type_enforced

Type Enforced

A pure python (no special compiler required) type enforcer for type annotations. Enforce types in python functions and methods.

Setup

Make sure you have Python 3.11.x (or higher) installed on your system. You can download it here.

Unsupported python versions can be used, however newer features will not be available.
- For 3.7: use type_enforced==0.0.16 (only very basic type checking is supported)
- For 3.8: use type_enforced==0.0.16 (only very basic type checking is supported)
- For 3.9: use type_enforced<=1.9.0 (staticmethod, union with | and from __future__ import annotations typechecking are not supported)
- For 3.10: use type_enforced<=1.10.2 (from __future__ import annotations may cause errors (EG: when using staticmethods and classmethods))

Installation

pip install type_enforced

Basic Usage

import type_enforced

@type_enforced.Enforcer(enabled=True, strict=True)
def my_fn(a: int , b: int | str =2, c: int =3) -> None:
    pass

Note: enabled=True by default if not specified. You can set enabled=False to disable type checking for a specific function, method, or class. This is useful for a production vs debugging environment or for undecorating a single method in a larger wrapped class.
Note: strict=True by default if not specified. You can set strict=False to disable exceptions being raised when type checking fails. Instead, a warning will be printed to the console.

Getting Started

type_enforcer contains a basic Enforcer wrapper that can be used to enforce many basic python typing hints. Technical Docs Here.

Enforcer can be used as a decorator for functions, methods, and classes. It will enforce the type hints on the function or method inputs and outputs. It takes in the following optional arguments:

enabled (True): A boolean to enable or disable type checking. If True, type checking will be enforced. If False, type checking will be disabled.
strict (True): A boolean to enable or disable type mismatch exceptions. If True exceptions will be raised when type checking fails. If False, exceptions will not be raised but instead a warning will be printed to the console.

type_enforcer currently supports many single and multi level python types. This includes class instances and classes themselves. For example, you can force an input to be an int, a number int | float, an instance of the self defined MyClass, or a even a vector with list[int]. Items like typing.List, typing.Dict, typing.Union and typing.Optional are supported.

You can pass union types to validate one of multiple types. For example, you could validate an input was an int or a float with int | float or typing.Union[int, float].

Nesting is allowed as long as the nested items are iterables (e.g. typing.List, dict, ...). For example, you could validate that a list is a vector with list[int] or possibly typing.List[int].

Variables without an annotation for type are not enforced.

Why use Type Enforced?

type_enforced is a pure python type enforcer that does not require any special compiler or preprocessor to work.
type_enforced uses the standard python typing hints and enforces them at runtime.
- This means that you can use it in any python environment (3.11+) without any special setup.
type_enforced is designed to be lightweight and easy to use, making it a great choice for both small and large projects.
type_enforced supports complex (nested) typing hints, union types, and many of the standard python typing functions.
type_enforced is designed to be fast and efficient, with minimal overhead.
type_enforced offers the fastest performance for enforcing large objects of complex types
- Note: See the benchmarks for more information on the performance of each type checker.

Supported Type Checking Features:

