Python bindings for the official Rust implementation of
BLAKE3, based on
PyO3. These bindings expose all the features of
BLAKE3, including extendable output, keying, and multithreading. The basic API
matches that of Python's standard
hashlib
module.
from blake3 import blake3
# Hash some input all at once. The input can be bytes, a bytearray, or a memoryview.
hash1 = blake3(b"foobarbaz").digest()
# Hash the same input incrementally.
hasher = blake3()
hasher.update(b"foo")
hasher.update(b"bar")
hasher.update(b"baz")
hash2 = hasher.digest()
assert hash1 == hash2
# Hexadecimal output.
print("The hash of 'hello world' is", blake3(b"hello world").hexdigest())
# Use the keyed hashing mode, which takes a 32-byte key.
import secrets
random_key = secrets.token_bytes(32)
message = b"a message to authenticate"
mac = blake3(message, key=random_key).digest()
# Use the key derivation mode, which takes a context string. Context strings
# should be hardcoded, globally unique, and application-specific.
context = "blake3-py 2020-03-04 11:13:10 example context"
key_material = b"usually at least 32 random bytes, not a password"
derived_key = blake3(key_material, derive_key_context=context).digest()
# Extendable output. The default digest size is 32 bytes.
extended = blake3(b"foo").digest(length=100)
assert extended[:32] == blake3(b"foo").digest()
assert extended[75:100] == blake3(b"foo").digest(length=25, seek=75)
# Hash a large input using multiple threads. Note that this can be slower for
# inputs shorter than ~1 MB, and it's a good idea to benchmark it for your use
# case on your platform.
large_input = bytearray(1_000_000)
hash_single = blake3(large_input).digest()
hash_two = blake3(large_input, max_threads=2).digest()
hash_many = blake3(large_input, max_threads=blake3.AUTO).digest()
assert hash_single == hash_two == hash_many
# Copy a hasher that has already accepted some input.
hasher1 = blake3(b"foo")
hasher2 = hasher1.copy()
hasher1.update(b"bar")
hasher2.update(b"baz")
assert hasher1.digest() == blake3(b"foobar").digest()
assert hasher2.digest() == blake3(b"foobaz").digest()
pip install blake3
As usual with Pip, you might need to use sudo
or the --user
flag
with the command above, depending on how you installed Python on your
system.
There are binary wheels available on PyPI for most environments. But if you're building the source distribution, or if a binary wheel isn't available for your environment, you'll need to install the Rust toolchain.
Like the hashlib
functions in the Python standard library, we release
the GIL while hashing, to avoid blocking other threads for a potentially
long time. However, this allows race conditions: it's possible for other
threads to access a hasher or an input buffer while hashing is going on.
This is worse than an ordinary Python race condition. It's undefined
behavior in the C/C++/Rust sense. But this seems to be the standard way
to do hashing in Python. In any case, it should be rare for real world
programs to share a hasher between threads. For more details about this
issue, see the comments on usafe code in lib.rs
.