A static type analyzer for Python code

Overview

CI PyPI - Wheel

pytype - ?

Pytype checks and infers types for your Python code - without requiring type annotations. Pytype can:

  • Lint plain Python code, flagging common mistakes such as misspelled attribute names, incorrect function calls, and much more, even across file boundaries.
  • Enforce user-provided type annotations. While annotations are optional for pytype, it will check and apply them where present.
  • Generate type annotations in standalone files ("pyi files"), which can be merged back into the Python source with a provided merge-pyi tool.

Pytype is a static analyzer; it does not execute the code it runs on.

Thousands of projects at Google rely on pytype to keep their Python code well-typed and error-free.

For more information, check out the user guide, FAQ, or supported features.

How is pytype different from other type checkers?

  1. Pytype uses inference instead of gradual typing. This means it will infer types on code even when the code has no type hints on it. So it can detect issues with code like this, which other type checkers would miss:

    def f():
        return "PyCon"
    def g():
        return f() + 2019
    
    # pytype: line 4, in g: unsupported operand type(s) for +: 'str'
    # and 'int' [unsupported-operands]
  2. Pytype is lenient instead of strict. That means it allows all operations that succeed at runtime and don't contradict annotations. For instance, this code will pass as safe in pytype, but fail in other type checkers, which assign types to variables as soon as they are initialized:

    from typing import List
    def get_list() -> List[str]:
        lst = ["PyCon"]
        lst.append(2019)
        return [str(x) for x in lst]
    
    # mypy: line 4: error: Argument 1 to "append" of "list" has
    # incompatible type "int"; expected "str"

Also see the corresponding FAQ entry.

Quickstart

To quickly get started with type-checking a file or directory, run the following, replacing file_or_directory with your input:

pip install pytype
pytype file_or_directory

To set up pytype on an entire package, add the following to a setup.cfg file in the directory immediately above the package, replacing package_name with the package name:

[pytype]
inputs = package_name

Now you can run the no-argument command pytype to type-check the package. It's also easy to add pytype to your automated testing; see this example of a GitHub project that runs pytype on Travis.

Finally, pytype generates files of inferred type information, located by default in .pytype/pyi. You can use this information to type-annotate the corresponding source file:

merge-pyi -i <filepath>.py .pytype/pyi/<filename>.pyi

Requirements

You need a Python 3.6-3.8 interpreter to run pytype, as well as an interpreter in $PATH for the Python version of the code you're analyzing (supported: 2.7, 3.5-3.8).

Platform support:

  • Pytype is currently developed and tested on Linux*, which is the main supported platform.
  • Installation on MacOSX requires OSX 10.7 or higher and Xcode v8 or higher.
  • Windows is currently not supported unless you use WSL.

* Note: On Alpine Linux, installing may fail due to issues with upstream dependencies. See the details of this issue for a possible fix.

Installing

Pytype can be installed via pip. Note that the installation requires wheel and setuptools. (If you're working in a virtualenv, these two packages should already be present.)

pip install pytype

Or from the source code on GitHub.

git clone --recurse-submodules https://github.com/google/pytype.git
cd pytype
pip install .

Instead of using --recurse-submodules, you could also have run

git submodule init
git submodule update

in the pytype directory. To edit the code and have your edits tracked live, replace the pip install command with:

pip install -e .

Installing on WSL

Follow the steps above, but make sure you have the correct libraries first:

sudo apt install build-essential python3-dev libpython3-dev

Usage

usage: pytype [options] input [input ...]

positional arguments:
  input                 file or directory to process

Common options:

  • -V, --python-version: Python version (major.minor) of the target code. Defaults to the version that pytype is running under.
  • -o, --output: The directory into which all pytype output goes, including generated .pyi files. Defaults to .pytype.
  • -d, --disable. Comma or space separated list of error names to ignore. Detailed explanations of pytype's error names are in this doc. Defaults to empty.

For a full list of options, run pytype --help.

In addition to the above, you can direct pytype to use a custom typeshed installation instead of its own bundled copy by setting $TYPESHED_HOME.

Config File

For convenience, you can save your pytype configuration in a file. The config file is an INI-style file with a [pytype] section; if an explicit config file is not supplied, pytype will look for a [pytype] section in the first setup.cfg file found by walking upwards from the current working directory.

Start off by generating a sample config file:

$ pytype --generate-config pytype.cfg

Now customize the file based on your local setup, keeping only the sections you need. Directories may be relative to the location of the config file, which is useful if you want to check in the config file as part of your project.

For example, suppose you have the following directory structure and want to analyze package ~/repo1/foo, which depends on package ~/repo2/bar:

~/
├── repo1
│   └── foo
│       ├── __init__.py
│       └── file_to_check.py
└── repo2
    └── bar
        ├── __init__.py
        └── dependency.py

Here is the filled-in config file, which instructs pytype to type-check ~/repo1/foo as Python 3.6 code, look for packages in ~/repo1 and ~/repo2, and ignore attribute errors. Notice that the path to a package does not include the package itself.

