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Citi/parfun

Citi

Citi/parfun

Lightweight parallelisation library for Python.

PyPI - Version


Parfun is a lightweight library providing helpers to make it easy to write and run a Python function in parallel and distributed systems.

The main feature of the library is its @parfun decorator that transparently executes standard Python functions following the map-reduce pattern:

from parfun import parfun
from parfun.combine.collection import list_concat
from parfun.partition.api import per_argument
from parfun.partition.collection import list_by_chunk

@parfun(
    split=per_argument(
        values=list_by_chunk
    ),
    combine_with=list_concat,
)
def list_pow(values: List[float], factor: float) -> List[float]:
    return [v**factor for v in values]

Features

  • Provides significant speedups to existing Python functions
  • Does not require any deep knowledge of parallel or distributed computing systems
  • Automatically estimates the optimal sub-task splitting (the partition size)
  • Automatically handles data transmission, caching and synchronization.
  • Supports various distributed computing backends, including Python's multiprocessing, Scaler or Dask.

Benchmarks

Parfun efficiently parallelizes short-duration functions.

When running a short 0.28-second ML function on an AMD Epyc 7313 16-Cores Processor, Parfun provides an impressive 7.4x speedup. Source code for this experiment here.

Benchmark Results

Quick Start

The official documentation is availaible at citi.github.io/parfun/.

Alternatively, you can build the HTML documentation from the source code:

cd docs
pip install -r requirements.txt
make html

The documentation's main page can then ben found at docs/build/html/index.html.

Take a look at our documentation's quickstart tutorial to get more examples and a deeper overview of the library.

Contributing

Your contributions are at the core of making this a true open source project. Any contributions you make are greatly appreciated.

We welcome you to:

Please review our community contribution guidelines and functional contribution guidelines to get started đź‘Ť.

Code of Conduct

We are committed to making open source an enjoyable and respectful experience for our community. See CODE_OF_CONDUCT for more information.

License

This project is distributed under the Apache-2.0 License. See LICENSE for more information.

Contact

If you have a query or require support with this project, raise an issue. Otherwise, reach out to [email protected].