The mypy command line

This section documents many of mypy’s command line flags. A quick summary of command line flags can always be printed using the -h flag (or its long form --help):

$ mypy -h
usage: mypy [-h] [-v] [-V] [--python-version x.y] [--platform PLATFORM] [-2]
            [--follow-imports {normal,silent,skip,error}]
            [--disallow-untyped-calls] [--disallow-untyped-defs]
            [--check-untyped-defs] [--disallow-subclassing-any]
            [--warn-incomplete-stub] [--warn-redundant-casts]
            [--no-warn-no-return] [--warn-return-any] [--warn-unused-ignores]
            [--show-error-context] [--no-implicit-optional] [-i]
            [--quick-and-dirty] [--cache-dir DIR] [--skip-version-check]
            [--strict-optional-whitelist [GLOB [GLOB ...]]]
            [--junit-xml JUNIT_XML] [--pdb] [--show-traceback] [--stats]
            [--inferstats] [--custom-typing MODULE]
            [--custom-typeshed-dir DIR] [--scripts-are-modules]
            [--config-file CONFIG_FILE] [--show-column-numbers]
            [--find-occurrences CLASS.MEMBER] [--strict]
            [--shadow-file SOURCE_FILE SHADOW_FILE] [--any-exprs-report DIR]
            [--cobertura-xml-report DIR] [--html-report DIR]
            [--linecount-report DIR] [--linecoverage-report DIR]
            [--memory-xml-report DIR]
            [--txt-report DIR] [--xml-report DIR] [--xslt-html-report DIR]
            [--xslt-txt-report DIR] [-m MODULE] [-c PROGRAM_TEXT] [-p PACKAGE]
            [files [files ...]]

(etc., too long to show everything here)

Specifying files and directories to be checked

You’ve already seen mypy as a way to type check the file More generally you can pass any number of files and directories on the command line and they will all be type checked together.

  • Files ending in .py (and stub files ending in .pyi) are checked as Python modules.
  • Files not ending in .py or .pyi are assumed to be Python scripts and checked as such.
  • Directories representing Python packages (i.e. containing a[i] file) are checked as Python packages; all submodules and subpackages will be checked (subpackages must themselves have a[i] file).
  • Directories that don’t represent Python packages (i.e. not directly containing an[i] file) are checked as follows:
    • All *.py[i] files contained directly therein are checked as toplevel Python modules;
    • All packages contained directly therein (i.e. immediate subdirectories with an[i] file) are checked as toplevel Python packages.

One more thing about checking modules and packages: if the directory containing a module or package specified on the command line has an[i] file, mypy assigns these an absolute module name by crawling up the path until no[i] file is found. For example, suppose we run the command mypy foo/bar/ where foo/bar/ exists but foo/ does not. Then the module name assumed is bar.baz and the directory foo is added to mypy’s module search path. On the other hand, if foo/bar/ did not exist, foo/bar would be added to the module search path instead, and the module name assumed is just baz.

If a script (a file not ending in .py[i]) is processed, the module name assumed is always __main__ (matching the behavior of the Python interpreter).

Other ways of specifying code to be checked

The flag -m (long form: --module) lets you specify a module name to be found using the default module search path. The module name may contain dots. For example:

$ mypy -m html.parser

will type check the module html.parser (this happens to be a library stub).

The flag -p (long form: --package) is similar to -m but you give it a package name and it will type check all submodules and subpackages (recursively) of that package. (If you pass a package name to -m it will just type check the package’s and anything imported from there.) For example:

$ mypy -p html

will type check the entire html package (of library stubs).

Finally the flag -c (long form: --command) will take a string from the command line and type check it as a small program. For example:

$ mypy -c 'x = [1, 2]; print(x())'

will type check that little program (and complain that List[int] is not callable).

Reading a list of files from a file

Finally, any command-line argument starting with @ reads additional command-line arguments from the file following the @ character. This is primarily useful if you have a file containing a list of files that you want to be type-checked: instead of using shell syntax like:

mypy $(cat file_of_files)

you can use this instead:

mypy @file_of_files

Such a file can also contain other flags, but a preferred way of reading flags (not files) from a file is to use a configuration file.

How imports are found

When mypy encounters an import statement it tries to find the module on the file system, similar to the way Python finds it. However, there are some differences.

First, mypy has its own search path. This is computed from the following items:

  • The MYPYPATH environment variable (a colon-separated list of directories).
  • The directories containing the sources given on the command line (see below).
  • The relevant directories of the typeshed repo.

For sources given on the command line, the path is adjusted by crawling up from the given file or package to the nearest directory that does not contain an or __init__.pyi file.

Second, mypy searches for stub files in addition to regular Python files and packages. The rules for searching a module foo are as follows:

  • The search looks in each of the directories in the search path (see above) until a match is found.
  • If a package named foo is found (i.e. a directory foo containing an or __init__.pyi file) that’s a match.
  • If a stub file named foo.pyi is found, that’s a match.
  • If a Python module named is found, that’s a match.

These matches are tried in order, so that if multiple matches are found in the same directory on the search path (e.g. a package and a Python file, or a stub file and a Python file) the first one in the above list wins.

