parallel-conveyor 0.1.3

Simple, intuitive pipelining in Python

Conveyor - Intuitive Python pipelines

Conveyor is a multiprocessing framework for creating intuitive data pipelines. With Conveyor, you can easily create stream-based pipelines to efficiently perform a series of operations on data, a task especially useful in the fields of machine learning and scientific computing. Creating a pipelined job is as easy as writing a function.

Why use Conveyor?

The answer is simple: throughput. It's like putting a second load of laundry in the washer while a previous load is in the dryer. By breaking down a problem into smaller serial tasks, we perform the smaller tasks in parallel and increase the efficiency of whatever problem we're trying to solve.

Installation

Install Conveyor with pip install parallel-conveyor.

A quick and trivial example

Let's say we wanted to build a short pipeline that computed the fourth root of a number (done in two steps) and the cube of a number (in one step). In this case, we would describe this pipeline visually as such:

To express it with Conveyor, we simply build the pipeline as follows

from conveyor.pipeline import Pipeline
from conveyor.stages import Processor, Pipe, ReplicatingFork, Join
from math import sqrt

def square_root(arg):
    return sqrt(arg)

def cube(arg):
    return arg ** 3

with Pipeline() as pl:
    # Duplicate the input
    pl.add(ReplicatingFork(2))

    # On first copy, compute the sqrt, on the second, the cube
    pl.add(Processor(square_root), Processor(cube))

    # On first copy, compute the sqrt, on the second, do nothing
    pl.add(Processor(square_root), Pipe())

    # Join the two data streams
    pl.add(Join(2))

    # Print the results
    pl.add(Processor(print))

    # Run the pipeline with three different inputs
    pl.run([16, 3, 81])

$ python3 sample.py
2.0
1.3160740129524924
3.0
4096
27
531441

Other links

• Documentation
• PyPI project page

A note on stability

Conveyor is currently considered in alpha. Specifications will change, potentially in breaking ways.

Testing

To run the tests, ensure nose is installed and run nosetests from the project directory

pip3 install nose && nosetests

Building from source

To build the distribution archives, you will need the latest version of setuptools and wheel.

python3 -m pip install --user --upgrade setuptools wheel

Run setup.py to build using the following command:

python3 setup.py sdist bdist_wheel

The compiled .whl and .tar.gz files will be in the /dist directory.