{"categories":[{"label":"Database","url":"https://skillfed.io/packages/category/database"}],"enrichment":{"capability":"ArrayRecord is a file format for storing and accessing array data with parallel read/write support and random access by record index, built on Riegeli compression.","skillfed_tags":["data-serialization","parallel-io","array-storage"],"use_cases":["Store and retrieve training datasets for machine learning with parallel I/O in data pipelines","Random-access indexing into large serialized record collections without sequential scanning","Replace Riegeli when you need parallel read/write and indexed record lookup in Python","Efficient data interchange format for distributed computing frameworks handling array data"],"what_it_does":"ArrayRecord is a file format designed for efficient storage and retrieval of array data, derived from Google's Riegeli format. It supports parallel read and write operations, random access by record index, and reuses Riegeli's compression algorithms. The package provides Python bindings to work with ArrayRecord files, making it suitable for machine learning pipelines, data processing workflows, and other scenarios where you need fast, indexed access to serialized array data.\n\nThe package depends on absl-py and etils, and requires Python 3.11 or later. It ships as precompiled wheels for modern Python versions across macOS and Linux platforms, reducing installation complexity. The format is particularly relevant for systems that need to read or write large collections of records in parallel without sequential bottlenecks.","worth_installing":"Yes, if you need parallel record I/O and random indexing for array data. The active maintenance, Apache-2.0 license, and prebuilt wheels make it low-friction to adopt. Install it when your workflow involves large record collections that benefit from indexed access and parallel operations; skip it if you only need sequential streaming or don't require index-based lookups."},"id":"array-record","links":{"html":"https://skillfed.io/packages/array-record","md":"https://skillfed.io/packages/array-record.md","pypi":"https://pypi.org/project/array-record/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-11-13","license_spdx":null,"license_treatment":"permissive","name":"array-record","python_support":"supports_current","summary":"A file format that achieves a new frontier of IO efficiency"},"popularity":{"monthly_downloads":3636122,"position":2548,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.8.3"}