To add a simple unit test for a new feature you developed, open or create a
test-data/unit/check-*.test
file with a name that roughly relates to the
feature you added.
Add the test in this format anywhere in the file:
[case testNewSyntaxBasics]
# flags: --python-version 3.6
x: int
x = 5
y: int = 5
a: str
a = 5 # E: Incompatible types in assignment (expression has type "int", variable has type "str")
b: str = 5 # E: Incompatible types in assignment (expression has type "int", variable has type "str")
zzz: int
zzz: str # E: Name 'zzz' already defined
- no code here is executed, just type checked
- optional
# flags:
indicates which flags to use for this unit test # E: abc...
indicates that this line should result in type check error with text "abc..."- note a space after
E:
andflags:
# E:12
adds column number to the expected error- repeating
# E:
several times in one line indicates multiple expected errors in one line W: ...
andN: ...
works exactly likeE:
, but report a warning and a note respectively- lines that don't contain the above should cause no type check errors
- optional
[builtins fixtures/...]
tells the type checker to use stubs from the indicated file (see Fixtures section below) - optional
[out]
is an alternative to the "# E:" notation: it indicates that any text after it contains the expected type checking error messages. Usually, "E: " is preferred because it makes it easier to associate the errors with the code generating them at a glance, and to change the code of the test without having to change line numbers in[out]
- an empty
[out]
section has no effect - to run just this test, use
pytest -n0 -k testNewSyntaxBasics
The unit tests use minimal stubs for builtins, so a lot of operations are not
possible. You should generally define any needed classes within the test case
instead of relying on builtins, though clearly this is not always an option
(see below for more about stubs in test cases). This way tests run much
faster and don't break if the stubs change. If your test crashes mysteriously
even though the code works when run manually, you should make sure you have
all the stubs you need for your test case, including built-in classes such as
list
or dict
, as these are not included by default.
Where the stubs for builtins come from for a given test:
-
The builtins used by default in unit tests live in
test-data/unit/lib-stub
. -
Individual test cases can override the builtins stubs by using
[builtins fixtures/foo.pyi]
; this targets files intest-data/unit/fixtures
. Feel free to modify existing files there or create new ones as you deem fit. -
Test cases can also use
[typing fixtures/typing-full.pyi]
to use a more complete stub fortyping
that contains the async types, among other things. -
Feel free to add additional stubs to that
fixtures
directory, but generally don't expand files inlib-stub
without first discussing the addition with other mypy developers, as additions could slow down the test suite.
First install any additional dependencies needed for testing:
$ python3 -m pip install -U -r test-requirements.txt
You must also have a Python 2.7 binary installed that can import the typing
module:
$ python2 -m pip install -U typing
The unit test suites are driven by the pytest
framework. To run all tests,
run pytest
in the mypy repository:
$ pytest
Note that some tests will be disabled for older python versions.
This will run all tests, including integration and regression tests, and will type check mypy and verify that all stubs are valid. This may take several minutes to run, so you don't want to use this all the time while doing development.
Test suites for individual components are in the files mypy/test/test*.py
.
You can run tests from a specific module directly, a specific suite within a module, or a test in a suite (even if it's data-driven):
$ pytest mypy/test/testdiff.py
$ pytest mypy/test/testsemanal.py::SemAnalTypeInfoSuite
$ pytest -n0 mypy/test/testargs.py::ArgSuite::test_coherence
$ pytest -n0 mypy/test/testcheck.py::TypeCheckSuite::testCallingVariableWithFunctionType
To control which tests are run and how, you can use the -k
switch:
$ pytest -k "MethodCall"
You can also run the type checker for manual testing without installing it by setting up the Python module search path suitably:
$ export PYTHONPATH=$PWD
$ python3 -m mypy PROGRAM.py
You will have to manually install the typing
module if you're running Python
3.4 or earlier.
You can also execute mypy as a module
$ python3 -m mypy PROGRAM.py
You can check a module or string instead of a file:
$ python3 -m mypy PROGRAM.py
$ python3 -m mypy -m MODULE
$ python3 -m mypy -c 'import MODULE'
To run mypy on itself:
$ python3 -m mypy --config-file mypy_self_check.ini -p mypy
To run the linter:
$ flake8
Many test suites store test case descriptions in text files
(test-data/unit/*.test
). The module mypy.test.data
parses these
descriptions.
Python evaluation test cases are a little different from unit tests
(mypy/test/testpythoneval.py
, test-data/unit/pythoneval.test
). These
type check programs and run them. Unlike the unit tests, these use the
full builtins and library stubs instead of minimal ones. Run them using
pytest -k testpythoneval
.
pytest
determines the number of processes to use. The default (set in
./pytest.ini
) is the number of logical cores; this can be overridden using
-n
option. To run a single process, use pytest -n0
.
Note that running more processes than logical cores is likely to significantly decrease performance.
You can use interactive debuggers like pdb
to debug failing tests. You
need to pass the -n0
option to disable parallelization:
$ pytest -n0 --pdb -k MethodCall
You can also write import pdb; pdb.set_trace()
in code to enter the
debugger.
The --mypy-verbose
flag can be used to enable additional debug output from
most tests (as if --verbose
had been passed to mypy):
$ pytest -n0 --mypy-verbose -k MethodCall
There is an experimental feature to generate coverage reports. To use
this feature, you need to pip install -U lxml
. This is an extension
module and requires various library headers to install; on a
Debian-derived system the command
apt-get install python3-dev libxml2-dev libxslt1-dev
may provide the necessary dependencies.
To use the feature, pass e.g. --txt-report "$(mktemp -d)"
.