Common infrastructure for initializing random number generators.
Project description
Python Seed Manager
Python programs, particularly data science applications, often need to interact with multiple different random number generators.
This package provides a unified interface to seeding them, along with APIs for deriving additional RNG seeds in a predictable way (using NumPy 1.17's new random infrastructure) and constructing random generators.
Quick Start
To get started, just use the seedbank.initialize() function to seed all available random number generators:
import seedbank
seedbank.initialize(65000)
SeedBank will seed all of the known generators that will be available, including:
- Python standard random
- NumPy legacy random
numpy.random
- PyTorch (with torch.manual_seed())
- Numba’s NumPy random
- TensorFlow (with tf.random.set_seed())
In addition, it will initialize a root seed for constructing new-style NumPy Generator
instances.
If SeedBank doesn’t support your RNG yet, please submit a pull request!
Developing SeedBank
SeedBank uses Flit for managing dependencies. To set up in a fresh virtual environment:
python -m pip install flit
flit install --pth-file
If you want to use a Conda environment for development, use:
python build-tools/flit-conda --create-env --python-version 3.8
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