Cython code reorg and co-opted pyzmq build framework so do not have t…

…o check in cythonized .c code into git

.gitignore

@@ -4,6 +4,9 @@ dist
 MANIFEST
 *.so
 *.pyd
+pandas/src/tseries.c
+pandas/src/sparse.c
 doc/source/generated
+*flymake*
 scikits
 .coverage

MANIFEST.in

@@ -5,7 +5,21 @@ include README.rst
 include TODO.rst
 include setup.py
 include setupegg.py
+
+graft docs
+prune docs/build
+prune docs/gh-pages
+
+graft examples
+graft pandas
+
+global-exclude *.so
+global-exclude *.pyd
+global-exclude *.pyc
+global-exclude .git*
+global-exclude .DS_Store
+
 # include examples/data/*
-recursive-include examples *.py
+# recursive-include examples *.py
 # recursive-include doc/source *
 # recursive-include doc/sphinxext *

RELEASE.rst

@@ -150,6 +150,9 @@ Thanks
 - Chris Uga
 - Chris Withers
 - Jeff Reback
+- William Ferreira
+- Daniel Fortunov
+- Martin Felder
 
 ************************
 pandas 0.3 Release Notes

pandas/core/common.py

@@ -7,7 +7,7 @@
 from numpy.lib.format import read_array, write_array
 import numpy as np
 
-import pandas.lib.tseries as tseries
+import pandas._tseries as _tseries
 
 # XXX: HACK for NumPy 1.5.1 to suppress warnings
 try:
@@ -32,11 +32,11 @@ def isnull(input):
         if input.dtype.kind in ('O', 'S'):
             # Working around NumPy ticket 1542
             result = input.copy().astype(bool)
-            result[:] = tseries.isnullobj(input)
+            result[:] = _tseries.isnullobj(input)
         else:
             result = -np.isfinite(input)
     else:
-        result = tseries.checknull(input)
+        result = _tseries.checknull(input)
 
     return result
 
@@ -56,7 +56,7 @@ def notnull(input):
     if isinstance(input, np.ndarray):
         return -isnull(input)
     else:
-        return not tseries.checknull(input)
+        return not _tseries.checknull(input)
 
 def _pickle_array(arr):
     arr = arr.view(np.ndarray)

pandas/core/frame.py

@@ -30,7 +30,7 @@
 from pandas.core.series import Series
 import pandas.core.common as common
 import pandas.core.datetools as datetools
-import pandas.lib.tseries as tseries
+import pandas._tseries as _tseries
 
 #-------------------------------------------------------------------------------
 # Factory helper methods
@@ -2182,7 +2182,7 @@ def median(self, axis=0):
         def f(arr):
             if arr.dtype != np.float_:
                 arr = arr.astype(float)
-            return tseries.median(arr[notnull(arr)])
+            return _tseries.median(arr[notnull(arr)])
 
         if axis == 0:
             med = [f(self[col].values) for col in self.columns]

pandas/core/functions.py

@@ -116,5 +116,5 @@ def ts_upsample(dates, buckets, values, aggfunc, inclusive=True):
 
     result = reduce_mean(values, index, buckets)
 
-    import pandas.lib.tseries as tseries
+    import pandas._tseries as tseries
     tseries.ts_upsample_mean(index, buckets, values)

pandas/core/groupby.py

@@ -6,7 +6,7 @@
 from pandas.core.series import Series
 from pandas.core.panel import WidePanel
 import pandas.core.common as common
-import pandas.lib.tseries as tseries
+import pandas._tseries as _tseries
 
 class GroupDict(dict):
     def __repr__(self):
@@ -54,15 +54,14 @@ def __init__(self, obj, grouper):
             grouper = grouper.get
         self.grouper = grouper
         axis = self._group_axis
-        self.groups = tseries.groupby(axis, self.grouper,
+        self.groups = _tseries.groupby(axis, self.grouper,
                                       output=GroupDict())
 
     @property
     def group_indices(self):
         if self._group_indices is None:
             axis = self._group_axis
-            self._group_indices = tseries.groupby_indices(axis,
-                                                          self.grouper)
+            self._group_indices = _tseries.groupby_indices(axis, self.grouper)
 
         return self._group_indices
 

pandas/core/index.py

@@ -3,7 +3,7 @@
 import numpy as np
 
 from pandas.core.common import _ensure_index
-import pandas.lib.tseries as _tseries
+import pandas._tseries as _tseries
 
 __all__ = ['Index']
 
@@ -260,8 +260,6 @@ def get_indexer(self, target, method=None):
         -------
         (indexer, mask)
         """
-        import pandas.lib.tseries as tseries
-
         if method:
             method = method.upper()
 
