Pytypedecl - https://github.com/google/pytypedecl/
Pytypedecl consists of a type declaration language for Python and an optional run-time type checker. This project was started by Raoul-Gabriel Urma under the supervision of Peter Ludemann during a summer 2013 internship at Google.
Apache 2.0
Type declarations are useful to document your code. This proposal is an attempt at starting a conversation with the community to reach a standard for a type declaration language for Python.
Runtime type-checking of optional type declarations is useful for code maintenance and debugging. Our type-checker is available as a Python package. You therefore do not need to run external tools to benefit from the type-checking.
This project is in its infancy, as such there are many updates to come in the next couple of months. We currently support Python 2.7. Support for Python 3 coming soon.
Types declarations are specified in an external file with the extension “pytd”. For example if you want to provide types for “application.py”, you define the type inside the file “application.pytd”. Many examples of type declarations files can be found in the /tests/ folder.
Here’s an example of a type declaration file that mixes several features:
class Logger:
def log(messages: list[str], buffer: Readable & Writable) -> None raise IOException
def log(messages: list[str]) -> None
def setStatus(status: int | str) -> None
interface Writable(Openable, Closeable):
def write
interface Readable(Openable, Closeable):
def read
interface Openable:
def open
interface Closeable:
def closeThe type declaration language currently supports the following features:
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Function signatures: Functions can be given a signature following the Python 3 function annotation convention. However, we extended it to specify a list of possible exceptions that the function may raise.
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Overloading: A function is allowed to have multiple different signatures. This is not supported in the Python 3 function annotation syntax but is supported by pytypedecl.
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Interfaces: An interface describes a set of operations that a type must support. It can be seen as defining a structural type with an additional name to refer to that structure. Interfaces can also be multiply inherited like in Java. The Logger example above declares four interfaces: Writable and Readable are both inheriting from the interfaces Openable and Closeable. This means that in addition to the operations they define, Openable and Closeable implicitly support the operations defined by Openable and Closeable: open and close.
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None-able types: A none-able type can represent the range of values for its value type plus an additional None value. We use a trailing ? to indicate that a type is none-able. For example, a parameter of type int? can accept a int or a None value.
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Union types: It is sometime convenient to indicate that a type can hold values from a type or another one. Union types allow to express this idea. For example int | float indicates that a value may be an int or a float. There is no limit to the number of types that a part of a union. Note that a none-able type can be seen as the union of a given type and None. For example int? is equivalent to int | None.
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Intersection types: An intersection type describe a type that belongs to all values of a list of types. For example, the intersection type Readable & Writable (the operator & is used for detonating intersection) describes a type that supports the operations open, close, read and write. As a consequence, the intersection type int & float wouldn’t make much sense because there isn’t a value in Python that is both an int and a float.
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Generics: A type can be parameterised with a set of type arguments, similarly to Java generics. For example, generator[str] describes a generator that only produces strings, dict[int, str] describes a dictionary of keys of type int and values of type str.
- Declaration of type parameters for methods and classes.
- Bounded type parameters
- Support for tags: @classmethod, @staticmethod...
git clone https://github.com/google/pytypedecl.git
python setup.py install
The package is now installed. You can run an example:
$ python -B demo.py
The -B flag prevents the generation of pyc file.
You can also run the tests:
$ python -B all_tests.py
Look into the /examples/ directory to see how the emailer example works. You need to do two things to type-check your program:
1. Create a type declaration file
Create a type declaration file that has the name of the Python file you want to type-check but with the extension .pytd (e.g. email.pytd for email.py)
2. Import the checker package
Include the following two imports in the Python file that you want to type-check:
import sys
from pytypedecl import checker
And the following line after your function and class declarations (before they are used)
checker.CheckFromFile(sys.modules[__name__], __file__ + "td")
That’s it! You can now run your python program and it will be type-checked at runtime using the type declarations you defined in the pytd file.
- Check out the issue tracker
- Mailing List: https://groups.google.com/forum/#!forum/pytypedecl-dev
- Send us suggestions
- Fork