Function/Method Input Typing
Function/Method Return Typing
Dataclass Typing
All standard python types (str, list, int, dict, ...)
Union types
- typing.Union
- | separated items (e.g. int | float)
Nested types (e.g. dict[str, int] or list[int|float])
- Note: Each parent level must be an iterable
  - Specifically a variant of list, set, tuple or dict
- Note: dict requires two types to be specified (unions count as a single type)
  - The first type is the key type and the second type is the value type
  - e.g. dict[str, int|float] or dict[int, float]
- Note: list and set require a single type to be specified (unions count as a single type)
  - e.g. list[int], set[str], list[float|str]
- Note: tuple Allows for N types to be specified
  - Each item refers to the positional type of each item in the tuple
  - Support for ellipsis (...) is supported if you only specify two types and the second is the ellipsis type
    - e.g. tuple[int, ...] or tuple[int|str, ...]
  - Note: Unions between two tuples are not supported
    - e.g. tuple[int, str] | tuple[str, int] will not work
- Deeply nested types are supported too:
  - dict[dict[int]]
  - list[set[str]]
Many of the typing (package) functions and methods including:
- Standard typing functions:
  - List
  - Set
  - Dict
  - Tuple
- Union
- Optional
- Any
- Sized
  - Essentially creates a union of:
    - list, tuple, dict, set, str, bytes, bytearray, memoryview, range
  - Note: Can not have a nested type
    - Because this does not always meet the criteria for Nested types above
- Literal
  - Only allow certain values to be passed. Operates slightly differently than other checks.
  - e.g. Literal['a', 'b'] will require any passed values that are equal (==) to 'a' or 'b'.
    - This compares the value of the passed input and not the type of the passed input.
  - Note: Multiple types can be passed in the same Literal as acceptable values.
    - e.g. Literal['a', 'b', 1, 2] will require any passed values that are equal (==) to 'a', 'b', 1 or 2.
  - Note: If type is a str | Literal['a', 'b']
    - The check will validate that the type is a string or the value is equal to 'a' or 'b'.
    - This means that an input of 'c' will pass the check since it matches the string type, but an input of 1 will fail.
  - Note: If type is a int | Literal['a', 'b']
    - The check will validate that the type is an int or the value is equal to 'a' or 'b'.
    - This means that an input of 'c' will fail the check, but an input of 1 will pass.
  - Note: Literals stack when used with unions.
    - e.g. Literal['a', 'b'] | Literal[1, 2] will require any passed values that are equal (==) to 'a', 'b', 1 or 2.
- Callable
  - Essentially creates a union of:
    - staticmethod, classmethod, types.FunctionType, types.BuiltinFunctionType, types.MethodType, types.BuiltinMethodType, types.GeneratorType
- Note: Other functions might have support, but there are not currently tests to validate them
  - Feel free to create an issue (or better yet a PR) if you want to add tests/support
Constraint validation.
- This is a special type of validation that allows passed input to be validated.
  - Standard and custom constraints are supported.
- This is useful for validating that a passed input is within a certain range or meets a certain criteria.
- Note: Constraints stack when used with unions.
  - e.g. int | Constraint(ge=0) | Constraint(le=5) will require any passed values to be integers that are greater than or equal to 0 and less than or equal to 5.
- Note: The constraint is checked after type checking occurs and operates independently of the type checking.
  - This operates differently than other checks (like Literal) and is evaluated post type checking.
  - For example, if you have an annotation of str | Constraint(ge=0), this will always raise an exception since if you pass a string, it will raise on the constraint check and if you pass an integer, it will raise on the type check.
- Note: See the example below or technical constraint and generic constraint docs for more information. ```

Interactive Example

>>> import type_enforced
>>> @type_enforced.Enforcer
... def my_fn(a: int , b: int|str =2, c: int =3) -> None:
...     pass
...
>>> my_fn(a=1, b=2, c=3)
>>> my_fn(a=1, b='2', c=3)
>>> my_fn(a='a', b=2, c=3)
Traceback (most recent call last):
  File "<python-input-2>", line 1, in <module>
    my_fn(a='a', b=2, c=3)
    ~~~~~^^^^^^^^^^^^^^^^^
  File "/app/type_enforced/enforcer.py", line 233, in __call__
    self.__check_type__(assigned_vars.get(key), value, key)
    ~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/app/type_enforced/enforcer.py", line 266, in __check_type__
    self.__exception__(
    ~~~~~~~~~~~~~~~~~~^
        f"Type mismatch for typed variable `{key}`. Expected one of the following `{list(expected.keys())}` but got `{obj_type}` with value `{obj}` instead."
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/app/type_enforced/enforcer.py", line 188, in __exception__
    raise TypeError(f"TypeEnforced Exception ({self.__fn__.__qualname__}): {message}")
TypeError: TypeEnforced Exception (my_fn): Type mismatch for typed variable `a`. Expected one of the following `[<class 'int'>]` but got `<class 'str'>` with value `a` instead.

Nested Examples

import type_enforced
import typing

@type_enforced.Enforcer
def my_fn(
    a: dict[str,dict[str, int|float]], # Note: For dicts, the key is the first type and the value is the second type
    b: list[typing.Set[str]] # Could also just use set
) -> None:
    return None

my_fn(a={'i':{'j':1}}, b=[{'x'}]) # Success

my_fn(a={'i':{'j':'k'}}, b=[{'x'}]) # Error =>
# TypeError: TypeEnforced Exception (my_fn): Type mismatch for typed variable `a['i']['j']`. Expected one of the following `[<class 'int'>, <class 'float'>]` but got `<class 'str'>` with value `k` instead.

