones
which have an unknown number of locals due to the use of language constructs
exec
orfrom bla import *
on the function level. This one currently only highlights the failure to support it. - Reverted removals of extended slice syntax from some parts of the CPython test suite.
- The compiled generator types are using the new C++0x type safe enums feature.
- Resolved a circular dependency between
TreeBuilding
andTreeTransforming
modules.
This is some significant progress, a lot of important things were addressed.
- Scope analysis is now done during the tree building instead of sometimes during code generation, this fixed a few issues that didn't show up in tests previously.
- Reference leaks of generator expressions that were not fishing, but then deleted are not more.
- Inlining of exec is more correct now.
- More accurate exception lines when iterator creation executes compiled code, e.g. in a for loop
- The list of base classes of a class was evaluated in the context of the class, now it is done in the context of the containing scope.
- The first iterated of a generator expression was evaluated in its own context, now it is done in the context of the containing scope.
- With the enhanced scope analysis,
UnboundLocalError
is now correctly supported. - Generator expressions (but not yet functions) have a
throw()
,send()
andclose()
method. - Exec can now write to local function namespace even if
None
is provided at run time. - Relative imports inside packages are now correctly resolved at compile time
when using
--deep
.
- The compiled function type got further enhanced and cleaned up.
- The compiled generator expression function type lead to a massive cleanup of the code for generator expressions.
- Cleaned up namespaces, was still using old names, or "Py*" which is reserved to core CPython.
- Overhaul of the code responsible for
eval
andexec
, it has been split, and it pushed the detection defaults to the C++ compiler which means, we can do it at run time or compile time, depending on circumstances. - Made
PyTemporaryObject
safer to use, disabling copy constructor it should be also a relief to the C++ compiler if it doesn't have to eliminate all its uses. - The way delayed work is handled in
TreeBuilding
step has been changed to use closured functions, should be more readable. - Some more code templates have been created, making the code generation more readable in some parts. More to come.
- As I start to consider announcing Nuitka, I moved the version logic so that
the version can now be queried with
--version
.
- Name lookups for
None
,True
andFalse
and now always detected as constants, eliminating many useless module variable lookups.
- More complete test of generator expressions.
- Added test program for packages with relative imports inside the package.
- The built-in
dir()
in a function was not having fully deterministic output list, now it does.
Overall, the amount of differences between CPython and Nuitka is heading towards zero. Also most of the improvements done in this release were very straightforward cleanups and not much work was required, mostly things are about cleanups and then it becomes easily right. The new type for the compiled generator expressions was simple to create, esp. as I could check what CPython does in its source code.
For optimization purposes, I decided that generator expressions and generator functions will be separate compiled types, as most of their behavior will not be shared. I believe optimizing generator expressions to run well is an important enough goal to warrant that they have their own implementation. Now that this is done, I will repeat it with generator functions.
Generator functions already work quite fine, but like generator expressions did
before this release, they can leak references if not finished , and they don't
have the throw()
method, which seems very important to the correct operation
of contextlib
. So I will introduce a decicated type for these too, possibly
in the next release.
The march goes on, this is another minor release with a bunch of substantial improvements:
- Packages now also can be embedded with the
--deep
option too, before they could not be imported from the executable. - In-lined exec with their own future statements leaked these to the surrounding code.
- The future print function import is now supported too.
- Independence of the compiled function type. When I started it was merely
PyCFunction
and then a copy of it patched at run time, using increasingly less code from CPython. Now it's nothing at all anymore. - This lead to major cleanup of run time compiled function creation code, no
more
methoddefs
,PyCObject
holding context, etc. - PyLint was used to find the more important style issues and potential bugs, also helping to identify some dead code.
The major difference now is the lack of a throw method for generator functions. I will try to address that in a 0.2.2 release if possible. The plan is that the 0.2.x series will complete these tasks, and 0.3 could aim at some basic optimization finally.
Good day, this is a major step ahead, improvements everywhere.
- Migrated the Python parser from the deprecated and problematic
compiler
module to theast
module which fixes thed[a,] = b
parser problem. A pity it was not available at the time I started, but the migration was relatively painless now. - I found and fixed wrong encoding of binary data into C++ literals. Now Nuitka uses C++0x raw strings, and these problems are gone.
- The decoding of constants was done with the
marshal
module, but that appears to not deeply care enough about unicode encoding it seems. UsingcPickle
now, which seems less efficient, but is more correct. - Another difference is gone: The
continue
andbreak
inside loops do no longer prevent the execution of finally blocks inside the loop.
