fastavro
Fast read/write of AVRO files
Decision gist · record as of 2026-08-14
Yes. fastavro is production-stable, actively maintained, permissively licensed, has zero runtime dependencies, and offers substantial performance gains over pure-Python alternatives. Install it if you work with Avro files or need fast serialization of structured data. The C-extension build is well-supported across modern Python versions and platforms.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later; C extensions are precompiled for common platforms but may require a C compiler if building from source on an unsupported platform.
- Medium install friction due to C extensions; however, prebuilt wheels cover CPython 3.9–3.14 and PyPy3 across macOS, Linux (including musllinux), and Windows.
- Repository is active with recent commits and stable maintenance.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you may use, modify, and distribute fastavro freely in commercial and private projects with minimal restrictions.
last release 2026-04-24 (112 days) · last repo commit 2026-08-07 · 711 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 45,741,179 downloads/mo, #616 on PyPI
Alternatives
Verify before relying
pip install fastavro
import fastavro
with open('data.avro', 'rb') as f:
for record in fastavro.reader(f):
print(record)- Whether the C extension performance gains (1.7 seconds vs 14 seconds on 10,000 records) remain representative for current workloads and file sizes.
- Specific codec library availability and whether optional codec dependencies are automatically installed or must be added separately.
What it is and what it does
fastavro is a high-performance library for reading and writing Apache Avro files in Python. It wraps C extensions to achieve speed comparable to the Java Avro SDK—iterating 10,000 records in 1.7 seconds with CPython versus 14 seconds for the pure-Python Apache avro package. It supports file and schemaless read/write modes, JSON serialization, multiple compression codecs (Snappy, Deflate, Zstandard, Bzip2, LZ4, XZ), schema resolution, logical types, and schema fingerprinting.
The library is production-stable, actively maintained, and available as prebuilt wheels for Python 3.9–3.14 on CPython and PyPy3 across macOS, Linux, and Windows. It has no runtime dependencies, making installation straightforward. RPC features are not supported. Use it when you need fast Avro serialization in data pipelines, ETL workflows, or applications that process large volumes of Avro-encoded records.
Use it for
- Deserialize large Avro files in data pipelines where pure-Python libraries are too slow.
- Serialize structured data to Avro format for efficient storage or transmission with schema evolution support.
- Read Avro records from Kafka or other message brokers with schema resolution and codec decompression.
- Convert between Avro and JSON formats while preserving schema metadata and logical types.
- Build ETL jobs that require fast iteration over millions of Avro records with optional compression.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
fastavro is production-stable, actively maintained, permissively licensed, has zero runtime dependencies, and offers substantial performance gains over pure-Python alternatives. Install it if you work with Avro files or need fast serialization of structured data. The C-extension build is well-supported across modern Python versions and platforms.
Install
fastavro on PyPI
Before you install
Medium install friction due to C extensions; however, prebuilt wheels cover CPython 3.9–3.14 and PyPy3 across macOS, Linux (including musllinux), and Windows. Repository is active with recent commits and stable maintenance.
Requires Python 3.9 or later; C extensions are precompiled for common platforms but may require a C compiler if building from source on an unsupported platform.
License in practice
MIT license is permissive; you may use, modify, and distribute fastavro freely in commercial and private projects with minimal restrictions.
Quickstart
pip install fastavro
import fastavro
with open('data.avro', 'rb') as f:
for record in fastavro.reader(f):
print(record)Verify before relying
- Whether the C extension performance gains (1.7 seconds vs 14 seconds on 10,000 records) remain representative for current workloads and file sizes.
- Specific codec library availability and whether optional codec dependencies are automatically installed or must be added separately.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 112 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 45,741,179 / month, #616 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: Scientific/Engineering :: Information AnalysisTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python Modules |
Evidence: fastavro-1.12.2-cp310-cp310-macosx_10_9_universal2.whl; fastavro-1.12.2-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; fastavro-1.12.2-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; fastavro-1.12.2-cp310-cp310-musllinux_1_2_aarch64.whl; fastavro-1.12.2-cp310-cp310-musllinux_1_2_x86_64.whl; fastavro-1.12.2-cp310-cp310-win_amd64.whl; fastavro-1.12.2-cp311-cp311-macosx_10_9_universal2.whl; fastavro-1.12.2-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; fastavro-1.12.2-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; fastavro-1.12.2-cp311-cp311-musllinux_1_2_aarch64.whl; fastavro-1.12.2-cp311-cp311-musllinux_1_2_x86_64.whl; fastavro-1.12.2-cp311-cp311-win_amd64.whl; fastavro-1.12.2-cp311-cp311-win_arm64.whl; fastavro-1.12.2-cp312-cp312-macosx_10_13_universal2.whl; fastavro-1.12.2-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; fastavro-1.12.2-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; fastavro-1.12.2-cp312-cp312-musllinux_1_2_aarch64.whl; fastavro-1.12.2-cp312-cp312-musllinux_1_2_x86_64.whl; fastavro-1.12.2-cp312-cp312-win_amd64.whl; fastavro-1.12.2-cp312-cp312-win_arm64.whl
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