parallel-runner 0.1.2

A Python utility for running functions in parallel using multiprocessing.

ParallelRunner

Overview

ParallelRunner is a Python utility for executing functions in parallel using the multiprocessing module. It allows you to distribute workloads across multiple CPU cores, making it ideal for computationally intensive tasks.

Features:

• Run functions in parallel with controlled concurrency.
• Supports both normal and array-based arguments.
• Optionally track progress using tqdm.
• Handles errors gracefully without stopping execution.
• Supports indexed execution if needed.

Installation

pip install parallel-runner

Usage

Basic Example

from parallel_runner import ParallelRunner

def sample_task(ix, x, y):
    return x + y + ix  # Example function that takes indexed arguments

runner = ParallelRunner(
    procedure=sample_task,
    concurrency=4,
    ix_needed=True,
    use_tqdm=True,
    array_args={"x": [1, 2, 3, 4], "y": [10, 20, 30, 40]},
)

results = runner.run()
print(results)  # Outputs: {0: 11, 1: 23, 2: 35, 3: 47}

Example: Processing Large Data Sets

import time
from parallel_runner import ParallelRunner

def process_data(data_chunk):
    time.sleep(1)  # Simulate a long computation
    return sum(data_chunk)

data = [[i for i in range(100)] for _ in range(10)]
runner = ParallelRunner(
    procedure=process_data,
    concurrency=5,
    array_args={"data_chunk": data},
)

results = runner.run()
print(results)  # Outputs sum of each chunk

Example: Web Scraping in Parallel

import requests
from parallel_runner import ParallelRunner

def fetch_page(ix, url):
    response = requests.get(url)
    return len(response.content)

urls = ["https://example.com" for _ in range(10)]
runner = ParallelRunner(
    procedure=fetch_page,
    concurrency=5,
    ix_needed=True,
    array_args={"url": urls},
)

results = runner.run()
print(results)  # Outputs content length for each page

Parameters

Parameter	Type	Description
procedure	function	The function to run in parallel.
debug	bool	If True, runs sequentially for debugging.
concurrency	int	Number of parallel processes.
ix_needed	bool	If True, passes an index (ix) to the function.
use_tqdm	bool	If True, displays a progress bar.
no_iteration	int	Number of iterations (if array_args is empty).
normal_args	dict	Arguments passed unchanged to all function calls.
array_args	dict	Arguments that vary per process (lists must have the same length).

License

This project is licensed under the MIT License.