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Error codes enabled by default

This section documents various errors codes that mypy can generate with default options. See :ref:`error-codes` for general documentation about error codes. :ref:`error-codes-optional` documents additional error codes that you can enable.

Check that attribute exists [attr-defined]

Mypy checks that an attribute is defined in the target class or module when using the dot operator. This applies to both getting and setting an attribute. New attributes are defined by assignments in the class body, or assignments to self.x in methods. These assignments don’t generate attr-defined errors.

This error code is also generated if an imported name is not defined in the module in a from . import statement (as long as the target module can be found):

A reference to a missing attribute is given the Any type. In the above example, the type of non_existent will be Any , which can be important if you silence the error.

Check that attribute exists in each union item [union-attr]

If you access the attribute of a value with a union type, mypy checks that the attribute is defined for every type in that union. Otherwise the operation can fail at runtime. This also applies to optional types.

You can often work around these errors by using assert isinstance(obj, ClassName) or assert obj is not None to tell mypy that you know that the type is more specific than what mypy thinks.

Check that name is defined [name-defined]

Mypy expects that all references to names have a corresponding definition in an active scope, such as an assignment, function definition or an import. This can catch missing definitions, missing imports, and typos.

This example accidentally calls sort() instead of :py:func:`sorted` :

Check arguments in calls [call-arg]

Mypy expects that the number and names of arguments match the called function. Note that argument type checks have a separate error code arg-type .

Check argument types [arg-type]

Mypy checks that argument types in a call match the declared argument types in the signature of the called function (if one exists).

Check calls to overloaded functions [call-overload]

When you call an overloaded function, mypy checks that at least one of the signatures of the overload items match the argument types in the call.

Check validity of types [valid-type]

Mypy checks that each type annotation and any expression that represents a type is a valid type. Examples of valid types include classes, union types, callable types, type aliases, and literal types. Examples of invalid types include bare integer literals, functions, variables, and modules.

This example incorrectly uses the function log as a type:

typing.Callable` as the type for callable objects:

Require annotation if variable type is unclear [var-annotated]

In some cases mypy can’t infer the type of a variable without an explicit annotation. Mypy treats this as an error. This typically happens when you initialize a variable with an empty collection or None . If mypy can’t infer the collection item type, mypy replaces any parts of the type it couldn’t infer with Any and generates an error.

Example with an error:

To address this, we add an explicit annotation:

Check validity of overrides [override]

Mypy checks that an overridden method or attribute is compatible with the base class. A method in a subclass must accept all arguments that the base class method accepts, and the return type must conform to the return type in the base class (Liskov substitution principle).

Argument types can be more general is a subclass (i.e., they can vary contravariantly). The return type can be narrowed in a subclass (i.e., it can vary covariantly). It’s okay to define additional arguments in a subclass method, as long all extra arguments have default values or can be left out ( *args , for example).

Check that function returns a value [return]

If a function has a non- None return type, mypy expects that the function always explicitly returns a value (or raises an exception). The function should not fall off the end of the function, since this is often a bug.

Check that return value is compatible [return-value]

Mypy checks that the returned value is compatible with the type signature of the function.

Check types in assignment statement [assignment]

Mypy checks that the assigned expression is compatible with the assignment target (or targets).

Check type variable values [type-var]

Mypy checks that value of a type variable is compatible with a value restriction or the upper bound type.

Check uses of various operators [operator]

Mypy checks that operands support a binary or unary operation, such as + or

. Indexing operations are so common that they have their own error code index (see below).

Check indexing operations [index]

Mypy checks that the indexed value in indexing operation such as x[y] supports indexing, and that the index expression has a valid type.

Check list items [list-item]

When constructing a list using [item, . ] , mypy checks that each item is compatible with the list type that is inferred from the surrounding context.

Check dict items [dict-item]

When constructing a dictionary using or dict(key=value, . ) , mypy checks that each key and value is compatible with the dictionary type that is inferred from the surrounding context.

Check TypedDict items [typeddict-item]

When constructing a TypedDict object, mypy checks that each key and value is compatible with the TypedDict type that is inferred from the surrounding context.

When getting a TypedDict item, mypy checks that the key exists. When assigning to a TypedDict , mypy checks that both the key and the value are valid.

Check that type of target is known [has-type]

Mypy sometimes generates an error when it hasn’t inferred any type for a variable being referenced. This can happen for references to variables that are initialized later in the source file, and for references across modules that form an import cycle. When this happens, the reference gets an implicit Any type.

In this example the definitions of x and y are circular:

To work around this error, you can add an explicit type annotation to the target variable or attribute. Sometimes you can also reorganize the code so that the definition of the variable is placed earlier than the reference to the variable in a source file. Untangling cyclic imports may also help.

