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jcrist/msgspec

Analysis updated 2026-07-03

3,752PythonAudience · developerComplexity · 2/5LicenseSetup · easy

TLDR

msgspec is a fast Python library that encodes, decodes, and validates JSON, MessagePack, YAML, and TOML using standard type annotations, combining parsing and schema validation into a single step.

Mindmap

mindmap
  root((msgspec))
    What it does
      Encode data
      Decode and validate
      Type checking
    Formats
      JSON
      MessagePack
      YAML
      TOML
    Core Concept
      Struct type
      Type annotations
      Single-pass validation
    Tech Stack
      Python
      PyPI
      conda-forge
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What do people build with it?

USE CASE 1

Define a Struct with type annotations for an API response and decode incoming JSON into it with automatic type validation in one call.

USE CASE 2

Replace a separate parsing-plus-validation step in a Python web service with msgspec to reduce latency and simplify the code.

USE CASE 3

Serialize Python objects to MessagePack for a high-throughput data pipeline where JSON would be too slow.

USE CASE 4

Use msgspec Structs as a faster alternative to dataclasses in performance-sensitive code that does a lot of object creation and attribute access.

What is it built with?

Python

How does it compare?

jcrist/msgspeccuemacro/finmarketpymymusise/chatglm-tuning
Stars3,7523,7523,752
LanguagePythonPythonPython
Setup difficultyeasymoderatehard
Complexity2/53/54/5
Audiencedeveloperdataresearcher

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min
Use, modify, and distribute freely for any purpose including commercial use, with the copyright notice and license text retained.

In plain English

msgspec is a Python library for converting data between Python objects and common data formats: JSON, MessagePack, YAML, and TOML. Its main selling point is speed. According to the benchmarks linked in the README, its JSON and MessagePack implementations are the fastest available for Python, and it can decode and validate JSON faster than some libraries can decode JSON alone. The library works by letting you define your data shapes using standard Python type annotations. You create a Struct (a lightweight alternative to Python's built-in dataclasses) that describes what fields a piece of data should have and what types they should be. When you decode incoming data into that Struct, msgspec automatically checks that the values match the expected types and raises a clear error with a precise location if something does not match. This combines what would normally be two separate steps, parsing and validation, into a single fast operation. Encoding goes the other way: a Python Struct gets serialized into bytes in whichever format you choose. The library can also be used purely for its fast JSON or MessagePack encoding and decoding without any schema validation, for cases where you just need raw speed. A Struct behaves similarly to a dataclass or an attrs class, so developers already familiar with those patterns will find the API straightforward. The README notes that common operations on Structs are five to sixty times faster than the equivalent dataclass operations in benchmarks. The library has no required dependencies and is available on PyPI and conda-forge. It is released under the New BSD license. The project's documentation site covers the full API, extension points for adding support for custom types, and detailed benchmarks comparing it to other Python serialization libraries.

Copy-paste prompts

Prompt 1
Show me how to define a msgspec Struct for a JSON API response that has nested objects and optional fields, then decode a JSON bytes value into it with automatic validation.
Prompt 2
I have a FastAPI endpoint that receives JSON payloads. Show me how to use msgspec instead of Pydantic for decoding and validation and explain the performance trade-off.
Prompt 3
Write a Python script that encodes a list of msgspec Structs to MessagePack, writes the bytes to a file, then reads and decodes them back into Struct instances.
Prompt 4
How do I add a custom encoder to msgspec so that datetime objects are serialized as ISO 8601 strings in JSON output?

Frequently asked questions

What is msgspec?

msgspec is a fast Python library that encodes, decodes, and validates JSON, MessagePack, YAML, and TOML using standard type annotations, combining parsing and schema validation into a single step.

What language is msgspec written in?

Mainly Python. The stack also includes Python.

What license does msgspec use?

Use, modify, and distribute freely for any purpose including commercial use, with the copyright notice and license text retained.

How hard is msgspec to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is msgspec for?

Mainly developer.

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