--- id: pymongoarrow version: "1.15.0" license: Apache License, Version 2.0 license_treatment: permissive maintenance: active --- # pymongoarrow — Tools for using NumPy, Pandas, Polars, and PyArrow with MongoDB License: permissive · Maintenance: active · Downloads: 228.8K/mo ## What it is and what it does PyMongoArrow is a companion library to PyMongo that bridges MongoDB query results into columnar in-memory formats. It extends PyMongo's collection API with methods like find_pandas_all(), find_arrow_all(), and find_numpy_all() to materialize query results directly as Arrow tables, Pandas DataFrames, or NumPy arrays without intermediate serialization steps. The library is designed for analytical workloads where you need MongoDB data in typed, contiguous-in-memory arrays. It supports optional schema specification for type safety and can infer schemas automatically. Runtime dependencies include pyarrow, pymongo, numpy, and packaging; pandas is optional for DataFrame functionality. Use it for: - Export MongoDB query results as Pandas DataFrames for data analysis and machine learning pipelines - Load MongoDB collections into Apache Arrow tables for efficient columnar processing - Convert MongoDB documents to NumPy arrays for numerical computing workflows - Materialize large MongoDB result sets with explicit schema validation for type safety ## Worth the install? AI-flagged interpretation of the facts above — verify before relying. PyMongoArrow converts MongoDB query results into Apache Arrow tables, Pandas DataFrames, or NumPy arrays for analytical processing. Yes. PyMongoArrow is actively maintained, has no known vulnerabilities, and solves a specific problem—efficient materialization of MongoDB data into analytical formats. The permissive Apache license and broad platform support (Python 3.10–3.14 on macOS, Linux, Windows) make it a low-risk addition. Install it if you regularly need to move MongoDB query results into Arrow, Pandas, or NumPy for analysis. ## Install pip install pymongoarrow uv add pymongoarrow poetry add pymongoarrow ## Installing pymongoarrow Before you install: Medium install friction due to compiled wheels for multiple Python versions and platforms. Active maintenance with recent release (29 days ago) and ongoing repository activity. License in practice: Apache License 2.0 (permissive) allows commercial and private use with minimal restrictions; you may use, modify, and distribute this package freely. Quickstart: pip install pymongoarrow from pymongoarrow.monkey import patch_all from pymongo import MongoClient patch_all() client = MongoClient() data_frame = client.db.collection.find_pandas_all({}) Requires MongoDB server connection; pandas optional but needed for DataFrame output; not supported on big-endian systems. Verify before relying: - Performance characteristics when materializing large result sets into memory - Schema inference behavior when schema parameter is omitted - Compatibility with MongoDB Atlas connection strings beyond the documented srv extra ## Package facts - License: Apache License, Version 2.0 (permissive) - Python support: supports_current - Install friction: medium - Maintenance: active - Downloads: 228.8K/month (top 15,000 on PyPI) - Known vulnerabilities: none known ## Tags mongodb to arrow conversion, mongo query results as dataframe, mongodb numpy pandas export, arrow table from mongodb, mongodb analytical data loading, mongodb-integration, data-analytics, columnar-formats [View on SkillFed](https://skillfed.io/packages/pymongoarrow) · [View on PyPI](https://pypi.org/project/pymongoarrow/)