We add an explicit annotation to the y attribute to work around the issue:

Check that import target can be found [import]

Mypy generates an error if it can’t find the source code or a stub file for an imported module.

See :ref:`ignore-missing-imports` for how to work around these errors.

Check that each name is defined once [no-redef]

Mypy may generate an error if you have multiple definitions for a name in the same namespace. The reason is that this is often an error, as the second definition may overwrite the first one. Also, mypy often can’t be able to determine whether references point to the first or the second definition, which would compromise type checking.

If you silence this error, all references to the defined name refer to the first definition.

Check that called function returns a value [func-returns-value]

Mypy reports an error if you call a function with a None return type and don’t ignore the return value, as this is usually (but not always) a programming error.

In this example, the if f() check is always false since f returns None :

Check instantiation of abstract classes [abstract]

Mypy generates an error if you try to instantiate an abstract base class (ABC). An abstract base class is a class with at least one abstract method or attribute. (See also :py:mod:`abc` module documentation)

Sometimes a class is made accidentally abstract, often due to an unimplemented abstract method. In a case like this you need to provide an implementation for the method to make the class concrete (non-abstract).

Safe handling of abstract type object types [type-abstract]

Mypy always allows instantiating (calling) type objects typed as Type[t] , even if it is not known that t is non-abstract, since it is a common pattern to create functions that act as object factories (custom constructors). Therefore, to prevent issues described in the above section, when an abstract type object is passed where Type[t] is expected, mypy will give an error. Example:

Check that call to an abstract method via super is valid [safe-super]

Abstract methods often don’t have any default implementation, i.e. their bodies are just empty. Calling such methods in subclasses via super() will cause runtime errors, so mypy prevents you from doing so:

Mypy considers the following as trivial bodies: a pass statement, a literal ellipsis . , a docstring, and a raise NotImplementedError statement.

Check the target of NewType [valid-newtype]

The target of a :py:func:`NewType ` definition must be a class type. It can’t be a union type, Any , or various other special types.

You can also get this error if the target has been imported from a module whose source mypy cannot find, since any such definitions are treated by mypy as values with Any types. Example:

To work around the issue, you can either give mypy access to the sources for acme or create a stub file for the module. See :ref:`ignore-missing-imports` for more information.

Check the return type of __exit__ [exit-return]

If mypy can determine that :py:meth:`__exit__ ` always returns False , mypy checks that the return type is not bool . The boolean value of the return type affects which lines mypy thinks are reachable after a with statement, since any :py:meth:`__exit__ ` method that can return True may swallow exceptions. An imprecise return type can result in mysterious errors reported near with statements.

To fix this, use either typing_extensions.Literal[False] or None as the return type. Returning None is equivalent to returning False in this context, since both are treated as false values.

This produces the following output from mypy:

You can use Literal[False] to fix the error:

You can also use None :

Check that naming is consistent [name-match]

The definition of a named tuple or a TypedDict must be named consistently when using the call-based syntax. Example:

Check that overloaded functions have an implementation [no-overload-impl]

Overloaded functions outside of stub files must be followed by a non overloaded implementation.

Check that coroutine return value is used [unused-coroutine]

Mypy ensures that return values of async def functions are not ignored, as this is usually a programming error, as the coroutine won’t be executed at the call site.

You can work around this error by assigning the result to a temporary, otherwise unused variable:

Check types in assert_type [assert-type]

The inferred type for an expression passed to assert_type must match the provided type.

Check that function isn’t used in boolean context [truthy-function]

Functions will always evaluate to true in boolean contexts.

Report syntax errors [syntax]

If the code being checked is not syntactically valid, mypy issues a syntax error. Most, but not all, syntax errors are blocking errors: they can’t be ignored with a # type: ignore comment.

Miscellaneous checks [misc]

Mypy performs numerous other, less commonly failing checks that don’t have specific error codes. These use the misc error code. Other than being used for multiple unrelated errors, the misc error code is not special. For example, you can ignore all errors in this category by using # type: ignore[misc] comment. Since these errors are not expected to be common, it’s unlikely that you’ll see two different errors with the misc code on a single line — though this can certainly happen once in a while.

Future mypy versions will likely add new error codes for some errors that currently use the misc error code.

Источник

Error codes enabled by default#

This section documents various errors codes that mypy can generate with default options. See Error codes for general documentation about error codes. Error codes for optional checks documents additional error codes that you can enable.

Check that attribute exists [attr-defined]#

Mypy checks that an attribute is defined in the target class or module when using the dot operator. This applies to both getting and setting an attribute. New attributes are defined by assignments in the class body, or assignments to self.x in methods. These assignments don’t generate attr-defined errors.

