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jsonschema

An implementation of JSON Schema validation for Python

Worth itPyPI JSONReleased Jan 2026596.9M downloads / moMITPure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — jsonschema-4.26.0-py3-none-any.whl
v4.26.0 · released 2026-01-07 · Python >=3.10 · 4 runtime deps: attrs, jsonschema-specifications, referencing, rpds-py

Yes. jsonschema is a mature, actively maintained, widely-adopted library with no known vulnerabilities, permissive MIT licensing, and low install friction. It solves a core problem—validating structured data against schemas—with a simple API and broad schema standard support. Install it if you need to validate JSON or JSON-like data structures.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.10 or later
  • Low friction installation with four runtime dependencies.
  • Actively maintained with recent releases; last commit 2026-08-10.

License · maintenance · safety

MIT (permissive) — MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects.

last release 2026-01-07 (219 days) · last repo commit 2026-08-10 · 4,968 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 596,925,041 downloads/mo, #57 on PyPI

Verify before relying

from jsonschema import validate

schema = {"type": "object", "properties": {"price": {"type": "number"}}}
validate(instance={"price": 34.99}, schema=schema)
  • Performance characteristics when validating large or deeply nested JSON structures
  • Whether optional format validation extras (format, format-nongpl) are commonly needed in practice
Same gist for agents: .md · .json

What it is and what it does

jsonschema is a Python implementation of the JSON Schema specification that validates data structures against schema definitions. It supports Draft 2020-12, Draft 2019-09, Draft 7, Draft 6, Draft 4, and Draft 3 schemas. The core function is straightforward: pass an instance and a schema to validate(), and it either succeeds silently or raises a ValidationError with details about what failed. For more detailed error reporting, you can iterate through all validation errors rather than stopping at the first one.

The package depends on attrs, jsonschema-specifications, referencing, and rpds-py for its core functionality. It's designed for developers who need to enforce data structure contracts—checking that incoming JSON conforms to expected types, required fields, and constraints before processing. Optional extras for format validation are available but not required for basic schema validation.

Use it for

  • Validate API request/response payloads against a schema before processing or returning them
  • Check configuration file structure at startup to catch malformed configs early
  • Enforce data contracts in microservices or event-driven systems
  • Test data fixtures against expected schemas in unit tests
  • Programmatically query which fields or items failed validation for detailed error reporting

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

Worth it

Yes.

jsonschema is a mature, actively maintained, widely-adopted library with no known vulnerabilities, permissive MIT licensing, and low install friction. It solves a core problem—validating structured data against schemas—with a simple API and broad schema standard support. Install it if you need to validate JSON or JSON-like data structures.

Install

jsonschema on PyPI

Before you install

Low friction installation with four runtime dependencies. Actively maintained with recent releases; last commit 2026-08-10. Widely adopted (top 100 PyPI packages by downloads).

Requires Python 3.10 or later

License in practice

MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects.

Quickstart

from jsonschema import validate

schema = {"type": "object", "properties": {"price": {"type": "number"}}}
validate(instance={"price": 34.99}, schema=schema)

Verify before relying

  • Performance characteristics when validating large or deeply nested JSON structures
  • Whether optional format validation extras (format, format-nongpl) are commonly needed in practice

Package facts

LicenseMIT permissive
Python supportSupports the current Python release >=3.10
Install frictionLow. Pure-Python wheel
Runtime dependencies
4 packages
attrsjsonschema-specificationsreferencingrpds-py
MaintenanceActively maintained 219 days since the last release
Last repo commit
First released
Downloads596,925,041 / month, #57 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 5 - Production/StableIntended Audience :: DevelopersOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: File Formats :: JSONTopic :: File Formats :: JSON :: JSON Schema

Evidence: jsonschema-4.26.0-py3-none-any.whl

Tags

Capabilities
json schema validationvalidate json datajson schema validatordata validation against schemajson schema complianceschema validation libraryjson format checking
Topics
data-validationjson-schema
PyPI keywords
data validationjsonjson schemajsonschemavalidation

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See also check-jsonschema · eido · pycsvschema · jsonschema-typed-v2 · jschon · spdx3-validate · marshmallow-jsonschema · webargs