10 posts tagged with "msgspec"

When comparing two things, the advantages are the positive aspects that make one a better choice in a given situation.

Here’s why you should choose msgspec over Pydantic.

msgspec is an extremely fast serialization and validation library that consistently outperforms Pydantic v2 in benchmarks. This performance advantage comes from its design as a lean, compiled-code-based library focused on a narrow set of data handling tasks, whereas Pydantic v2 is a feature-rich framework.

The performance differences are most pronounced in two key areas: parsing/decoding (converting data like JSON into Python objects) and serialization/encoding (converting Python objects into data like JSON).

msgspec is a Python library designed for high-performance serialization and validation, which makes it a powerful partner for FastAPI. It can be used as a drop-in replacement for FastAPI's default Pydantic models to handle data validation and schema generation, often leading to a significant speedup in API performance.

msgspec.Struct is a powerful data class in the msgspec library that's used to define the schema of your data. It's similar to Python's built-in dataclasses or typing.NamedTuple, but it's specifically optimized for high-performance serialization and validation. When you use a Struct, msgspec can perform operations like JSON encoding and decoding significantly faster than standard Python methods because it has a predefined, static understanding of your data's layout.

To annotate JSON schema properties in Python using msgspec, you use msgspec.field to provide metadata and constraints for a struct field. This allows you to define a more detailed schema beyond just the Python type hints, including documentation, default values, and validation rules.

To JSON-encode a Python object using msgspec, you use the msgspec.json.encode() function. This function takes a Python object and returns a bytes object containing the JSON representation. msgspec is known for its high performance and correctness in handling data serialization.

Here's a simple guide with examples.

To convert a msgspec object to a dict, you can use the msgspec.structs.asdict() function. This function recursively converts a msgspec.Struct instance into a dictionary, including any nested Struct objects.

msgspec is a high-performance serialization library designed for modern Python applications. It combines type-safe data modeling, blazing-fast parsing, and flexible support for multiple serialization formats, including MessagePack, JSON, and TOML.

This article outlines the best practices for integrating msgspec into your codebase. It provides a practical, performance-oriented guide to writing cleaner, safer, and faster Python services.

msgspec is gaining attention in the Python ecosystem due to its incredible speed and minimalist design. It's written in Rust, supports JSON and MsgPack, and uses type hints for validation. But like every tool, it’s not perfect - and when compared to the battle-tested and feature-rich Pydantic, there are several key trade-offs to be aware of.

In this article, we’ll explore what msgspec lacks compared to Pydantic, illustrated with code examples and practical reasoning.