tableschema
A utility library for working with Table Schema in Python
Decision gist · record as of 2026-08-14
Yes, if you need to work with Table Schema standard and are not starting a new project. The package is stable and has no known vulnerabilities, but consider Frictionless Framework instead if you are building new data pipelines—tableschema is dormant (638 days since last release) and the maintainers explicitly recommend the successor. Install it for legacy integrations or when Table Schema compatibility is a hard requirement.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low friction install with 10 runtime dependencies.
- Maintenance is dormant—last release was 638 days ago—but the repository remains active and the project has been superseded by Frictionless Framework, which the maintainers recommend for new work.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.
last release 2024-11-14 (638 days) · last repo commit 2024-11-14 · 267 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 446,066 downloads/mo, #6,614 on PyPI
Alternatives
Verify before relying
pip install tableschema
from tableschema import Table
table = Table('data.csv')
table.infer()
for row in table.iter(keyed=True):
print(row)- Whether Python 2.7 support (listed in classifiers) is actually maintained or tested in the current release
- Current compatibility with modern Python versions beyond 3.6 (classifiers list only up to 3.6)
- Whether the package is actively maintained or in maintenance-only mode given the 638-day gap since last release
What it is and what it does
tableschema-py is a Python library that implements the Table Schema standard, allowing you to define, validate, and work with structured tabular data. It provides a `Table` class to read and write data with schema metadata, a `Schema` class to define field types and validation rules, and utilities to infer schemas from raw data and validate data against those schemas. The library handles type casting (converting string values to integers, geopoints, dates, etc.), missing value handling, and can read from local files or remote URLs.
The package is part of the Frictionless Data ecosystem and includes a command-line interface for schema validation and inference. However, the maintainers have released Frictionless Framework as a more complete successor; tableschema remains functional but is no longer the primary recommendation for new projects. It depends on standard libraries like jsonschema, requests, and python-dateutil for its core functionality.
Use it for
- Validate CSV or tabular data files against a predefined Table Schema to ensure data quality and type correctness
- Automatically infer a Table Schema from raw data, then use it to cast and validate subsequent rows
- Define reusable table schemas in JSON format and apply them across multiple data files in a pipeline
- Parse tabular data with proper type casting (e.g., convert string '51.50,-0.11' to a geopoint array) and handle missing values
- Build data validation workflows where invalid rows are collected for reporting rather than stopping on first error
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to work with Table Schema standard and are not starting a new project.
The package is stable and has no known vulnerabilities, but consider Frictionless Framework instead if you are building new data pipelines—tableschema is dormant (638 days since last release) and the maintainers explicitly recommend the successor. Install it for legacy integrations or when Table Schema compatibility is a hard requirement.
Install
tableschema on PyPI
Before you install
Low friction install with 10 runtime dependencies. Maintenance is dormant—last release was 638 days ago—but the repository remains active and the project has been superseded by Frictionless Framework, which the maintainers recommend for new work.
License in practice
MIT license is permissive; you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.
Quickstart
pip install tableschema
from tableschema import Table
table = Table('data.csv')
table.infer()
for row in table.iter(keyed=True):
print(row)Verify before relying
- Whether Python 2.7 support (listed in classifiers) is actually maintained or tested in the current release
- Current compatibility with modern Python versions beyond 3.6 (classifiers list only up to 3.6)
- Whether the package is actively maintained or in maintenance-only mode given the 638-day gap since last release
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 10 packagessixclickrequestscached-propertypython-dateutiljsonschemaunicodecsvisodaterfc3986dataflows-tabulator |
| Maintenance | Dormant 638 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 446,066 / month, #6,614 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaEnvironment :: Web EnvironmentIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 2Programming Language :: Python :: 2.7Programming Language :: Python :: 3Programming Language :: Python :: 3.4Programming Language :: Python :: 3.5Programming Language :: Python :: 3.6Topic :: Internet :: WWW/HTTP :: Dynamic ContentTopic :: Software Development :: Libraries :: Python Modules |
Evidence: tableschema-1.21.0-py2.py3-none-any.whl
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See also csvw · datapackage · frictionless · pycsvschema · tableschema-to-template · tabulator · patito · schema · dataflows-tabulator · pandas-schema