Class and Method Use

Type enforcer can be applied to methods individually:

import type_enforced

class my_class:
    @type_enforced.Enforcer
    def my_fn(self, b:int):
        pass

You can also enforce all typing for all methods in a class by decorating the class itself.

import type_enforced

@type_enforced.Enforcer
class my_class:
    def my_fn(self, b:int):
        pass

    def my_other_fn(self, a: int, b: int | str):
      pass

You can also enforce types on staticmethods and classmethods if you are using python >= 3.10. If you are using a python version less than this, classmethods and staticmethods methods will not have their types enforced.

import type_enforced

@type_enforced.Enforcer
class my_class:
    @classmethod
    def my_fn(self, b:int):
        pass

    @staticmethod
    def my_other_fn(a: int, b: int | str):
      pass

Dataclasses are suported too.

import type_enforced
from dataclasses import dataclass

@type_enforced.Enforcer
@dataclass
class my_class:
    foo: int
    bar: str

You can skip enforcement if you add the argument enabled=False in the Enforcer call.

This is useful for a production vs debugging environment.
This is also useful for undecorating a single method in a larger wrapped class.
Note: You can set enabled=False for an entire class or simply disable a specific method in a larger wrapped class.
Note: Method level wrapper enabled values take precedence over class level wrappers.

import type_enforced
@type_enforced.Enforcer
class my_class:
    def my_fn(self, a: int) -> None:
        pass

    @type_enforced.Enforcer(enabled=False)
    def my_other_fn(self, a: int) -> None:
        pass

Validate with Constraints

Type enforcer can enforce constraints for passed variables. These constraints are validated after any type checks are made.

To enforce basic input values are integers greater than or equal to zero, you can use the Constraint class like so:

import type_enforced
from type_enforced.utils import Constraint

@type_enforced.Enforcer()
def positive_int_test(value: int |Constraint(ge=0)) -> bool:
    return True

positive_int_test(1) # Passes
positive_int_test(-1) # Fails
positive_int_test(1.0) # Fails

To enforce a GenericConstraint:

import type_enforced
from type_enforced.utils import GenericConstraint

CustomConstraint = GenericConstraint(
    {
        'in_rgb': lambda x: x in ['red', 'green', 'blue'],
    }
)

@type_enforced.Enforcer()
def rgb_test(value: str | CustomConstraint) -> bool:
    return True

rgb_test('red') # Passes
rgb_test('yellow') # Fails

Validate class instances and classes

Type enforcer can enforce class instances and classes. There are a few caveats between the two.

To enforce a class instance, simply pass the class itself as a type hint:

import type_enforced

class Foo():
    def __init__(self) -> None:
        pass

@type_enforced.Enforcer
class my_class():
    def __init__(self, object: Foo) -> None:
        self.object = object

x=my_class(Foo()) # Works great!
y=my_class(Foo) # Fails!

Notice how an initialized class instance Foo() must be passed for the enforcer to not raise an exception.

To enforce an uninitialized class object use typing.Type[classHere] on the class to enforce inputs to be an uninitialized class:

import type_enforced
import typing

class Foo():
    def __init__(self) -> None:
        pass

@type_enforced.Enforcer
class my_class():
    def __init__(self, object_class: typing.Type[Foo]) -> None:
        self.object = object_class()

y=my_class(Foo) # Works great!
x=my_class(Foo()) # Fails

By default, type_enforced will check for subclasses of a class when validating types. This means that if you pass a subclass of the expected class, it will pass the type check.

Note: Uninitialized class objects that are passed are not checked for subclasses.

import type_enforced

class Foo:
    pass

class Bar(Foo):
    pass

class Baz:
    pass

@type_enforced.Enforcer
def my_fn(custom_class: Foo):
    pass

my_fn(Foo()) # Passes as expected
my_fn(Bar()) # Passes as expected
my_fn(Baz()) # Raises TypeError as expected

What changed in 2.0.0?

The main changes in version 2.0.0 revolve around migrating towards the standard python typing hint process and away from the original type_enfoced type hints (as type enforced was originally created before the | operator was added to python).

