---
id: pyserde
version: "0.32.0"
license: MIT License Copyright (c) 2021 yukinarit Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in… (full text in the JSON record)
license_treatment: permissive
maintenance: active
---

# pyserde — Yet another serialization library on top of dataclasses

License: permissive · Maintenance: active · Downloads: 1.3M/mo

## What it is and what it does

pyserde is a serialization library built on top of Python dataclasses that converts objects to and from multiple formats (JSON, YAML, TOML, MsgPack, Pickle, dict) using a decorator. You annotate your dataclass fields with PEP 484 type hints, and the library generates serialization and deserialization code automatically. It handles a wide range of types including primitives, standard containers (list, dict, set, tuple), Optional and Union types, datetime objects, UUID, Path, Decimal, Enum, and numpy types.

The library focuses on simplicity: declare your class, decorate it, and call to_json() or from_json() to convert. It supports field-level customization (rename, alias, skip conditions, custom serializers), class-level attributes (case conversion, custom serializers), and advanced features like flattening, forward references, and generic types. Dependencies are minimal and well-established (beartype for runtime type checking, jinja2 for code generation, plum-dispatch for method dispatch).

Use it for:

- Convert API request/response dataclasses to JSON for REST endpoints or webhooks.
- Load configuration files (YAML, TOML) into typed dataclass objects with validation.
- Serialize domain objects to multiple formats (JSON for APIs, Pickle for caching) from a single definition.
- Build data pipelines where objects move between services in different formats without manual conversion.
- Validate and transform incoming JSON data into strongly-typed Python objects.
- Store and retrieve structured data with automatic type checking during deserialization.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Serialize and deserialize Python dataclasses to and from JSON, YAML, TOML, MsgPack, Pickle, and dict formats using a decorator-based API.

Yes. pyserde is actively maintained, has no known vulnerabilities, supports current Python versions (3.10–3.14), and offers a clean, decorator-based API for multi-format serialization of dataclasses. Install friction is low and the dependency set is reasonable. It is a solid choice for projects that need type-safe serialization without the overhead of heavier frameworks.

## Install

pip install pyserde
uv add pyserde
poetry add pyserde

## Installing pyserde

Before you install: Low friction install with a pure-Python wheel. Actively maintained with a release 4 days ago; repository shows 851 stars and recent activity. Six runtime dependencies (beartype, casefy, jinja2, plum-dispatch, typing-extensions, typing-inspect) are all standard utilities with minimal overhead.

License in practice: MIT License permits unrestricted use, modification, and distribution in both open-source and commercial projects with only attribution required.

Quickstart:

pip install pyserde

from pyserde import to_json, from_json

@serde
class Foo:
    i: int
    s: str

obj = Foo(i=10, s='foo')
json_str = to_json(obj)
obj_restored = from_json(Foo, json_str)

Requires Python 3.10 or later (3.10, 3.11, 3.12, 3.13, 3.14 supported).

Verify before relying:

- Performance characteristics compared to other serialization libraries in typical workloads.
- Maturity and stability of experimental SQLAlchemy integration.
- Whether custom (de)serializers handle all edge cases users encounter in production.

## Package facts

- License: MIT License Copyright (c) 2021 yukinarit Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in… (full text in the JSON record) (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 1.3M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

dataclass serialization, json serialization library, python serialization, serialize deserialize dataclass, yaml json conversion, type-safe serialization, multi-format serialization, serialization, dataclass, type-safe

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