DataSpell 2021.3 Help

Type hinting

DataSpell provides various means to assist inspecting and checking the types of the objects in your script. DataSpell supports type hinting in function annotations and type comments using the typing module and the format defined by PEP 484.

Adding type hints

Although DataSpell supports all methods for adding types supported in PEP 484, using type hints through intention actions is the most convenient way. Depending on the interpreter you use, the type is added as an annotation (Python 3) or as a comment (Python 2).

To add a type hint, follow these steps:

  1. Select a code element.

  2. Press Alt+Enter.

  3. Select Add type hint for ....

  4. Press Enter to complete the action or edit the type if appropriate.

Example

Intention Action

Resulting Code for comments (Python 2)

Resulting Code for annotations (Python 3)

Variables

example of adding a type hint for a variable
example of adding a type hint for a variable (Python 2)
example of adding a type hint for a variable (Python 3)

Functions

example of adding a type hint for a function
example of adding a type hint for a function (Python 2)
example of adding a type hint for a function (Python 3)

Class attributes

example of adding a type hint for a class attribute
example of adding a type hint for a class attribute (Python 2)
example of adding a type hint for a class attribute (Python 3)

You can also use Python stubs or comments to specify the types of variables, functions, and class fields.

Specifying types by using comments

Use a # type: comment to specify the types of local variables and attributes:

Type hinting attributes

Converting comments

For comment-based type hints, DataSpell suggests an intention action that allows you to convert comment-based type hint to a variable annotation. This intention has the name Convert to variable annotation, and works as follows:

Before

After

from typing import List, Optional xs = [] # type: List[Optional[str]]
from typing import List, Optional xs: List[Optional[str]] = []

Type hints validation

Any time you're applying type hints, DataSpell checks if the type is used correctly according to the supported PEPs. If there is a usage error, the corresponding warning is shown and the recommended action is suggested. Below are the validation examples.

Validation error

Suggested action

Duplication of type declaration.

incorrect type hint

Remove either of the type declarations.

Number of arguments in the type declaration differs from the number of function arguments.

too many arguments

Adjust the number of the arguments.

Type comments with unpacking do not match the corresponding targets.

incorrect type for unpacked variables

Check the target format and modify the type comment accordingly.

Incorrect syntax of Callable parameters.

Incorrect Callable format

Use the suggested format and add the required brackets to wrap Callable parameters.

Unexpected type in assignment expressions.

Unexpected type in an assignment expression

Align the types to match the expected pattern.

Assigning a value to a Final variable.

Assigning a value to a Final variable

You cannot alter a Final variable. Consider changing the type of the variable.

Inheriting a Final class.

Inheriting a final class

You cannot inherit a Final class. Consider changing its type.

Incorrect type of the function argument.

Literal type validation

Use the Color type instead of int.

Incorrect usage of the TypedDict class.

Type validation for the TypedDict class

Refer to the TypedDict object as follows:

record_movie(Movie(title='Blade Runner', year=1982))

Incorrect type of decorated methods. DataSpell can validate the type of decorated methods based on the types of their decorators as well as the type hints of their decorators:

Infer type of a decorate method

Use the suggested type, in this example, str instead of int.

You can add a # type: ignore comment to suppress a type validate warning or a missing import statement.

Ignore type validation

Python stubs

As DataSpell supports Python stub files, you can specify the type hints using Python 3 syntax for both Python 2 and 3.

If any type hints recorded in the stub files, they become available in your code that use these stubs. For example, the following type hint for some_func_2 becomes available in the Python code:

type hints in stubs

If you're using a package for which a stub analog is detected, the following message will be shown:

The stub package inspection

You can install the stub package, ignore this message and continue working with the currently installed package, or even disable the corresponding inspection in the project Settings/Preferences.

Using Typeshed

Typeshed is a set of files with type annotations for the standard Python library and various packages. Typeshed stubs provide definitions for Python classes, functions, and modules defined with type hints. DataSpell uses this information for better code completion, inspections, and other code insight features.

DataSpell is switching to Typeshed, the common repository for Python stubs. The Typeshed stubs bundled with DataSpell are shown in the project view under the node External Libraries | <Python interpreter> | Typeshed Stubs. Note that DataSpell currently uses only a few of the bundled stubs (that is builtins.pyi, typing.pyi, and several others).

To override the bundled Typeshed repository with your own version, follow these steps:

  1. Copy some or all the stubs into a directory in your project.

  2. Mark a directory as a source root by choosing Mark Directory as | Sources Root from the context menu of the directory.

The Python skeletons repository https://github.com/JetBrains/python-skeletons is now deprecated.

Last modified: 31 May 2021
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