I now maintain the "README.txt" in org-mode, and intend to use it as the issue tracker, but I am still a beginner at that.
Update
Turned out I never master it, and used ReStructured Text instead.
There is a public git repository for you to track Nuitka releases. Make your changes and then
git pull --rebase
. If you encounter conflicts in things you consider useful, please submit the patches and a pull offer. When you make your clones of Nuitka public, usenuitka-unofficial
or not the nameNuitka
at all.There is a now a mailing list available too.
- Did you know you could write
lambda : (yield something)
and it gives you a lambda that creates a generator that produces that one value? Well, now Nuitka has support for lambda generator functions. - The
from __future__ import division
statement works as expected now, leading to some newly passing CPython tests. - Same for
from __future__ import unicode_literals
statement, these work as expected now, removing many differences in the CPython tests that use this already.
- The
Python
binary provided andNuitka.py
are now capable of accepting parameters for the program executed, in order to make it even more of a drop-in replacement topython
. - Inlining of
exec
statements with constant expressions. These are now compiled at compile time, not at run time anymore. I observed that an increasing number of CPython tests use exec to do things in isolation or to avoid warnings, and many more these tests will now be more effective. I intend to do the same with eval expressions too, probably in a minor release.
So give it a whirl. I consider it to be substantially better than before, and the list of differences to CPython is getting small enough, plus there is already a fair bit of polish to it. Just watch out that it needs gcc-4.5 or higher now.
I just have just updated Nuitka to version 0.1.1 which is a bug fix release to 0.1, which corrects many of the small things:
- Updated the CPython test suite to 2.6.6rc and minimized much of existing differences in the course.
- Compiles standalone executable that includes modules (with --deep option), but packages are not yet included successfully.
- Reference leaks with exceptions are no more.
- sys.exc_info() works now mostly as expected (it's not a stack of exceptions).
- More readable generated code, better organisation of C++ template code.
- Restored debug option
--g++-only
.
The biggest thing probably is the progress with exception tracebacks objects in
exception handlers, which were not there before (always None
). Having these
in place will make it much more compatible. Also with manually raised exceptions
and assertions, tracebacks will now be more correct to the line.
On a bad news, I discovered that the compiler
module that I use to create
the AST from Python source code, is not only deprecated, but also broken. I
created the CPython bug about it,
basically it cannot distinguish some code of the form d[1,] = None
from
d[1] = None
. This will require a migration of the ast
module, which
should not be too challenging, but will take some time.
I am aiming at it for a 0.2 release. Generating wrong code (Nuitka sees d[1] =
None
in both cases) is a show blocker and needs a solution.
So, yeah. It's better, it's there, but still experimental. You will find its latest version here. Please try it out and let me know what you think in the comments section.
Obviously this is very exciting step for me. I am releasing Nuitka today. Finally. For a long time I knew I would, but actually doing it, is a different beast. Reaching my goals for release turned out to be less far away than I hope, so instead of end of August, I can already release it now.
Currently it's not more than 4% faster than CPython. No surprise there, if all you did, is removing the bytecode interpretation so far. It's not impressive at all. It's not even a reason to use it. But it's also only a start. Clearly, once I get into optimizing the code generation of Nuitka, it will only get better, and then probably in sometimes dramatic steps. But I see this as a long term goal.
I want to have infrastructure in the code place, before doing lots of possible optimization that just make Nuitka unmaintainable. And I will want to have a look at what others did so far in the domain of type inference and how to apply that for my project.
I look forward to the reactions about getting this far. The supported language volume is amazing, and I have a set of nice tricks used. For example the way generator functions are done is a clever hack.
Where to go from here? Well, I guess, I am going to judge it by the feedback I receive. I personally see "constant propagation" as a laudable first low hanging fruit, that could be solved.
Consider this readable code on the module level:
meters_per_nautical_mile = 1852
def convertMetersToNauticalMiles(meters):
return meters / meters_per_nautical_mile
def convertNauticalMilesToMeters(miles):
return miles * meters_per_nautical_mile
Now imagine you are using this very frequently in code. Quickly you determine that the following will be much faster:
def convertMetersToNauticalMiles(meters):
return meters / 1852
def convertNauticalMilesToMeters(miles):
return miles * 1852
Still good? Well, probably next step you are going to in-line the function calls entirely. For optimization, you are making your code less readable. I do not all appreciate that. My first goal is there to make the more readable code perform as well or better as the less readable variant.