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Various small documentation updates (#11817)
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Improve consistency, grammar, formatting and clarity in the documentation. Also
some minor content fixes.
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@JukkaL
JukkaL committed Dec 22, 2021
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22 changes: 14 additions & 8 deletions docs/source/class_basics.rst
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Expand Up @@ -320,8 +320,8 @@ Slots
*****

When a class has explicitly defined
`__slots__ <https://docs.python.org/3/reference/datamodel.html#slots>`_
mypy will check that all attributes assigned to are members of `__slots__`.
`__slots__ <https://docs.python.org/3/reference/datamodel.html#slots>`_,
mypy will check that all attributes assigned to are members of ``__slots__``:

.. code-block:: python
Expand All @@ -331,13 +331,19 @@ mypy will check that all attributes assigned to are members of `__slots__`.
def __init__(self, name: str, year: int) -> None:
self.name = name
self.year = year
self.released = True # E: Trying to assign name "released" that is not in "__slots__" of type "Album"
# Error: Trying to assign name "released" that is not in "__slots__" of type "Album"
self.released = True
my_album = Album('Songs about Python', 2021)
Mypy will only check attribute assignments against `__slots__` when the following conditions hold:
Mypy will only check attribute assignments against ``__slots__`` when
the following conditions hold:

1. All base classes (except builtin ones) must have explicit ``__slots__`` defined (mirrors CPython's behaviour)
2. ``__slots__`` does not include ``__dict__``, since if ``__slots__`` includes ``__dict__``
it allows setting any attribute, similar to when ``__slots__`` is not defined (mirrors CPython's behaviour)
3. All values in ``__slots__`` must be statically known. For example, no variables: only string literals.
1. All base classes (except builtin ones) must have explicit
``__slots__`` defined (this mirrors Python semantics).

2. ``__slots__`` does not include ``__dict__``. If ``__slots__``
includes ``__dict__``, arbitrary attributes can be set, similar to
when ``__slots__`` is not defined (this mirrors Python semantics).

3. All values in ``__slots__`` must be string literals.
4 changes: 2 additions & 2 deletions docs/source/command_line.rst
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Expand Up @@ -312,8 +312,8 @@ The following options are available:
.. option:: --disallow-any-generics

This flag disallows usage of generic types that do not specify explicit
type parameters. For example you can't use a bare ``x: list``, you must say
``x: list[int]``.
type parameters. For example, you can't use a bare ``x: list``. Instead, you
must always write something like ``x: list[int]``.

.. option:: --disallow-subclassing-any

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204 changes: 107 additions & 97 deletions docs/source/common_issues.rst
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Expand Up @@ -26,102 +26,102 @@ No errors reported for obviously wrong code
There are several common reasons why obviously wrong code is not
flagged as an error.

- **The function containing the error is not annotated.** Functions that
do not have any annotations (neither for any argument nor for the
return type) are not type-checked, and even the most blatant type
errors (e.g. ``2 + 'a'``) pass silently. The solution is to add
annotations. Where that isn't possible, functions without annotations
can be checked using :option:`--check-untyped-defs <mypy --check-untyped-defs>`.
**The function containing the error is not annotated.** Functions that
do not have any annotations (neither for any argument nor for the
return type) are not type-checked, and even the most blatant type
errors (e.g. ``2 + 'a'``) pass silently. The solution is to add
annotations. Where that isn't possible, functions without annotations
can be checked using :option:`--check-untyped-defs <mypy --check-untyped-defs>`.

Example:
Example:

.. code-block:: python
.. code-block:: python
def foo(a):
return '(' + a.split() + ')' # No error!
def foo(a):
return '(' + a.split() + ')' # No error!
This gives no error even though ``a.split()`` is "obviously" a list
(the author probably meant ``a.strip()``). The error is reported
once you add annotations:
This gives no error even though ``a.split()`` is "obviously" a list
(the author probably meant ``a.strip()``). The error is reported
once you add annotations:

.. code-block:: python
.. code-block:: python
def foo(a: str) -> str:
return '(' + a.split() + ')'
# error: Unsupported operand types for + ("str" and List[str])
def foo(a: str) -> str:
return '(' + a.split() + ')'
# error: Unsupported operand types for + ("str" and List[str])
If you don't know what types to add, you can use ``Any``, but beware:
If you don't know what types to add, you can use ``Any``, but beware:

- **One of the values involved has type 'Any'.** Extending the above
example, if we were to leave out the annotation for ``a``, we'd get
no error:
**One of the values involved has type 'Any'.** Extending the above
example, if we were to leave out the annotation for ``a``, we'd get
no error:

.. code-block:: python
.. code-block:: python
def foo(a) -> str:
return '(' + a.split() + ')' # No error!
def foo(a) -> str:
return '(' + a.split() + ')' # No error!
The reason is that if the type of ``a`` is unknown, the type of
``a.split()`` is also unknown, so it is inferred as having type
``Any``, and it is no error to add a string to an ``Any``.
The reason is that if the type of ``a`` is unknown, the type of
``a.split()`` is also unknown, so it is inferred as having type
``Any``, and it is no error to add a string to an ``Any``.