In particular, if a Python file and a stub file are both present in the same directory on the search path, only the stub file is used. (However, if the files are in different directories, the one found in the earlier directory is used.)

NOTE: These rules are relevant to the following section too: the --follow-imports flag described below is applied after the above algorithm has determined which package, stub or module to use.

Following imports or not?

When you’re first attacking a large existing codebase with mypy, you may only want to check selected files. For example, you may only want to check those files to which you have already added annotations. This is easily accomplished using a shell pipeline like this:

mypy $(find . -name \*.py | xargs grep -l '# type:')

(While there are many improvements possible to make this example more robust, this is not the place for a tutorial in shell programming.)

However, by default mypy doggedly tries to follow imports. This may cause several types of problems that you may want to silence during your initial conquest:

  • Your code may import library modules for which no stub files exist yet. This can cause a lot of errors like the following: error: No library stub file for standard library module 'antigravity' error: No library stub file for module 'flask' error: Cannot find module named 'sir_not_appearing_in_this_film'

    If you see only a few of these you may be able to silence them by putting # type: ignore on the respective import statements, but it’s usually easier to silence all such errors by using –ignore-missing-imports.

  • Your project’s directory structure may hinder mypy in finding certain modules that are part of your project, e.g. modules hidden away in a subdirectory that’s not a package. You can usually deal with this by setting the MYPYPATH variable (see How imports are found).

  • When following imports mypy may find a module that’s part of your project but which you haven’t annotated yet, mypy may report errors for the top level code in that module (where the top level includes class bodies and function/method default values). Here the --follow-imports flag comes in handy.

The --follow-imports flag takes a mandatory string value that can take one of four values. It only applies to modules for which a .py file is found (but no corresponding .pyi stub file) and that are not given on the command line. Passing a package or directory on the command line implies all modules in that package or directory. The four possible values are:

  • normal (the default) follow imports normally and type check all top level code (as well as the bodies of all functions and methods with at least one type annotation in the signature).

  • silent follow imports normally and even “type check” them normally, but suppress any error messages. This is typically the best option for a new codebase.

  • skip don’t follow imports, silently replacing the module (and everything imported from it) with an object of type Any. (This option used to be known as --silent-imports and while it is very powerful it can also cause hard-to-debug errors, hence the recommendation of using silent instead.)

  • error the same behavior as skip but not quite as silent – it flags the import as an error, like this: note: Import of 'submodule' ignored note: (Using --follow-imports=error, module not passed on command line)

Disallow Any Flags

The --disallow-any family of flags disallows various types of Any in a module. The following options are available:

  • --disallow-any-unimported disallows usage of types that come from unfollowed imports (such types become aliases for Any). Unfollowed imports occur either when the imported module does not exist or when --follow-imports=skip is set.
  • --disallow-any-expr disallows all expressions in the module that have type Any. If an expression of type Any appears anywhere in the module mypy will output an error unless the expression is immediately used as an argument to cast or assigned to a variable with an explicit type annotation. In addition, declaring a variable of type Any or casting to type Any is not allowed. Note that calling functions that take parameters of type Any is still allowed.
  • --disallow-any-decorated disallows functions that have Any in their signature after decorator transformation.
  • --disallow-any-explicit disallows explicit Any in type positions such as type annotations and generic type parameters.
  • --disallow-any-generics disallows usage of generic types that do not specify explicit type parameters. Moreover, built-in collections (such as list and dict) become disallowed as you should use their aliases from the typing module (such as List[int] and Dict[str, str]).

Additional command line flags

Here are some more useful flags:

  • --ignore-missing-imports suppresses error messages about imports that cannot be resolved (see Following imports or not? for some examples).
  • --strict-optional enables experimental strict checking of Optional[...] types and None values. Without this option, mypy doesn’t generally check the use of None values – they are valid everywhere. See Experimental strict optional type and None checking for more about this feature.
  • --strict-optional-whitelist attempts to suppress strict Optional-related errors in non-whitelisted files. Takes an arbitrary number of globs as the whitelist. This option is intended to be used to incrementally roll out --strict-optional to a large codebase that already has mypy annotations. However, this flag comes with some significant caveats. It does not suppress all errors caused by turning on --strict-optional, only most of them, so there may still be a bit of upfront work to be done before it can be used in CI. It will also suppress some errors that would be caught in a non-strict-Optional run. Therefore, when using this flag, you should also re-check your code without --strict-optional to ensure new type errors are not introduced.
  • --disallow-untyped-defs reports an error whenever it encounters a function definition without type annotations.
  • --check-untyped-defs is less severe than the previous option – it type checks the body of every function, regardless of whether it has type annotations. (By default the bodies of functions without annotations are not type checked.) It will assume all arguments have type Any and always infer Any as the return type.
  • --disallow-incomplete-defs reports an error whenever it encounters a partly annotated function definition.
  • --disallow-untyped-calls reports an error whenever a function with type annotations calls a function defined without annotations.
  • --disallow-untyped-decorators reports an error whenever a function with type annotations is decorated with a decorator without annotations.
  • --disallow-subclassing-any reports an error whenever a class subclasses a value of type Any. This may occur when the base class is imported from a module that doesn’t exist (when using –ignore-missing-imports) or is ignored due to –follow-imports=skip or a # type: ignore comment on the import statement. Since the module is silenced, the imported class is given a type of Any. By default mypy will assume that the subclass correctly inherited the base class even though that may not actually be the case. This flag makes mypy raise an error instead.
  • --incremental is an experimental option that enables a module cache. When enabled, mypy caches results from previous runs to speed up type checking. Incremental mode can help when most parts of your program haven’t changed since the previous mypy run. A companion flag is --cache-dir DIR, which specifies where the cache files are written. By default this is .mypy_cache in the current directory. While the cache is only read in incremental mode, it is written even in non-incremental mode, in order to “warm” the cache. To disable writing the cache, use --cache-dir=/dev/null (UNIX) or --cache-dir=nul (Windows). Cache files belonging to a different mypy version are ignored.
  • --quick-and-dirty is an experimental, unsafe variant of incremental mode. Quick mode is faster than regular incremental mode, because it only re-checks modules that were modified since their cache file was last written (regular incremental mode also re-checks all modules that depend on one or more modules that were re-checked). Quick mode is unsafe because it may miss problems caused by a change in a dependency. Quick mode updates the cache, but regular incremental mode ignores cache files written by quick mode.