This error code is also generated if an imported name is not defined in the module in a from . import statement (as long as the target module can be found):

A reference to a missing attribute is given the Any type. In the above example, the type of non_existent will be Any , which can be important if you silence the error.

Check that attribute exists in each union item [union-attr]#

If you access the attribute of a value with a union type, mypy checks that the attribute is defined for every type in that union. Otherwise the operation can fail at runtime. This also applies to optional types.

You can often work around these errors by using assert isinstance(obj, ClassName) or assert obj is not None to tell mypy that you know that the type is more specific than what mypy thinks.

Check that name is defined [name-defined]#

Mypy expects that all references to names have a corresponding definition in an active scope, such as an assignment, function definition or an import. This can catch missing definitions, missing imports, and typos.

This example accidentally calls sort() instead of sorted() :

Check arguments in calls [call-arg]#

Mypy expects that the number and names of arguments match the called function. Note that argument type checks have a separate error code arg-type .

Check argument types [arg-type]#

Mypy checks that argument types in a call match the declared argument types in the signature of the called function (if one exists).

Check calls to overloaded functions [call-overload]#

When you call an overloaded function, mypy checks that at least one of the signatures of the overload items match the argument types in the call.

Check validity of types [valid-type]#

Mypy checks that each type annotation and any expression that represents a type is a valid type. Examples of valid types include classes, union types, callable types, type aliases, and literal types. Examples of invalid types include bare integer literals, functions, variables, and modules.

This example incorrectly uses the function log as a type:

You can use Callable as the type for callable objects:

Require annotation if variable type is unclear [var-annotated]#

In some cases mypy can’t infer the type of a variable without an explicit annotation. Mypy treats this as an error. This typically happens when you initialize a variable with an empty collection or None . If mypy can’t infer the collection item type, mypy replaces any parts of the type it couldn’t infer with Any and generates an error.

Example with an error:

To address this, we add an explicit annotation:

Check validity of overrides [override]#

Mypy checks that an overridden method or attribute is compatible with the base class. A method in a subclass must accept all arguments that the base class method accepts, and the return type must conform to the return type in the base class (Liskov substitution principle).

Argument types can be more general is a subclass (i.e., they can vary contravariantly). The return type can be narrowed in a subclass (i.e., it can vary covariantly). It’s okay to define additional arguments in a subclass method, as long all extra arguments have default values or can be left out ( *args , for example).

Check that function returns a value [return]#

If a function has a non- None return type, mypy expects that the function always explicitly returns a value (or raises an exception). The function should not fall off the end of the function, since this is often a bug.

Check that return value is compatible [return-value]#

Mypy checks that the returned value is compatible with the type signature of the function.

Check types in assignment statement [assignment]#

Mypy checks that the assigned expression is compatible with the assignment target (or targets).

Check type variable values [type-var]#

Mypy checks that value of a type variable is compatible with a value restriction or the upper bound type.

Check uses of various operators [operator]#

Mypy checks that operands support a binary or unary operation, such as + or

. Indexing operations are so common that they have their own error code index (see below).

Check indexing operations [index]#

Mypy checks that the indexed value in indexing operation such as x[y] supports indexing, and that the index expression has a valid type.

Check list items [list-item]#

When constructing a list using [item, . ] , mypy checks that each item is compatible with the list type that is inferred from the surrounding context.

Check dict items [dict-item]#

When constructing a dictionary using or dict(key=value, . ) , mypy checks that each key and value is compatible with the dictionary type that is inferred from the surrounding context.

Check TypedDict items [typeddict-item]#

When constructing a TypedDict object, mypy checks that each key and value is compatible with the TypedDict type that is inferred from the surrounding context.

When getting a TypedDict item, mypy checks that the key exists. When assigning to a TypedDict , mypy checks that both the key and the value are valid.

Check that type of target is known [has-type]#

Mypy sometimes generates an error when it hasn’t inferred any type for a variable being referenced. This can happen for references to variables that are initialized later in the source file, and for references across modules that form an import cycle. When this happens, the reference gets an implicit Any type.

In this example the definitions of x and y are circular:

To work around this error, you can add an explicit type annotation to the target variable or attribute. Sometimes you can also reorganize the code so that the definition of the variable is placed earlier than the reference to the variable in a source file. Untangling cyclic imports may also help.

We add an explicit annotation to the y attribute to work around the issue:

Check that import target can be found [import]#

Mypy generates an error if it can’t find the source code or a stub file for an imported module.

See Missing imports for how to work around these errors.

Check that each name is defined once [no-redef]#

Mypy may generate an error if you have multiple definitions for a name in the same namespace. The reason is that this is often an error, as the second definition may overwrite the first one. Also, mypy often can’t be able to determine whether references point to the first or the second definition, which would compromise type checking.

If you silence this error, all references to the defined name refer to the first definition.

