{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/5"}],"enrichment":{"capability":"Serialize and deserialize Python dataclasses to and from JSON, YAML, TOML, MsgPack, Pickle, and dict formats using a decorator-based API.","skillfed_tags":["serialization","dataclass","type-safe"],"use_cases":["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."],"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.\n\nThe 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).","worth_installing":"Yes. pyserde is actively maintained, has no known vulnerabilities, supports current Python versions (3.10\u20133.14), 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."},"id":"pyserde","links":{"html":"https://skillfed.io/packages/pyserde","md":"https://skillfed.io/packages/pyserde.md","pypi":"https://pypi.org/project/pyserde/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-10","license_spdx":null,"license_treatment":"permissive","name":"pyserde","python_support":"supports_current","summary":"Yet another serialization library on top of dataclasses"},"popularity":{"monthly_downloads":1290473,"position":4104,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.32.0"}