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

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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