Support for python3.10 has been dropped.
List based union types are no longer supported.
- For example [int, float] is no longer a supported type hint.
- Use int|float or typing.Union[int, float] instead.
Dict types now require two types to be specified.
- The first type is the key type and the second type is the value type.
- For example, dict[str, int|float] or dict[int, float] are valid types.
Tuple types now allow for N types to be specified.
- Each item refers to the positional type of each item in the tuple.
- Support for ellipsis (...) is supported if you only specify two types and the second is the ellipsis type.
  - For example, tuple[int, ...] or tuple[int|str, ...] are valid types.
- Note: Unions between two tuples are not supported.
  - For example, tuple[int, str] | tuple[str, int] will not work.
Constraints and Literals can now be stacked with unions.
- For example, int | Constraint(ge=0) | Constraint(le=5) will require any passed values to be integers that are greater than or equal to 0 and less than or equal to 5.
- For example, Literal['a', 'b'] | Literal[1, 2] will require any passed values that are equal (==) to 'a', 'b', 1 or 2.
Literals now evaluate during the same time as type checking and operate as OR checks.
- For example, int | Literal['a', 'b'] will validate that the type is an int or the value is equal to 'a' or 'b'.
Constraints are still are evaluated after type checking and operate independently of the type checking.

Development

Running Tests, Prettifying Code, and Updating Docs

Make sure Docker is installed and running.

Create a docker container and drop into a shell
- ./run.sh
Run all tests (see ./utils/test.sh)
- ./run.sh test
Prettify the code (see ./utils/prettify.sh)
- ./run.sh prettify
Update the docs (see ./utils/docs.sh)
- ./run.sh docs
Note: You can and should modify the Dockerfile to test different python versions.

