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pymetastore

A Python client for the Thrift interface to Hive Metastore

pymetastore v0.4.2 125.4K downloads/30d#11,819 on PyPI13
Permissive license MIT AGING released

What it is and what it does

pymetastore wraps the Thrift protocol used by Hive Metastore into a Python-friendly API, letting you programmatically query metadata about databases, tables, and partitions stored in a Hive metastore service. It depends only on thrift and supports Python 3.8 and later, making it a lightweight addition to data engineering workflows that need to inspect or manage Hive metadata without writing raw Thrift code.

The package is typically used in data pipelines and catalog systems where you need to discover table schemas, list partitions, or retrieve metadata properties from a running metastore. It abstracts away the low-level Thrift details and provides context managers and straightforward method calls for common operations like listing databases, fetching table definitions, and querying partition information.

Use it for:

  • Discover table schemas and partition structures from a Hive metastore in a data discovery or catalog tool.
  • Automate metadata validation or governance checks by querying metastore state programmatically.
  • Build data pipeline orchestration logic that depends on inspecting table properties or partition availability.
  • Integrate Hive metastore metadata into a data lineage or data quality monitoring system.
  • Query partition information to dynamically determine which data to process in a batch job.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

pymetastore is a Python client for the Hive Metastore that provides a Thrift-based interface to query and manage metadata about databases, tables, and partitions in a Hive metastore service.

Yes, if you need to query a Hive Metastore from Python code. The package has low install friction, a permissive license, no known vulnerabilities, and provides a clean abstraction over Thrift. Maintenance is aging but not stalled—updates are infrequent but the repo is not archived. Suitable for production use in data engineering contexts where metastore access is a real requirement.

Install

pymetastore on PyPI

pip

pip install pymetastore

uv

uv add pymetastore

poetry

poetry add pymetastore

Installing pymetastore

Before you install

Installation is straightforward with low friction—a pure Python wheel with a single runtime dependency on thrift. The package is in aging maintenance status with a last commit on 2025-11-04, so it receives updates but is not under active development.

License in practice

Licensed under MIT (permissive), so you can use, modify, and distribute pymetastore freely in both open-source and commercial projects without copyleft obligations.

Quickstart

pip install pymetastore

from pymetastore.metastore import HMS

with HMS.create(host="localhost", port=9083) as hms:
    databases = hms.list_databases()
    tables = hms.list_tables(database_name="test_db")

Requires a running Hive Metastore service accessible at the specified host and port (default 9083).

Verify before relying

  • Whether the package supports all Hive metastore operations or only a subset of the full API.
  • Performance characteristics and scalability limits when querying large metastores.
  • Compatibility with specific Hive or Hadoop versions beyond the Python version requirement.

Package facts

License MIT (permissive)
Python support supports the current Python release (>=3.8)
Install friction low — pure-Python wheel
Runtime dependencies 1 — thrift
Maintenance aging — 283 days since the last release
Last repo commit
First released
Downloads 125,436/month — #11,819 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: pymetastore-0.4.2-py3-none-any.whl

Keywords: data, data catalog, data discovery, data engineering, data governance, data infrastructure, data integration, data pipelines, hcatalog, hive, hive metastore, metadata, metastore, thrift, python, recap

Tags

hive metastore clientpython thrift metastorehive metadata querymetastore database tableshcatalog python clientdata catalog integrationhive partition management
hive-ecosystemmetadata-managementdata-engineering

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