pymetastore
A Python client for the Thrift interface to Hive Metastore
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a running Hive Metastore service accessible at the specified host and port (default 9083).
- 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 · maintenance · safety
MIT (permissive) — Licensed under MIT (permissive), so you can use, modify, and distribute pymetastore freely in both open-source and commercial projects without copyleft obligations.
last release 2025-11-04 (283 days) · last repo commit 2025-11-04 · 13 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 125,436 downloads/mo, #11,819 on PyPI
Alternatives
Verify before relying
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")- 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.
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 on it.
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
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.
Requires a running Hive Metastore service accessible at the specified host and port (default 9083).
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")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 packagethrift |
| 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
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See also hive-metastore-client · hmsclient · google-cloud-dataproc-metastore · pure-transport · google-cloud-bigquery-biglake · apache-airflow-providers-apache-hive · databricks-dbapi · impyla · PyHive · pyhiveapi