How do I use infer-types with Python 3.9 or older?

Add 'from __future__ import annotations' at the top of each file or use isort with the --add-import flag, as recommended in the README, to ensure compatibility with the modern syntax output.

Does infer-types work well with frameworks like Django or Flask?

It can infer types for standard Python code, but may struggle with framework-specific patterns like ORM models or decorators, so manual review is often needed for accuracy.

infer-types vs mypy: which is better for type checking?

infer-types is for adding annotations automatically, while mypy is for static type checking; they complement each other, but infer-types focuses on inference, not validation.

Can infer-types handle async functions and generics?

It has basic support for async via heuristics like yielding for iterators, but complex generics or type variables may require manual annotation due to limitations in static inference.

What should I do if infer-types makes incorrect type guesses?

Review and manually correct the annotations, as the tool uses heuristics that can produce false positives; running type checkers like mypy afterward can help identify errors.

Is infer-types safe to run on production code without breaking it?

Yes, it's static and doesn't execute code, but always use version control and review changes, as incorrect annotations could affect type safety or readability in edge cases.

Open-Awesome

infer-types

MITPython1.0.0

A CLI tool that automatically adds type annotations to Python code using static analysis and heuristics.

GitHub

102 stars6 forks0 contributors

What is infer-types?

infer-types is a CLI tool that automatically adds type annotations to Python code using static analysis and heuristics. It helps developers annotate large, legacy codebases by inferring simple return types and reducing manual typing effort.

Target Audience

Python developers working on large or old codebases who need to add type annotations efficiently, and teams adopting type hints for better code maintainability.

Value Proposition

It provides a fully automated, static approach to type inference with smart heuristics and typeshed integration, significantly speeding up the annotation process compared to manual typing.

Overview

A CLI tool to automatically add type annotations into Python code. Must have tool for annotating existing code.

Use Cases

Best For

Adding type annotations to large, untyped Python codebases
Refactoring legacy Python code to include type hints
Automating simple type inference for functions with obvious return types
Integrating type checking into CI/CD pipelines for existing projects
Reducing manual effort when adopting Python's type system
Enforcing consistent type annotations across a project

Not Ideal For

Projects with highly dynamic or polymorphic code where static inference fails
Teams requiring 100% accurate type annotations without manual review
Codebases targeting Python versions below 3.10 without __future__ imports

Pros & Cons

Pros

Fully Automated Inference

Infers types 100% statically without executing code, allowing safe and fast annotation of large codebases with minimal effort, as highlighted in the README.

Smart Heuristic Rules

Uses multiple inference rules like function name patterns (e.g., 'is_' for bool) and control flow analysis, improving accuracy for common coding scenarios based on the documentation.

Typeshed Integration

Leverages the typeshed repository to find annotations for unannotated dependencies, reducing gaps in type coverage as mentioned in the features list.

Modern Syntax Output

Defaults to Python 3.10+ type syntax such as 'str | None', promoting cleaner code, though it requires adjustments for older versions.

Cons

Requires Post-Processing

Output can have duplicated or misplaced imports, necessitating additional tools like isort for cleanup, which adds steps to the workflow as noted in the usage instructions.

Limited to Simple Cases

The README admits it won't solve 100% of cases; complex logic or ambiguous types often need manual intervention, reducing effectiveness for advanced typing scenarios.

Python Version Constraints

Modern syntax output may break compatibility with Python versions below 3.10 unless __future__ annotations are added, introducing extra work for legacy projects.

Frequently Asked Questions

Related Projects

pyre-check

Performant type-checking for python.

Stars7,171

Forks452

Last commit28 days ago

monkeytype

A Python library that generates static type annotations by collecting runtime types

Stars5,002

Forks209

Last commit5 months ago

pyannotate

Auto-generate PEP-484 annotations

Stars1,443

Forks60

Last commit18 days ago

RightTyper

A fast and efficient type assistant for Python, including tensor shape inference

Stars359

Forks7

Last commit2 months ago

Community-curated · Updated weekly · 100% open source

Found a gem we're missing?

Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.

Submit a project Star on GitHub