apischema
JSON (de)serialization, GraphQL and JSON schema generation using Python typing.
Decision gist · record as of 2026-08-14
Yes. Apischema is actively maintained, has no dependencies, supports current Python versions, and solves a real problem (API data handling) without imposing a base class or breaking from standard library conventions. The MIT license is permissive. No known security vulnerabilities. Suitable for production use in API clients and servers.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later; PyPy3 is supported.
- Low install friction with no runtime dependencies.
- Active maintenance with recent commits and a steady release cadence since 2020; last release 2024-10-01.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions; you must include a copy of the license and copyright notice.
last release 2024-10-01 (682 days) · last repo commit 2026-08-10 · 242 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 158,326 downloads/mo, #10,727 on PyPI
Alternatives
Verify before relying
pip install apischema
from dataclasses import dataclass
from apischema import deserialize, serialize
@dataclass
class Item:
name: str
value: int
data = {"name": "example", "value": 42}
item = deserialize(Item, data)
result = serialize(Item, item)- Whether performance claims ('a lot faster') have been independently verified against current versions of competing libraries.
- Whether the GraphQL implementation is feature-complete relative to graphql-core or other GraphQL libraries.
- Real-world adoption patterns and ecosystem integration beyond the documented examples.
What it is and what it does
Apischema is a Python library for converting between Python objects and JSON, generating GraphQL schemas, and producing JSON schemas—all driven by standard Python type annotations and dataclasses. It works with any type (dataclasses, NewType, generic collections) without requiring a base class, and integrates with your IDE and type checker naturally.
The library is designed to stay close to Python's standard library (dataclasses, typing) rather than imposing its own object model. It handles validation during deserialization, generates schemas for documentation and API contracts, and supports GraphQL as a first-class concern alongside JSON. It has no runtime dependencies and supports Python 3.9 and later, including PyPy3.
Use it for
- Deserialize and validate JSON API responses into typed Python dataclasses with automatic error reporting.
- Generate JSON Schema and GraphQL schemas from your existing dataclass definitions for API documentation.
- Serialize Python dataclass instances back to JSON for API responses without manual field mapping.
- Build GraphQL query resolvers that work directly with your Python type annotations.
- Adapt the library to support custom types (ORM models, attrs classes) via its conversion system.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Apischema is actively maintained, has no dependencies, supports current Python versions, and solves a real problem (API data handling) without imposing a base class or breaking from standard library conventions. The MIT license is permissive. No known security vulnerabilities. Suitable for production use in API clients and servers.
Install
apischema on PyPI
Before you install
Low install friction with no runtime dependencies. Active maintenance with recent commits and a steady release cadence since 2020; last release 2024-10-01.
Requires Python 3.9 or later; PyPy3 is supported.
License in practice
MIT license permits commercial and private use with minimal restrictions; you must include a copy of the license and copyright notice.
Quickstart
pip install apischema
from dataclasses import dataclass
from apischema import deserialize, serialize
@dataclass
class Item:
name: str
value: int
data = {"name": "example", "value": 42}
item = deserialize(Item, data)
result = serialize(Item, item)Verify before relying
- Whether performance claims ('a lot faster') have been independently verified against current versions of competing libraries.
- Whether the GraphQL implementation is feature-complete relative to graphql-core or other GraphQL libraries.
- Real-world adoption patterns and ecosystem integration beyond the documented examples.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 682 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 158,326 / month, #10,727 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9Topic :: Software Development :: Libraries :: Python Modules |
Evidence: apischema-0.19.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “json serialization deserialization python”
- apischemaApischema handles JSON serialization/deserialization, GraphQL schema…
- databindDatabind deserializes JSON-like nested data structures into Python…
- msrestProvides HTTP client runtime and serialization/deserialization…
Give your agent the search over MCP, or paste the wish link into any chat.
More Python Modules packages
Converts domain names between Unicode and ASCII-compatible encoding (Punycode) according to IDNA 2008 and Unicode Technical Standard 46, with security validation and broader script coverage than the standard library.
Install it if you work with internationalized domain names, need to validate domains, or use HTTP clients that depend on it transitively.
Setuptools is a Python build backend and package management tool that handles building, distributing, and installing Python packages, including support for C/C++ extension modules.
PyYAML parses and emits YAML 1.1 data format, enabling serialization and deserialization of configuration files and Python objects to and from human-readable YAML text.
Pydantic validates Python data structures against type hints, coercing and checking input at runtime to ensure it matches a declared schema.
Provides reusable metadata objects for use with PEP-593 `typing.Annotated` to express common constraints like bounds, collection sizes, and predicates on types.
Install it if you use or build libraries that need to express type constraints in a standardized, inspectable way—or if you want to annotate your own types with…
Provides runtime tools to inspect and introspect Python type annotations, enabling programmatic examination of type hints at execution time.
See also colander · dataclasses-jsonschema · dataclasses-avroschema · py-avro-schema · datamodel-code-generator · json-strong-typing · warchant_dc_schema · desert · djangorestframework-queryfields · anyjson