Check that called function returns a value [func-returns-value]#

Mypy reports an error if you call a function with a None return type and don’t ignore the return value, as this is usually (but not always) a programming error.

In this example, the if f() check is always false since f returns None :

Check instantiation of abstract classes [abstract]#

Mypy generates an error if you try to instantiate an abstract base class (ABC). An abstract base class is a class with at least one abstract method or attribute. (See also abc module documentation)

Sometimes a class is made accidentally abstract, often due to an unimplemented abstract method. In a case like this you need to provide an implementation for the method to make the class concrete (non-abstract).

Safe handling of abstract type object types [type-abstract]#

Mypy always allows instantiating (calling) type objects typed as Type[t] , even if it is not known that t is non-abstract, since it is a common pattern to create functions that act as object factories (custom constructors). Therefore, to prevent issues described in the above section, when an abstract type object is passed where Type[t] is expected, mypy will give an error. Example:

Check that call to an abstract method via super is valid [safe-super]#

Abstract methods often don’t have any default implementation, i.e. their bodies are just empty. Calling such methods in subclasses via super() will cause runtime errors, so mypy prevents you from doing so:

Mypy considers the following as trivial bodies: a pass statement, a literal ellipsis . , a docstring, and a raise NotImplementedError statement.

Check the target of NewType [valid-newtype]#

The target of a NewType definition must be a class type. It can’t be a union type, Any , or various other special types.

You can also get this error if the target has been imported from a module whose source mypy cannot find, since any such definitions are treated by mypy as values with Any types. Example:

To work around the issue, you can either give mypy access to the sources for acme or create a stub file for the module. See Missing imports for more information.

Check the return type of __exit__ [exit-return]#

If mypy can determine that __exit__ always returns False , mypy checks that the return type is not bool . The boolean value of the return type affects which lines mypy thinks are reachable after a with statement, since any __exit__ method that can return True may swallow exceptions. An imprecise return type can result in mysterious errors reported near with statements.

To fix this, use either typing_extensions.Literal[False] or None as the return type. Returning None is equivalent to returning False in this context, since both are treated as false values.

This produces the following output from mypy:

You can use Literal[False] to fix the error:

You can also use None :

Check that naming is consistent [name-match]#

The definition of a named tuple or a TypedDict must be named consistently when using the call-based syntax. Example:

Check that overloaded functions have an implementation [no-overload-impl]#

Overloaded functions outside of stub files must be followed by a non overloaded implementation.

Check that coroutine return value is used [unused-coroutine]#

Mypy ensures that return values of async def functions are not ignored, as this is usually a programming error, as the coroutine won’t be executed at the call site.

You can work around this error by assigning the result to a temporary, otherwise unused variable:

Check types in assert_type [assert-type]#

The inferred type for an expression passed to assert_type must match the provided type.

Report syntax errors [syntax]#

If the code being checked is not syntactically valid, mypy issues a syntax error. Most, but not all, syntax errors are blocking errors: they can’t be ignored with a # type: ignore comment.

Miscellaneous checks [misc]#

Mypy performs numerous other, less commonly failing checks that don’t have specific error codes. These use the misc error code. Other than being used for multiple unrelated errors, the misc error code is not special. For example, you can ignore all errors in this category by using # type: ignore[misc] comment. Since these errors are not expected to be common, it’s unlikely that you’ll see two different errors with the misc code on a single line – though this can certainly happen once in a while.

Future mypy versions will likely add new error codes for some errors that currently use the misc error code.

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def _http_request(method: _HttpMethod, url: str, **kwargs) -> Optional[requests.models.Response]:
    _body: Any = None
    _retries: Any = 3
    if "json" in kwargs:
        _body = kwargs.get("json")
    elif "data" in kwargs:
        _body = kwargs.get("data")
    elif "retries" in kwargs:
        _retries = kwargs.get("retries")
    elif "timeout" in kwargs:
        _timeout = kwargs.get("timeout")

    for _retry in range(1, _retries):
        try:
            logging.debug(f"{method.value} {url} body: {_body}")
            _response = requests.request(method.value, url, **kwargs)
            logging.debug(f"{_response.status_code} body: {_response.text}")
            return _response
        except NewConnectionError:
            logging.error("Failed to establish a new connection: [WinError 10060] A connection attempt failed because the connected party did not properly respond after a period of time.")
            return None
        except requests.exceptions.ConnectionError:
            logging.error("Failed to establish a new connection: [Errno 113] No route to host.")
            return None
        except requests.exceptions.Timeout:
            if _retry <= 3:
                logging.warning(f"Connection to Jira timed out after {_timeout}, trying to connect again({_retry} of {_retries} retries)")
            else:
                logging.error(f"Failed to connect to jira server efter {_retries}")
                return None

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