{"categories":[{"label":"Database","url":"https://skillfed.io/packages/category/database"}],"enrichment":{"capability":"fastparquet reads and writes Apache Parquet files in Python, offering a native implementation that integrates with pandas, numpy, and other data processing libraries.","skillfed_tags":["parquet-io","columnar-storage","data-serialization"],"use_cases":["Read Parquet files produced by Spark or Hive into pandas DataFrames for local analysis.","Write pandas DataFrames to Parquet format for efficient columnar storage and downstream consumption by big data tools.","Load specific columns or apply categorical encoding when reading large Parquet files to reduce memory footprint.","Partition data into row groups and apply compression when writing Parquet files for distributed processing.","Integrate Parquet I/O into existing pandas-based data pipelines without introducing a pyarrow dependency."],"what_it_does":"fastparquet is a Python implementation of the Apache Parquet columnar file format, designed to integrate with pandas and numpy for big data workflows. It reads Parquet files into pandas DataFrames and writes DataFrames back to Parquet, supporting features like column selection, categorical encoding, compression, and row-group partitioning. The library has been used implicitly by Dask, Pandas, and intake-parquet.\n\nThe package is now in maintenance mode: as of March 2026, the project is being retired because pandas 3.0 now depends explicitly on pyarrow, eliminating the original rationale for fastparquet's existence. Continued use is anticipated only for those still on pandas 2.x. Installation requires numpy, pandas, and cramjam; optional compression support includes gzip, snappy, brotli, lz4, and zstandard by default.","worth_installing":"Yes, if you are on pandas 2.x and need a lightweight Parquet reader/writer without pyarrow. No, if you are adopting pandas 3.0 or later\u2014use pyarrow instead, which pandas now depends on explicitly. The project is being retired and will receive no further development; evaluate your pandas version and long-term maintenance needs before committing to it."},"id":"fastparquet","links":{"html":"https://skillfed.io/packages/fastparquet","md":"https://skillfed.io/packages/fastparquet.md","pypi":"https://pypi.org/project/fastparquet/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-05-15","license_spdx":null,"license_treatment":"permissive","name":"fastparquet","python_support":"supports_current","summary":"Python support for Parquet file format"},"popularity":{"monthly_downloads":15251519,"position":1192,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"2026.5.0"}