@@ -273,8 +271,8 @@ def get_indexer(self, target, method=None):
         target = _ensure_index(target)
 
         method = aliases.get(method, method)
-        indexer, mask = tseries.getFillVec(self, target, self.indexMap,
-                                           target.indexMap, method)
+        indexer, mask = _tseries.getFillVec(self, target, self.indexMap,
+                                            target.indexMap, method)
         return indexer, mask
 
     def slice_locs(self, start=None, end=None):

pandas/core/panel.py

@@ -14,7 +14,7 @@
 from pandas.core.frame import DataFrame
 from pandas.core.generic import PandasGeneric, Picklable
 import pandas.core.common as common
-import pandas.lib.tseries as tseries
+import pandas._tseries as _tseries
 
 class PanelError(Exception):
     pass
@@ -900,7 +900,7 @@ def median(self, axis='major'):
         y : DataFrame
         """
         def f(arr):
-            return tseries.median(arr[common.notnull(arr)])
+            return _tseries.median(arr[common.notnull(arr)])
 
         return self.apply(f, axis=axis)
 
@@ -1086,8 +1086,8 @@ def fromRecords(cls, data, major_field, minor_field,
         major_axis = Index(sorted(set(major_vec)))
         minor_axis = Index(sorted(set(minor_vec)))
 
-        major_labels, _ = tseries.getMergeVec(major_vec, major_axis.indexMap)
-        minor_labels, _ = tseries.getMergeVec(minor_vec, minor_axis.indexMap)
+        major_labels, _ = _tseries.getMergeVec(major_vec, major_axis.indexMap)
+        minor_labels, _ = _tseries.getMergeVec(minor_vec, minor_axis.indexMap)
 
         for col in exclude:
             del data[col]
@@ -2012,8 +2012,8 @@ def _make_long_index(major_values, minor_values):
     major_axis = Index(sorted(set(major_values)))
     minor_axis = Index(sorted(set(minor_values)))
 
-    major_labels, _ = tseries.getMergeVec(major_values, major_axis.indexMap)
-    minor_labels, _ = tseries.getMergeVec(minor_values, minor_axis.indexMap)
+    major_labels, _ = _tseries.getMergeVec(major_values, major_axis.indexMap)
+    minor_labels, _ = _tseries.getMergeVec(minor_values, minor_axis.indexMap)
 
     long_index = LongPanelIndex(major_axis, minor_axis,
                                major_labels, minor_labels)

pandas/core/series.py

@@ -18,7 +18,7 @@
 from pandas.core.generic import PandasGeneric
 from pandas.core.index import Index
 import pandas.core.datetools as datetools
-import pandas.lib.tseries as tseries
+import pandas._tseries as _tseries
 
 __all__ = ['Series', 'TimeSeries']
 
@@ -58,10 +58,10 @@ def wrapper(self, other):
 
                 # buffered Cython function expects double type
 
-                arr = tseries.combineFunc(name, newIndex,
-                                          this, other,
-                                          self.index.indexMap,
-                                          other.index.indexMap)
+                arr = _tseries.combineFunc(name, newIndex,
+                                           this, other,
+                                           self.index.indexMap,
+                                           other.index.indexMap)
             except Exception:
                 arr = Series._combineFunc(self, other,
                                           getattr(type(self[0]), name))
@@ -613,7 +613,7 @@ def median(self):
             arr = arr.astype(float)
 
         arr = arr[notnull(arr)]
-        return tseries.median(arr)
+        return _tseries.median(arr)
 
     def corr(self, other):
         """
@@ -923,7 +923,7 @@ def map(self, arg):
             if isinstance(arg, dict):
                 arg = Series(arg)
 
-            indexer, mask = tseries.getMergeVec(self, arg.index.indexMap)
+            indexer, mask = _tseries.getMergeVec(self, arg.index.indexMap)
             notmask = -mask
 
             new_values = arg.view(np.ndarray).take(indexer)

pandas/core/sparse.py

@@ -20,8 +20,8 @@
 import pandas.core.common as common
 import pandas.core.datetools as datetools
 
-from pandas.lib.sparse import BlockIndex, IntIndex
-import pandas.lib.sparse as splib
+from pandas._sparse import BlockIndex, IntIndex
+import pandas._sparse as splib
 
 def make_sparse(arr, kind='block', fill_value=nan):
     """

pandas/finance/portstats.py

@@ -2,7 +2,7 @@
 Compute common portfolio statistics
 """
 
-import pandas.lib.tseries as _tseries
+import pandas._tseries as _tseries
 import pandas.stats.moments as moments
 
 def leverage(weights):

pandas/io/pytables.py

@@ -13,7 +13,7 @@
                     LongPanel)
 from pandas.core.pytools import adjoin
 import pandas.core.internals as internals
-import pandas.lib.tseries as tseries
+import pandas._tseries as _tseries
 
 # reading and writing the full object in one go
 _TYPE_MAP = {
@@ -593,7 +593,7 @@ def _read_index_legacy(group, key):
 
 def _unconvert_index_legacy(data, kind, legacy=False):
     if kind == 'datetime':
-        index = tseries.array_to_datetime(data)
+        index = _tseries.array_to_datetime(data)
     elif kind in ('string', 'integer'):
         index = np.array(data, dtype=object)
     else: # pragma: no cover