jsons
For serializing Python objects to JSON (dicts) and back
Decision gist · record as of 2026-08-14
Yes, if you need straightforward object-to-JSON serialization for dataclasses or attrs without boilerplate. The library is stable and has no known vulnerabilities, but be aware it is dormant (last release 2022-06-09, last commit 2023-12-29). It works well for current Python versions and common use cases, but may not receive updates for future language features. Install it if your project's Python version and dependencies are stable; avoid it if you need active maintenance or cutting-edge typing support.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low install friction; single runtime dependency (typish).
- Maintenance is dormant—last release was 2022-06-09 and last commit 2023-12-29.
- No active development reported.
License · maintenance · safety
MIT (permissive) — MIT license (permissive). No restrictions on use, modification, or distribution in commercial or private projects.
last release 2022-06-09 (1527 days) · last repo commit 2023-12-29 · 291 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,471,741 downloads/mo, #3,867 on PyPI
Alternatives
Verify before relying
pip install jsons
import jsons
from dataclasses import dataclass
from datetime import datetime
@dataclass
class Person:
name: str
birthday: datetime
p = Person('Guido van Rossum', datetime(1956, 1, 31, 12, 0))
out = jsons.dump(p) # {'name': 'Guido van Rossum', 'birthday': '1956-01-31T12:00:00'}
p2 = jsons.load(out, Person) # Deserialize back to Person instance- Whether dormant status poses compatibility risks with Python 3.11+ or newer typing constructs.
- Real-world performance characteristics when serializing deeply nested or large object graphs.
- Whether typish dependency is actively maintained and compatible with current Python versions.
What it is and what it does
jsons is a serialization library that converts Python objects into JSON-compatible dicts and strings, then deserializes them back into typed instances. It works with dataclasses, attrs classes, and plain Python objects without requiring changes to your class definitions. The library handles common types (datetime, date, time, timezone, timedelta, Decimal, Path) and supports generic types like List and Dict with type hints.
You use it by calling jsons.dump() to serialize an instance to a dict, and jsons.load() to deserialize a dict back into a typed object. It's designed to be customizable and extendable, with support for complex nested structures and optional type-aware validation. The single runtime dependency is typish, and installation is straightforward.
Use it for
- Serialize dataclass instances to JSON for API responses or file storage without manual field mapping.
- Deserialize JSON payloads into typed dataclass or attrs objects with automatic type conversion (e.g., string to datetime).
- Convert Python objects to dicts for database storage or caching while preserving type information.
- Handle nested structures with generic types (e.g., List[MyClass] or Dict[str, OtherClass]) in a single call.
- Build REST API handlers that accept JSON and automatically convert it to domain objects.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need straightforward object-to-JSON serialization for dataclasses or attrs without boilerplate.
The library is stable and has no known vulnerabilities, but be aware it is dormant (last release 2022-06-09, last commit 2023-12-29). It works well for current Python versions and common use cases, but may not receive updates for future language features. Install it if your project's Python version and dependencies are stable; avoid it if you need active maintenance or cutting-edge typing support.
Install
jsons on PyPI
Before you install
Low install friction; single runtime dependency (typish). Maintenance is dormant—last release was 2022-06-09 and last commit 2023-12-29. No active development reported.
License in practice
MIT license (permissive). No restrictions on use, modification, or distribution in commercial or private projects.
Quickstart
pip install jsons
import jsons
from dataclasses import dataclass
from datetime import datetime
@dataclass
class Person:
name: str
birthday: datetime
p = Person('Guido van Rossum', datetime(1956, 1, 31, 12, 0))
out = jsons.dump(p) # {'name': 'Guido van Rossum', 'birthday': '1956-01-31T12:00:00'}
p2 = jsons.load(out, Person) # Deserialize back to Person instanceVerify before relying
- Whether dormant status poses compatibility risks with Python 3.11+ or newer typing constructs.
- Real-world performance characteristics when serializing deeply nested or large object graphs.
- Whether typish dependency is actively maintained and compatible with current Python versions.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.5 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagetypish |
| Maintenance | Dormant 1,527 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,471,741 / month, #3,867 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.5Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: jsons-1.6.3-py3-none-any.whl
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See also databind.json · dataclass-factory · databind · vdf · serpyco-rs · typedload · php2json · typed-json-dataclass · databind.core · attrs