# Pyrefly

## Docs

- [Infer](autotype): Automatically add type annotations to your code with the Pyrefly infer feature.
- [Configuration](configuration): Configure Pyrefly settings and options
- [Django Support](django): Pyrefly support for Django ORM.
- [Pyrefly Error Kinds](error-kinds): Pyrefly error categories and suppression codes
- [Pyrefly Error Suppressions](error-suppressions): Learn how to suppress type check errors in Pyrefly with code comments and baseline files.
- [IDE Installation](IDE): How to add Pyrefly Language Server and Typechecking to your IDE
- [IDE Supported Features](IDE-features): Supported features for Pyrefly's IDE extension
- [Import Resolution](import-resolution): How imports in a given file are found by Pyrefly and their bindings are resolved, including files that are being type checked
- [Introduction](index): Guides and references for all you need to know about Pyrefly type checker and IDE extension.
- [Installation](installation): How to install Pyrefly
- [Migrating from Mypy](migrating-from-mypy): How to switch your type checker configuration from Mypy to Pyrefly
- [Migrating from Pyright](migrating-from-pyright): How to switch your type checker configuration from Pyright to Pyrefly
- [Migration Guides](migrating-to-pyrefly): How to switch from another type checker to Pyrefly
- [Pydantic Support](pydantic): Pyrefly support for Pydantic.
- [Pydantic Lax Mode Type Conversions](pydantic-lax-conversions): Complete reference of how Pyrefly converts types in Pydantic lax mode.
- [FAQ](pyrefly-faq): Frequently Asked Questions about Pyrefly, a PEP 484 compliant Type Checker for Python and IDE extension.
- [Typing Features and PEPS](python-features-and-peps): Typing features and associated PEPs available in each Python version.
- [Python Typing 101](python-typing-for-beginners): A gentle, example‑driven introduction to static type hints in Python.
- [Coverage](report): Measure and enforce type coverage in your Python codebase with Pyrefly.
- [Stub Generation](stubgen): Generate .pyi stub files from Python source files with Pyrefly stubgen.
- [Tensor Shapes](tensor-shapes): An overview of Pyrefly's tensor shape type system for static type checking of PyTorch models.
- [Agent Skill for Tensor Shape Porting](tensor-shapes-ai-porting): How to use the port-model agent skill to automatically add tensor shape annotations to PyTorch models.
- [Contributing](tensor-shapes-contributing): How to extend tensor shape coverage by adding fixture stubs, DSL specifications, and ported models.
- [API Reference](tensor-shapes-reference): Complete reference for Dim, Tensor, and tensor shape type system APIs.
- [Getting Started](tensor-shapes-setup): How to configure Pyrefly for tensor shape checking and set up your project.
- [Tutorial 4: Configs and Dynamic Patterns](tensor-shapes-tutorial-advanced): Parameterized config dataclasses, dynamic construction patterns, and typed interfaces.
- [Tutorial 3: Complex Architectures](tensor-shapes-tutorial-architectures): Type encoder-decoder skip connections and recursive chains with exponential shapes.
- [Tutorial 1: Your First Port](tensor-shapes-tutorial-basics): Learn the basics of tensor shape annotations by typing a simple multi-layer perceptron (MLP) model.
- [Tutorial 2: Loops and Stacking](tensor-shapes-tutorial-loops): Type shape-preserving loops and ModuleList iteration in Transformer-style architectures.
- [Typing for Python Developers](typing-for-python-developers): Get to know Python's Type System with working examples