GitHub - oconnor663/blake3-py: Python bindings for the BLAKE3 cryptographic hash function (original) (raw)

Python bindings for the official Rust implementation of BLAKE3, based onPyO3. These bindings expose all the features of BLAKE3, including extendable output, keying, and multithreading. The basic API matches that of Python's standardhashlib module.

Examples

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

Hash the same input fluently.

assert hash1 == blake3(b"foo").update(b"bar").update(b"baz").digest()

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

Hash a file with multiple threads using memory mapping. This is what b3sum

does by default.

file_hasher = blake3(max_threads=blake3.AUTO) file_hasher.update_mmap("/big/file.txt") file_hash = file_hasher.digest()

Copy a hasher that's 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()

Installation

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.

C Bindings

Experimental bindings for the official BLAKE3 C implementation are available in the c_impl directory. These will probably not be published on PyPI, and most applications should prefer the Rust-based bindings. But if you can't depend on the Rust toolchain, and you're on some platform that this project doesn't provide binary wheels for, the C-based bindings might be an alternative.