View Source

  1"""
  2# Type Enforced
  3[![PyPI version](https://badge.fury.io/py/type_enforced.svg)](https://badge.fury.io/py/type_enforced)
  4[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
  5[![PyPI Downloads](https://pepy.tech/badge/type_enforced)](https://pypi.org/project/type_enforced/)
  6<!-- [![PyPI Downloads](https://img.shields.io/pypi/dm/type_enforced.svg?label=PyPI%20downloads)](https://pypi.org/project/type_enforced/) -->
  7
  8A pure python (no special compiler required) type enforcer for type annotations. Enforce types in python functions and methods.
  9
 10# Setup
 11
 12Make sure you have Python 3.11.x (or higher) installed on your system. You can download it [here](https://www.python.org/downloads/).
 13
 14- Unsupported python versions can be used, however newer features will not be available.
 15    - For 3.7: use type_enforced==0.0.16 (only very basic type checking is supported)
 16    - For 3.8: use type_enforced==0.0.16 (only very basic type checking is supported)
 17    - For 3.9: use type_enforced<=1.9.0 (`staticmethod`, union with `|` and `from __future__ import annotations` typechecking are not supported)
 18    - For 3.10: use type_enforced<=1.10.2 (`from __future__ import annotations` may cause errors (EG: when using staticmethods and classmethods))
 19
 20### Installation
 21
 22```
 23pip install type_enforced
 24```
 25
 26## Basic Usage
 27```py
 28import type_enforced
 29
 30@type_enforced.Enforcer(enabled=True, strict=True)
 31def my_fn(a: int , b: int | str =2, c: int =3) -> None:
 32    pass
 33```
 34- Note: `enabled=True` by default if not specified. You can set `enabled=False` to disable type checking for a specific function, method, or class. This is useful for a production vs debugging environment or for undecorating a single method in a larger wrapped class. 
 35- Note: `strict=True` by default if not specified. You can set `strict=False` to disable exceptions being raised when type checking fails. Instead, a warning will be printed to the console.
 36
 37## Getting Started
 38
 39`type_enforcer` contains a basic `Enforcer` wrapper that can be used to enforce many basic python typing hints. [Technical Docs Here](https://connor-makowski.github.io/type_enforced/type_enforced/enforcer.html).
 40
 41`Enforcer` can be used as a decorator for functions, methods, and classes. It will enforce the type hints on the function or method inputs and outputs. It takes in the following optional arguments:
 42
 43- `enabled` (True): A boolean to enable or disable type checking. If `True`, type checking will be enforced. If `False`, type checking will be disabled.
 44- `strict` (True): A boolean to enable or disable type mismatch exceptions. If `True` exceptions will be raised when type checking fails. If `False`, exceptions will not be raised but instead a warning will be printed to the console.
 45
 46`type_enforcer` currently supports many single and multi level python types. This includes class instances and classes themselves. For example, you can force an input to be an `int`, a number `int | float`, an instance of the self defined `MyClass`, or a even a vector with `list[int]`. Items like `typing.List`, `typing.Dict`, `typing.Union` and `typing.Optional` are supported.
 47
 48You can pass union types to validate one of multiple types. For example, you could validate an input was an int or a float with `int | float` or `typing.Union[int, float]`.
 49
 50Nesting is allowed as long as the nested items are iterables (e.g. `typing.List`, `dict`, ...). For example, you could validate that a list is a vector with `list[int]` or possibly `typing.List[int]`.
 51
 52Variables without an annotation for type are not enforced.
 53
 54## Why use Type Enforced?
 55
 56- `type_enforced` is a pure python type enforcer that does not require any special compiler or preprocessor to work. 
 57- `type_enforced` uses the standard python typing hints and enforces them at runtime.
 58    - This means that you can use it in any python environment (3.11+) without any special setup.
 59- `type_enforced` is designed to be lightweight and easy to use, making it a great choice for both small and large projects.
 60- `type_enforced` supports complex (nested) typing hints, union types, and many of the standard python typing functions.
 61- `type_enforced` is designed to be fast and efficient, with minimal overhead. 
 62- `type_enforced` offers the fastest performance for enforcing large objects of complex types 
 63    - Note: See the [benchmarks](https://github.com/connor-makowski/type_enforced/blob/main/benchmark.md) for more information on the performance of each type checker.
 64
 65## Supported Type Checking Features:
 66
 67- Function/Method Input Typing
 68- Function/Method Return Typing
 69- Dataclass Typing
 70- All standard python types (`str`, `list`, `int`, `dict`, ...)
 71- Union types
 72    - typing.Union
 73    - `|` separated items (e.g. `int | float`)
 74- Nested types (e.g. `dict[str, int]` or `list[int|float]`)
 75    - Note: Each parent level must be an iterable
 76        - Specifically a variant of `list`, `set`, `tuple` or `dict`
 77    - Note: `dict` requires two types to be specified (unions count as a single type)
 78        - The first type is the key type and the second type is the value type