  • --python-version X.Y will make mypy typecheck your code as if it were run under Python version X.Y. Without this option, mypy will default to using whatever version of Python is running mypy. Note that the -2 and --py2 flags are aliases for --python-version 2.7. See Python version and system platform checks for more about this feature.

  • --platform PLATFORM will make mypy typecheck your code as if it were run under the the given operating system. Without this option, mypy will default to using whatever operating system you are currently using. See Python version and system platform checks for more about this feature.

  • --show-column-numbers will add column offsets to error messages, for example, the following indicates an error in line 12, column 9 (note that column offsets are 0-based): error: Unsupported operand types for / ("int" and "str")
  • --scripts-are-modules will give command line arguments that appear to be scripts (i.e. files whose name does not end in .py) a module name derived from the script name rather than the fixed name __main__. This allows checking more than one script in a single mypy invocation. (The default __main__ is technically more correct, but if you have many scripts that import a large package, the behavior enabled by this flag is often more convenient.)

  • --custom-typeshed-dir DIR specifies the directory where mypy looks for typeshed stubs, instead of the typeshed that ships with mypy. This is primarily intended to make it easier to test typeshed changes before submitting them upstream, but also allows you to use a forked version of typeshed.

  • --config-file CONFIG_FILE causes configuration settings to be read from the given file. By default settings are read from mypy.ini or setup.cfg in the current directory. Settings override mypy’s built-in defaults and command line flags can override settings. See The mypy configuration file for the syntax of configuration files.
  • --junit-xml JUNIT_XML will make mypy generate a JUnit XML test result document with type checking results. This can make it easier to integrate mypy with continuous integration (CI) tools.
  • --find-occurrences CLASS.MEMBER will make mypy print out all usages of a class member based on static type information. This feature is experimental.
  • --cobertura-xml-report DIR causes mypy to generate a Cobertura XML type checking coverage report.
  • --warn-no-return causes mypy to generate errors for missing return statements on some execution paths. Mypy doesn’t generate these errors for functions with None or Any return types. Mypy also currently ignores functions with an empty body or a body that is just ellipsis (...), since these can be valid as abstract methods. This option is on by default.
  • --warn-return-any causes mypy to generate a warning when returning a value with type Any from a function declared with a non- Any return type.
  • --strict mode enables all optional error checking flags. You can see the list of flags enabled by strict mode in the full mypy -h output.
  • --shadow-file SOURCE_FILE SHADOW_FILE makes mypy typecheck SHADOW_FILE in place of SOURCE_FILE. Primarily intended for tooling. Allows tooling to make transformations to a file before type checking without having to change the file in-place. (For example, tooling could use this to display the type of an expression by wrapping it with a call to reveal_type in the shadow file and then parsing the output.)
  • --no-implicit-optional causes mypy to stop treating arguments with a None default value as having an implicit Optional[...] type.

For the remaining flags you can read the full mypy -h output.


Command line flags are liable to change between releases.

Integrating mypy into another Python application

It is possible to integrate mypy into another Python 3 application by importing mypy.api and calling the run function with a parameter of type List[str], containing what normally would have been the command line arguments to mypy.

Function run returns a Tuple[str, str, int], namely (<normal_report>, <error_report>, <exit_status>), in which <normal_report> is what mypy normally writes to sys.stdout, <error_report> is what mypy normally writes to sys.stderr and exit_status is the exit status mypy normally returns to the operating system.

A trivial example of using the api is the following:

import sys
from mypy import api

result =[1:])

if result[0]:
    print('\nType checking report:\n')
    print(result[0])  # stdout

if result[1]:
    print('\nError report:\n')
    print(result[1])  # stderr

print ('\nExit status:', result[2])