Pyanalyze is a semi-static type checker for Python code. Like a static type checker (e.g., mypy or pyright), it detects type errors in your code so bugs can be found before they reach production. Unlike such tools, however, it imports the modules it type checks, enabling pyanalyze to understand many dynamic constructs that other type checkers will reject. This property also makes it possible to extend pyanalyze with plugins that interact directly with your code.

You can install pyanalyze with:

$ pip install pyanalyze

Once it is installed, you can run pyanalyze on a Python file or package as follows:

$ python -m pyanalyze file.py
$ python -m pyanalyze package/

But note that this will try to import all Python files it is passed. If you have scripts that perform operations without if __name__ == "__main__": blocks, pyanalyze may end up executing them.

In order to run successfully, pyanalyze needs to be able to import the code it checks. To make this work you may have to manually adjust Python's import path using the $PYTHONPATH environment variable.

For quick experimentation, you can also use the -c option to directly type check a piece of code:

$ python -m pyanalyze -c 'import typing; typing.reveal_type(1)'
Runtime type is 'int'

Revealed type is 'Literal[1]' (code: reveal_type)
In <code> at line 1
   1: import typing; typing.reveal_type(1)
                                        ^

Pyanalyze has a number of command-line options, which you can see by running python -m pyanalyze --help. Important ones include -f, which runs an interactive prompt that lets you examine and fix each error found by pyanalyze, and --enable/--disable, which enable and disable specific error codes.

Configuration through a pyproject.toml file is also supported. See the documentation for details.

One of the main ways to extend pyanalyze is by providing a specification for a particular function. This allows you to run arbitrary code that inspects the arguments to the function and raises errors if something is wrong.

As an example, suppose your codebase contains a function database.run_query() that takes as an argument a SQL string, like this:

database.run_query("SELECT answer, question FROM content")

You want to detect when a call to run_query() contains syntactically invalid SQL or refers to a non-existent table or column. You could set that up with code like this:

from pyanalyze.error_code import ErrorCode
from pyanalyze.signature import CallContext, Signature, SigParameter
from pyanalyze.value import KnownValue, TypedValue, AnyValue, AnySource, Value

from database import run_query, parse_sql


def run_query_impl(ctx: CallContext) -> Value:
    sql = ctx.vars["sql"]
    if not isinstance(sql, KnownValue) or not isinstance(sql.val, str):
        ctx.show_error(
            "Argument to run_query() must be a string literal",
            ErrorCode.incompatible_call,
        )
        return AnyValue(AnySource.error)

    try:
        parsed = parse_sql(sql)
    except ValueError as e:
        ctx.show_error(
            f"Invalid sql passed to run_query(): {e}",
            ErrorCode.incompatible_call,
        )
        return AnyValue(AnySource.error)

    # check that the parsed SQL is valid...

    # pyanalyze will use this as the inferred return type for the function
    return TypedValue(list)


# in pyproject.toml, set:
# known_signatures = ["<module>.get_known_argspecs"]
def get_known_argspecs(arg_spec_cache):
    return {
        # This infers the parameter types and names from the function signature
        run_query: arg_spec_cache.get_argspec(
            run_query, impl=run_query_impl
        ),
        # You can also write the signature manually
        run_query: Signature.make(
            [SigParameter("sql", annotation=TypedValue(str))],
            callable=run_query,
            impl=run_query_impl,
        ),
    }

Pyanalyze generally aims to implement the Python typing spec, but support for some features is incomplete. See the documentation for details.

Sometimes pyanalyze gets things wrong and you need to ignore an error it emits. This can be done as follows:

• Add # static analysis: ignore on a line by itself before the line that generates the error.
• Add # static analysis: ignore at the end of the line that generates the error.
• Add # static analysis: ignore at the top of the file; this will ignore errors in the entire file.

You can add an error code, like # static analysis: ignore[undefined_name], to ignore only a specific error code. This does not work for whole-file ignores. If the bare_ignore error code is turned on, pyanalyze will emit an error if you don't specify an error code on an ignore comment.

Pyanalyze does not currently support the standard # type: ignore comment syntax.

Pyanalyze supports all versions of Python that have not reached end-of-life. Because it imports the code it checks, you have to run it using the same version of Python you use to run your code.

We welcome your contributions. See CONTRIBUTING.md for how to get started.

Documentation is available at ReadTheDocs or on GitHub.