README.md

iterpipe

Build functional, parallelized processing pipelines for Python iterables

iterpipe lets you run sequences (Iterables) of Python objects through a series of processing functions (the Pipeline). Pipelines can be seamlessly distributed across cores for fully parallelized execution.

Inspired by Clojure's threading macros, the parallel command and Unix pipes, iterpipe aims to make processing iterables in Python faster, easier to test and more functional.

from iterpipe import Pipeline

# All functions in the pipeline
# - take a single item as an argument
# - return a single item

def churn(x):
    n = x**2
    while n > 0:
        n -= 1
    return x

from functools import partial
import operator
multiply = partial(operator.mul, 10)

def even_filter(x):
    if x % 2 == 0:
        return x

if __name__ == "__main__":
    pipe = Pipeline(
        even_filter,       # remove odd values
        multiply,          # multiply
        churn,             # stress the CPU
        filter_value=None, # if any function returns None, filter it
        procs=4            # Use 4 CPU cores
    )

    data = list(pipe(range(100)))  # [0, 20, ..., 980]

Status

Alpha. Please try it out and give me some feedback.

Installation

pip install -e "git+https://github.com/perrygeo/iterpipe.git#egg=iterpipe"