$ cat ~/repo1/pytype.cfg

# NOTE: All relative paths are relative to the location of this file.

[pytype]

# Space-separated list of files or directories to process.
inputs =
    foo

# Python version (major.minor) of the target code.
python_version = 3.6

# Paths to source code directories, separated by ':'.
pythonpath =
    .:
    ~/repo2

# Comma or space separated list of error names to ignore.
disable =
    attribute-error

We could've discovered that ~/repo2 needed to be added to the pythonpath by running pytype's broken dependency checker:

$ pytype --config=~/repo1/pytype.cfg ~/repo1/foo/*.py --unresolved

Unresolved dependencies:
  bar.dependency

Subtools

Pytype ships with a few scripts in addition to pytype itself:

  • annotate-ast, an in-progress type annotator for ASTs.
  • merge-pyi, for merging type information from a .pyi file into a Python file.
  • pytd-tool, a parser for .pyi files.
  • pytype-single, a debugging tool for pytype developers, which analyzes a single Python file assuming that .pyi files have already been generated for all of its dependencies.
  • pyxref, a cross references generator.

2021 Roadmap

  • Python 3.9 support
  • Better performance on large files
  • Support for numerical libraries

License

Apache 2.0

Disclaimer

This is not an official Google product.

Owner
Google
Google ❤️ Open Source
Google
Pymwp is a tool for automatically performing static analysis on programs written in C

pymwp: MWP analysis in Python pymwp is a tool for automatically performing static analysis on programs written in C, inspired by "A Flow Calculus of m

Static Analyses of Program Flows: Types and Certificate for Complexity 2 Dec 02, 2022
Find dead Python code

Vulture - Find dead code Vulture finds unused code in Python programs. This is useful for cleaning up and finding errors in large code bases. If you r

Jendrik Seipp 2.4k Jan 03, 2023
TidyPy is a tool that encapsulates a number of other static analysis tools and makes it easy to configure, execute, and review their results.

TidyPy Contents Overview Features Usage Docker Configuration Ignoring Issues Included Tools Included Reporters Included Integrations Extending TidyPy

Jason Simeone 33 Nov 27, 2022
Unbearably fast O(1) runtime type-checking in pure Python.

Look for the bare necessities, the simple bare necessities. Forget about your worries and your strife. — The Jungle Book.

1.4k Dec 29, 2022
Metrinome is an all-purpose tool for working with code complexity metrics.

Overview Metrinome is an all-purpose tool for working with code complexity metrics. It can be used as both a REPL and API, and includes: Converters to

26 Dec 26, 2022
pycallgraph is a Python module that creates call graphs for Python programs.

Project Abandoned Many apologies. I've stopped maintaining this project due to personal time constraints. Blog post with more information. I'm happy t

gak 1.7k Jan 01, 2023
Data parsing and validation using Python type hints

pydantic Data validation and settings management using Python type hinting. Fast and extensible, pydantic plays nicely with your linters/IDE/brain. De

Samuel Colvin 12.1k Jan 05, 2023
A static analysis tool for Python

pyanalyze Pyanalyze is a tool for programmatically detecting common mistakes in Python code, such as references to undefined variables and some catego

Quora 212 Jan 07, 2023
A simple stopwatch for measuring code performance with static typing.

A simple stopwatch for measuring code performance. This is a fork from python-stopwatch, which adds static typing and a few other things.

Rafael 2 Feb 18, 2022
Turn your Python and Javascript code into DOT flowcharts

Notes from 2017 This is an older project which I am no longer working on. It was built before ES6 existed and before Python 3 had much usage. While it

Scott Rogowski 3k Jan 09, 2023
coala provides a unified command-line interface for linting and fixing all your code, regardless of the programming languages you use.

"Always code as if the guy who ends up maintaining your code will be a violent psychopath who knows where you live." ― John F. Woods coala provides a

coala development group 3.4k Jan 02, 2023
Auto-generate PEP-484 annotations

PyAnnotate: Auto-generate PEP-484 annotations Insert annotations into your source code based on call arguments and return types observed at runtime. F

Dropbox 1.4k Dec 26, 2022
Learning source code review, spot vulnerability, find some ways how to fix it.

Learn Source Code Review Learning source code review, spot vulnerability, find some ways how to fix it. WordPress Plugin Authenticated Stored XSS on C

Shan 24 Dec 31, 2022
Checkov is a static code analysis tool for infrastructure-as-code.

Checkov - Prevent cloud misconfigurations during build-time for Terraform, Cloudformation, Kubernetes, Serverless framework and other infrastructure-as-code-languages with Checkov by Bridgecrew.

Bridgecrew 5.1k Jan 03, 2023
A bytecode vm written in python.

CHex A bytecode vm written in python. hex command meaning note: the first two hex values of a CHex program are the magic number 0x01 (offset in memory

1 Aug 26, 2022
fixup: Automatically add and remove python import statements

fixup: Automatically add and remove python import statements The goal is that running fixup my_file.py will automatically add or remove import stateme

2 May 08, 2022
Guesslang detects the programming language of a given source code

Detect the programming language of a source code

Y. SOMDA 618 Dec 29, 2022
The uncompromising Python code formatter

The Uncompromising Code Formatter “Any color you like.” Black is the uncompromising Python code formatter. By using it, you agree to cede control over

Python Software Foundation 30.7k Dec 28, 2022
Run-time type checker for Python

This library provides run-time type checking for functions defined with PEP 484 argument (and return) type annotations. Four principal ways to do type

Alex Grönholm 1.1k Dec 19, 2022
An analysis tool for Python that blurs the line between testing and type systems.

CrossHair An analysis tool for Python that blurs the line between testing and type systems. THE LATEST NEWS: Check out the new crosshair cover command

Phillip Schanely 836 Jan 08, 2023