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Dev tools · March 15, 2025

Aiopandas – Async .apply() and .map() for Pandas, Faster API/LLMs Calls

Lightweight Pandas monkey-patch that adds async support to map, apply, applymap, aggregate, and transform, enabling seamless handling of async functions with controlled max_parallel execution. - telekinesis-inc/aiopandas

Aiopandas – Async .apply() and .map() for Pandas, Faster API/LLMs Calls launched on March 15, 2025 with 62 votes, #495 of 7,215 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 1 year on.

Visit github.com ↗Alternativestop 7% of March 2025

In plain words

Aiopandas is a Python library that adds asynchronous apply() and map() methods to Pandas DataFrames and Series. It enables concurrent processing of data transformations, making it particularly useful for speeding up API calls and LLM interactions that would otherwise block execution. The tool is designed for data engineers and developers who need to handle large-scale data operations with external services more efficiently than traditional synchronous Pandas methods allow.

written from the facts on this page · September 2026

From the sources

🚀 Async-Powered Pandas : Lightweight Pandas monkey-patch that adds async support to map , apply , applymap , aggregate , and transform , enabling seamless handling of async functions with controlled parallel execution ( max_parallel ). import aiopandas as pd # Monkey-patches Pandas with async methods import asyncio # Create a sample DataFrame df = pd . DataFrame ({ 'x' : range ( 10 )}) # Define an async function (simulating API calls, I/O, etc.) async def f ( x ): await asyncio . sleep ( 0.1 * x ) # Simulate async processing return x * 2 # Example transformation # Apply the async function to the DataFrame column df [ 'y' ] = await df . x . amap ( f , max_parallel = 5 ) # Default…from github.com

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