If you're having trouble debugging such situations,
:ref:`reveal_type() <reveal-type>` might come in handy.
If you're having trouble debugging such situations,
:ref:`reveal_type() <reveal-type>` might come in handy.

Note that sometimes library stubs have imprecise type information,
e.g. the :py:func:`pow` builtin returns ``Any`` (see `typeshed issue 285
<https://github.com/python/typeshed/issues/285>`_ for the reason).
Note that sometimes library stubs have imprecise type information,
e.g. the :py:func:`pow` builtin returns ``Any`` (see `typeshed issue 285
<https://github.com/python/typeshed/issues/285>`_ for the reason).

- :py:meth:`__init__ <object.__init__>` **method has no annotated
arguments or return type annotation.** :py:meth:`__init__ <object.__init__>`
is considered fully-annotated **if at least one argument is annotated**,
while mypy will infer the return type as ``None``.
The implication is that, for a :py:meth:`__init__ <object.__init__>` method
that has no argument, you'll have to explicitly annotate the return type
as ``None`` to type-check this :py:meth:`__init__ <object.__init__>` method:
:py:meth:`__init__ <object.__init__>` **method has no annotated
arguments or return type annotation.** :py:meth:`__init__ <object.__init__>`
is considered fully-annotated **if at least one argument is annotated**,
while mypy will infer the return type as ``None``.
The implication is that, for a :py:meth:`__init__ <object.__init__>` method
that has no argument, you'll have to explicitly annotate the return type
as ``None`` to type-check this :py:meth:`__init__ <object.__init__>` method:

.. code-block:: python
.. code-block:: python
def foo(s: str) -> str:
return s
class A():
def __init__(self, value: str): # Return type inferred as None, considered as typed method
self.value = value
foo(1) # error: Argument 1 to "foo" has incompatible type "int"; expected "str"
class B():
def __init__(self): # No argument is annotated, considered as untyped method
foo(1) # No error!
class C():
def __init__(self) -> None: # Must specify return type to type-check
foo(1) # error: Argument 1 to "foo" has incompatible type "int"; expected "str"
- **Some imports may be silently ignored**. Another source of
unexpected ``Any`` values are the :option:`--ignore-missing-imports
<mypy --ignore-missing-imports>` and :option:`--follow-imports=skip
<mypy --follow-imports>` flags. When you use :option:`--ignore-missing-imports <mypy --ignore-missing-imports>`,
any imported module that cannot be found is silently replaced with
``Any``. When using :option:`--follow-imports=skip <mypy --follow-imports>` the same is true for
modules for which a ``.py`` file is found but that are not specified
on the command line. (If a ``.pyi`` stub is found it is always
processed normally, regardless of the value of
:option:`--follow-imports <mypy --follow-imports>`.) To help debug the former situation (no
module found at all) leave out :option:`--ignore-missing-imports <mypy --ignore-missing-imports>`; to get
clarity about the latter use :option:`--follow-imports=error <mypy --follow-imports>`. You can
read up about these and other useful flags in :ref:`command-line`.

- **A function annotated as returning a non-optional type returns 'None'
and mypy doesn't complain**.
def foo(s: str) -> str:
return s
class A():
def __init__(self, value: str): # Return type inferred as None, considered as typed method
self.value = value
foo(1) # error: Argument 1 to "foo" has incompatible type "int"; expected "str"
class B():
def __init__(self): # No argument is annotated, considered as untyped method
foo(1) # No error!
class C():
def __init__(self) -> None: # Must specify return type to type-check
foo(1) # error: Argument 1 to "foo" has incompatible type "int"; expected "str"
**Some imports may be silently ignored**. Another source of
unexpected ``Any`` values are the :option:`--ignore-missing-imports
<mypy --ignore-missing-imports>` and :option:`--follow-imports=skip
<mypy --follow-imports>` flags. When you use :option:`--ignore-missing-imports <mypy --ignore-missing-imports>`,
any imported module that cannot be found is silently replaced with
``Any``. When using :option:`--follow-imports=skip <mypy --follow-imports>` the same is true for
modules for which a ``.py`` file is found but that are not specified
on the command line. (If a ``.pyi`` stub is found it is always
processed normally, regardless of the value of
:option:`--follow-imports <mypy --follow-imports>`.) To help debug the former situation (no
module found at all) leave out :option:`--ignore-missing-imports <mypy --ignore-missing-imports>`; to get
clarity about the latter use :option:`--follow-imports=error <mypy --follow-imports>`. You can
read up about these and other useful flags in :ref:`command-line`.