 79        - e.g. `dict[str, int|float]` or `dict[int, float]`
 80    - Note: `list` and `set` require a single type to be specified (unions count as a single type)
 81        - e.g. `list[int]`, `set[str]`, `list[float|str]`
 82    - Note: `tuple` Allows for `N` types to be specified
 83        - Each item refers to the positional type of each item in the tuple
 84        - Support for ellipsis (`...`) is supported if you only specify two types and the second is the ellipsis type
 85            - e.g. `tuple[int, ...]` or `tuple[int|str, ...]`
 86        - Note: Unions between two tuples are not supported
 87            - e.g. `tuple[int, str] | tuple[str, int]` will not work
 88    - Deeply nested types are supported too:
 89        - `dict[dict[int]]`
 90        - `list[set[str]]`
 91- Many of the `typing` (package) functions and methods including:
 92    - Standard typing functions:
 93        - `List`
 94        - `Set`
 95        - `Dict`
 96        - `Tuple`
 97    - `Union`
 98    - `Optional`
 99    - `Any`
100    - `Sized`
101        - Essentially creates a union of:
102            - `list`, `tuple`, `dict`, `set`, `str`, `bytes`, `bytearray`, `memoryview`, `range`
103        - Note: Can not have a nested type
104            - Because this does not always meet the criteria for `Nested types` above
105    - `Literal`
106        - Only allow certain values to be passed. Operates slightly differently than other checks.
107        - e.g. `Literal['a', 'b']` will require any passed values that are equal (`==`) to `'a'` or `'b'`.
108            - This compares the value of the passed input and not the type of the passed input.
109        - Note: Multiple types can be passed in the same `Literal` as acceptable values.
110            - e.g. Literal['a', 'b', 1, 2] will require any passed values that are equal (`==`) to `'a'`, `'b'`, `1` or `2`.
111        - Note: If type is a `str | Literal['a', 'b']`
112            - The check will validate that the type is a string or the value is equal to `'a'` or `'b'`.
113            - This means that an input of `'c'` will pass the check since it matches the string type, but an input of `1` will fail.
114        - Note: If type is a `int | Literal['a', 'b']`
115            - The check will validate that the type is an int or the value is equal to `'a'` or `'b'`.
116            - This means that an input of `'c'` will fail the check, but an input of `1` will pass.
117        - Note: Literals stack when used with unions.
118            - e.g. `Literal['a', 'b'] | Literal[1, 2]` will require any passed values that are equal (`==`) to `'a'`, `'b'`, `1` or `2`.
119    - `Callable`
120        - Essentially creates a union of:
121            - `staticmethod`, `classmethod`, `types.FunctionType`, `types.BuiltinFunctionType`, `types.MethodType`, `types.BuiltinMethodType`, `types.GeneratorType`
122    - Note: Other functions might have support, but there are not currently tests to validate them
123        - Feel free to create an issue (or better yet a PR) if you want to add tests/support
124- `Constraint` validation.
125    - This is a special type of validation that allows passed input to be validated.
126        - Standard and custom constraints are supported.
127    - This is useful for validating that a passed input is within a certain range or meets a certain criteria.
128    - Note: Constraints stack when used with unions.
129        - e.g. `int | Constraint(ge=0) | Constraint(le=5)` will require any passed values to be integers that are greater than or equal to `0` and less than or equal to `5`.
130    - Note: The constraint is checked after type checking occurs and operates independently of the type checking.
131        - This operates differently than other checks (like `Literal`) and is evaluated post type checking.
132        - For example, if you have an annotation of `str | Constraint(ge=0)`, this will always raise an exception since if you pass a string, it will raise on the constraint check and if you pass an integer, it will raise on the type check.
133    - Note: See the example below or technical [constraint](https://connor-makowski.github.io/type_enforced/type_enforced/utils.html#Constraint) and [generic constraint](https://connor-makowski.github.io/type_enforced/type_enforced/utils.html#GenericConstraint) docs for more information.
134    ```
135
136## Interactive Example
137
138```py
139>>> import type_enforced
140>>> @type_enforced.Enforcer
141... def my_fn(a: int , b: int|str =2, c: int =3) -> None:
142...     pass
143...
144>>> my_fn(a=1, b=2, c=3)
145>>> my_fn(a=1, b='2', c=3)
146>>> my_fn(a='a', b=2, c=3)
147Traceback (most recent call last):
148  File "<python-input-2>", line 1, in <module>
149    my_fn(a='a', b=2, c=3)
150    ~~~~~^^^^^^^^^^^^^^^^^
151  File "/app/type_enforced/enforcer.py", line 233, in __call__
152    self.__check_type__(assigned_vars.get(key), value, key)
153    ~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
154  File "/app/type_enforced/enforcer.py", line 266, in __check_type__
155    self.__exception__(
156    ~~~~~~~~~~~~~~~~~~^
157        f"Type mismatch for typed variable `{key}`. Expected one of the following `{list(expected.keys())}` but got `{obj_type}` with value `{obj}` instead."
158        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
