A static type analyzer for Python code

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Typing FAQ
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pytype - πŸ¦†βœ”

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

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"]
         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.


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 pyproject.toml file in the directory immediately above the package, replacing package_name with the package name:

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 GitHub Actions.

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


You need a Python 3.8-3.11 interpreter to run pytype, as well as an interpreter in $PATH for the Python version of the code you’re analyzing (supported: 3.8-3.11).

Platform support:

* On Alpine Linux, installation may fail due to issues with upstream dependencies. See the details of this issue for a possible fix.
** If the ninja dependency fails to install, make sure cmake is installed. See this issue for details.


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

positional arguments:
  input                 file or directory to process

Common options:

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 can be a TOML-style file with a [tool.pytype] section (preferred) or 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 pyproject.toml or setup.cfg file found by walking upwards from the current working directory.

Start off by generating a sample config file:

$ pytype --generate-config pytype.toml

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:

β”œβ”€β”€ repo1
β”‚   └── foo
β”‚       β”œβ”€β”€
β”‚       └──
└── repo2
    └── bar

Here is the filled-in config file, which instructs pytype to type-check ~/repo1/foo as Python 3.9 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.toml

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


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

# Python version (major.minor) of the target code.
python_version = '3.9'

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

# Space-separated list of error names to ignore.
disable = [

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

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

Unresolved dependencies:


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

2023 Roadmap


Apache 2.0


This is not an official Google product.