**A function annotated as returning a non-optional type returns 'None'
and mypy doesn't complain**.

.. code-block:: python
.. code-block:: python
def foo() -> str:
return None # No error!
def foo() -> str:
return None # No error!
You may have disabled strict optional checking (see
:ref:`no_strict_optional` for more).
You may have disabled strict optional checking (see
:ref:`no_strict_optional` for more).

.. _silencing_checker:

Expand Down Expand Up @@ -383,10 +383,10 @@ explicit type cast:
if index < 0:
raise ValueError('No str found')
found = a[index] # Has `object` type, despite the fact that we know it is `str`
return cast(str, found) # So, we need an explicit cast to make mypy happy
found = a[index] # Has type "object", despite the fact that we know it is "str"
return cast(str, found) # We need an explicit cast to make mypy happy
Alternatively, you can use ``assert`` statement together with some
Alternatively, you can use an ``assert`` statement together with some
of the supported type inference techniques:

.. code-block:: python
Expand All @@ -396,9 +396,9 @@ of the supported type inference techniques:
if index < 0:
raise ValueError('No str found')
found = a[index] # Has `object` type, despite the fact that we know it is `str`
assert isinstance(found, str) # Now, `found` will be narrowed to `str` subtype
return found # No need for the explicit `cast()` anymore
found = a[index] # Has type "object", despite the fact that we know it is "str"
assert isinstance(found, str) # Now, "found" will be narrowed to "str"
return found # No need for the explicit "cast()" anymore
.. note::

Expand All @@ -411,7 +411,7 @@ of the supported type inference techniques:

.. note::

You can read more about type narrowing techniques here.
You can read more about type narrowing techniques :ref:`here <type-narrowing>`.

Type inference in Mypy is designed to work well in common cases, to be
predictable and to let the type checker give useful error
Expand Down Expand Up @@ -634,32 +634,41 @@ You can install the latest development version of mypy from source. Clone the
Variables vs type aliases
-------------------------

Mypy has both type aliases and variables with types like ``Type[...]`` and it is important to know their difference.
Mypy has both *type aliases* and variables with types like ``Type[...]``. These are
subtly different, and it's important to understand how they differ to avoid pitfalls.

1. Variables with type ``Type[...]`` should be created by assignments with an explicit type annotations:
1. A variable with type ``Type[...]`` is defined using an assignment with an
explicit type annotation:

.. code-block:: python
class A: ...
tp: Type[A] = A
2. Aliases are created by assignments without an explicit type.
2. You can define a type alias using an assignment without an explicit type annotation
at the top level of a module:

.. code-block:: python
class A: ...
Alias = A
Or you can also use :pep:`613` and explicit type aliases:
You can also use ``TypeAlias`` (:pep:`613`) to define an *explicit type alias*:

.. code-block:: python
from typing import TypeAlias # or `from typing_extensions` before `python3.10`
from typing import TypeAlias # "from typing_extensions" in Python 3.9 and earlier
class A: ...
Alias: TypeAlias = A
3. The difference is that aliases are completely known statically and can be used in type context (annotations):
You should always use ``TypeAlias`` to define a type alias in a class body or
inside a function.

The main difference is that the target of an alias is precisely known statically, and this
means that they can be used in type annotations and other *type contexts*. Type aliases
can't be defined conditionally (unless using
:ref:`supported Python version and platform checks <version_and_platform_checks>`):

.. code-block:: python
Expand All @@ -669,17 +678,18 @@ Mypy has both type aliases and variables with types like ``Type[...]`` and it is
if random() > 0.5:
Alias = A
else:
Alias = B # error: Cannot assign multiple types to name "Alias" without an explicit "Type[...]" annotation \
# error: Incompatible types in assignment (expression has type "Type[B]", variable has type "Type[A]")
# error: Cannot assign multiple types to name "Alias" without an
# explicit "Type[...]" annotation
Alias = B
tp: Type[object] # tp is a type variable
tp: Type[object] # "tp" is a variable with a type object value
if random() > 0.5:
tp = A
else:
tp = B # This is OK
def fun1(x: Alias) -> None: ... # This is OK
def fun2(x: tp) -> None: ... # error: Variable "__main__.tp" is not valid as a type
def fun1(x: Alias) -> None: ... # OK
def fun2(x: tp) -> None: ... # Error: "tp" is not valid as a type
Incompatible overrides
----------------------
Expand Down

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