Scrypt for Python
Project description
There are a lot of different scrypt modules for Python, but none of them have everything that I’d like, so here’s One More1.
Features
Uses system libscrypt2 as the first choice.
If that isn’t available, tries the scrypt Python module3 or libsodium4.
Offers a pure Python scrypt implementation for when there’s no C scrypt.
Not unusably slow, even in pure Python… at least with pypy5.
With PyPy as the interpreter the Python implementation is around one fifth the speed of C scrypt. With CPython it is one fiftieth if libsodium is available to accelerate Salsa20/8, one two-hundredth if not.
Requirements
Python 2.7 or 3.4 or so. Pypy 2.2 also works. Older versions may or may not.
If you want speed, you should use one of:
libscrypt 1.8+ (older may work)
py-scrypt 0.6+ (pip install scrypt)
libsodium 0.5+ and the \(7\) prefix (see below)
pypy
Usage
You can install the most recent release from PyPi using:
pip install pylibscrypt
You most likely want to create MCF hashes and store them somewhere, then check user-entered passwords against those hashes. For that you only need to use two functions from the API:
from pylibscrypt import * # Generate an MCF hash with random salt mcf = scrypt_mcf('Hello World') # Test it print(scrypt_mcf_check(mcf, 'Hello World')) # prints True print(scrypt_mcf_check(mcf, 'HelloPyWorld')) # prints False
For full API, you can try help(pylibscrypt) from python after importing.
It is highly recommended that you use a random salt, i.e. don’t pass one.
Additionally, using the \(7\) MCF format by calling with prefix=\(7\) is recommended both because it will be made the default in a future release and because it allows using libsodium as a backend.
Versioning
The package has a version number that can be read from python like so:
print(pylibscrypt.__version__)
The version number is of the form X.Y.Z, following Semantic Versioning6. Releases are tagged vX.Y.Z and release branches bX.Y.x when they differ from master.
Development
Development happens on GitHub2. If you find a bug, please open an issue there.
tests.py tests both implementations with some quick tests. Running either implementation directly will also compare to scrypt test vectors from the paper but this is slow for the Python version unless you have pypy.
fuzz.py runs some basic fuzz tests with semi-randomly chosen inputs.
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