zulip/docs/contributing/mypy.md

Python static type checker (mypy)

mypy is a compile-time static type checker for Python, allowing optional, gradual typing of Python code. Zulip was fully annotated with mypy's Python 2 syntax in 2016, before our migration to Python 3 in late 2017.

As a result, Zulip is in the process of migrating from using mypy's Python 2 compatible syntax for type annotations (in which type annotations are written inside comments that start with # type: ) to the Python 3 syntax. Here's a brief example of the mypy syntax we're using in Zulip:

user_dict = {} # type: Dict[str, UserProfile]

def get_user(email: str, realm: Realm) -> UserProfile:
    ... # Actual code of the function here

You can learn more about it at:

• The mypy cheat sheet for Python 3 is the best resource for quickly understanding how to write the PEP 484 type annotations used by mypy correctly.

• The Python type annotation spec in PEP 484

The mypy type checker is run automatically as part of Zulip's Travis CI testing process in the backend build.

You can learn a lot more about mypy from our blog post on being an early adopted of mypy back in 2016:

https://blog.zulip.org/2016/10/13/static-types-in-python-oh-mypy/

mypy stubs for third-party modules.

For the Python standard library and some popular third-party modules, the typeshed project has stubs, basically the equivalent of C header files defining the types used in these Python APIs.

For other third-party modules that we call from Zulip, one either needs to add an ignore_missing_imports entry in mypy.ini in the root of the project, letting mypy know that it's third-party code, or add type stubs to the stubs/ directory, which has type stubs that mypy can use to type-check calls into that third-party module.

It's easy to add new stubs! Just read the docs, look at some of existing examples to see how they work, and remember to remove the ignore_missing_imports entry in mypy.ini when you add them.

For any third-party modules that don't have stubs, mypy treats everything in the third-party module as an Any, which is the right model (one certainly wouldn't want to need stubs for everything just to use mypy!), but means the code can't be fully type-checked.

type_debug.py

zerver/lib/type_debug.py has a useful decorator print_types. It prints the types of the parameters of the decorated function and the return type whenever that function is called. This can help find out what parameter types a function is supposed to accept, or if parameters with the wrong types are being passed to a function.

Here is an example using the interactive console:

>>> from zerver.lib.type_debug import print_types
>>>
>>> @print_types
... def func(x, y):
...     return x + y
...
>>> func(1.0, 2)
func(float, int) -> float
3.0
>>> func('a', 'b')
func(str, str) -> str
'ab'
>>> func((1, 2), (3,))
func((int, int), (int,)) -> (int, int, int)
(1, 2, 3)
>>> func([1, 2, 3], [4, 5, 6, 7])
func([int, ...], [int, ...]) -> [int, ...]
[1, 2, 3, 4, 5, 6, 7]

print_all prints the type of the first item of lists. So [int, ...] represents a list whose first element's type is int. Types of all items are not printed because a list can have many elements, which would make the output too large.

Similarly in dicts, one key's type and the corresponding value's type are printed. So {1: 'a', 2: 'b', 3: 'c'} will be printed as {int: str, ...}.

Installing mypy

If you installed Zulip's development environment correctly, mypy should already be installed inside the Python 3 virtualenv at zulip-py3-venv (mypy only supports Python 3).

If you'd like to install just the version of mypy that we're using (useful if e.g. you want mypy installed on your laptop outside the Vagrant guest), you can do that with pip install -r requirements/mypy.txt.

Running mypy on Zulip's code locally

To run mypy on Zulip's python code, you can run the command:

tools/run-mypy

You can also run mypy as a long-running daemon (server) process and send type-checking requests to the server via the command:

tools/run-mypy -d

While the mypy daemon is experimental and currently supports macOS and Linux only, we strongly recommend using the daemon if it is an option. Program state from previous runs will be cached in memory and will not have to be read from the file system on each run. For a large codebase like Zulip's and a workflow involving running mypy repeatedly after small edits, using the daemon can be 10 or more times faster.

Mypy will output errors in the same style as a compiler would. For example, if your code has a type error like this:

foo = 1
foo = '1'

you'll get an error like this:

test.py: note: In function "test":
test.py:200: error: Incompatible types in assignment (expression has type "str", variable has type "int")

Mypy is there to find bugs in Zulip before they impact users

For the purposes of Zulip development, you can treat mypy like a much more powerful linter that can catch a wide range of bugs. If, after running tools/run-mypy on your Zulip branch, you get mypy errors, it's important to get to the bottom of the issue, not just do something quick to silence the warnings. Possible explanations include:

• A bug in any new type annotations you added.
• A bug in the existing type annotations.
• A bug in Zulip!
• Some Zulip code is correct but confusingly reuses variables with different types.
• A bug in mypy (though this is increasingly rare as mypy is now fairly mature as a project).

Each explanation has its own solution, but in every case the result should be solving the mypy warning in a way that makes the Zulip codebase better. If you need help understanding an issue, please feel free to mention @sharmaeklavya2 or @timabbott on the relevant pull request or issue on GitHub.

If you think you have found a bug in Zulip or mypy, inform the zulip developers by opening an issue on Zulip's GitHub repository or posting on zulip-devel. If it's indeed a mypy bug, we can help with reporting it upstream.