159    )
160    ^
161  File "/app/type_enforced/enforcer.py", line 188, in __exception__
162    raise TypeError(f"TypeEnforced Exception ({self.__fn__.__qualname__}): {message}")
163TypeError: TypeEnforced Exception (my_fn): Type mismatch for typed variable `a`. Expected one of the following `[<class 'int'>]` but got `<class 'str'>` with value `a` instead.
164```
165
166## Nested Examples
167```py
168import type_enforced
169import typing
170
171@type_enforced.Enforcer
172def my_fn(
173    a: dict[str,dict[str, int|float]], # Note: For dicts, the key is the first type and the value is the second type
174    b: list[typing.Set[str]] # Could also just use set
175) -> None:
176    return None
177
178my_fn(a={'i':{'j':1}}, b=[{'x'}]) # Success
179
180my_fn(a={'i':{'j':'k'}}, b=[{'x'}]) # Error =>
181# TypeError: TypeEnforced Exception (my_fn): Type mismatch for typed variable `a['i']['j']`. Expected one of the following `[<class 'int'>, <class 'float'>]` but got `<class 'str'>` with value `k` instead.
182```
183
184## Class and Method Use
185
186Type enforcer can be applied to methods individually:
187
188```py
189import type_enforced
190
191class my_class:
192    @type_enforced.Enforcer
193    def my_fn(self, b:int):
194        pass
195```
196
197You can also enforce all typing for all methods in a class by decorating the class itself.
198
199```py
200import type_enforced
201
202@type_enforced.Enforcer
203class my_class:
204    def my_fn(self, b:int):
205        pass
206
207    def my_other_fn(self, a: int, b: int | str):
208      pass
209```
210
211You can also enforce types on `staticmethod`s and `classmethod`s if you are using `python >= 3.10`. If you are using a python version less than this, `classmethod`s and `staticmethod`s methods will not have their types enforced.
212
213```py
214import type_enforced
215
216@type_enforced.Enforcer
217class my_class:
218    @classmethod
219    def my_fn(self, b:int):
220        pass
221
222    @staticmethod
223    def my_other_fn(a: int, b: int | str):
224      pass
225```
226
227Dataclasses are suported too.
228
229```py
230import type_enforced
231from dataclasses import dataclass
232
233@type_enforced.Enforcer
234@dataclass
235class my_class:
236    foo: int
237    bar: str
238```
239
240You can skip enforcement if you add the argument `enabled=False` in the `Enforcer` call.
241- This is useful for a production vs debugging environment.
242- This is also useful for undecorating a single method in a larger wrapped class.
243- Note: You can set `enabled=False` for an entire class or simply disable a specific method in a larger wrapped class.
244- Note: Method level wrapper `enabled` values take precedence over class level wrappers.
245```py
246import type_enforced
247@type_enforced.Enforcer
248class my_class:
249    def my_fn(self, a: int) -> None:
250        pass
251
252    @type_enforced.Enforcer(enabled=False)
253    def my_other_fn(self, a: int) -> None:
254        pass
255```
256
257## Validate with Constraints
258Type enforcer can enforce constraints for passed variables. These constraints are validated after any type checks are made.
259
260To enforce basic input values are integers greater than or equal to zero, you can use the [Constraint](https://connor-makowski.github.io/type_enforced/type_enforced/utils.html#Constraint) class like so:
261```py
262import type_enforced
263from type_enforced.utils import Constraint
264
265@type_enforced.Enforcer()
266def positive_int_test(value: int |Constraint(ge=0)) -> bool:
267    return True
268
269positive_int_test(1) # Passes
270positive_int_test(-1) # Fails
271positive_int_test(1.0) # Fails
272```
273
274To enforce a [GenericConstraint](https://connor-makowski.github.io/type_enforced/type_enforced/utils.html#GenericConstraint):
275```py
276import type_enforced
277from type_enforced.utils import GenericConstraint
278
279CustomConstraint = GenericConstraint(
280    {
281        'in_rgb': lambda x: x in ['red', 'green', 'blue'],
282    }
283)
284
285@type_enforced.Enforcer()
286def rgb_test(value: str | CustomConstraint) -> bool:
287    return True
288
289rgb_test('red') # Passes
290rgb_test('yellow') # Fails
291```
292
293
294
295## Validate class instances and classes
296
297Type enforcer can enforce class instances and classes. There are a few caveats between the two.
298
299To enforce a class instance, simply pass the class itself as a type hint:
300```py
301import type_enforced
302
303class Foo():
304    def __init__(self) -> None:
305        pass
306
307@type_enforced.Enforcer
308class my_class():
309    def __init__(self, object: Foo) -> None:
310        self.object = object
311
312x=my_class(Foo()) # Works great!
313y=my_class(Foo) # Fails!
314```
315
316Notice how an initialized class instance `Foo()` must be passed for the enforcer to not raise an exception.
317
318To enforce an uninitialized class object use `typing.Type[classHere]` on the class to enforce inputs to be an uninitialized class:
319```py
320import type_enforced
321import typing
322
323class Foo():
324    def __init__(self) -> None:
325        pass
326
327@type_enforced.Enforcer
328class my_class():
329    def __init__(self, object_class: typing.Type[Foo]) -> None:
330        self.object = object_class()
331
332y=my_class(Foo) # Works great!
333x=my_class(Foo()) # Fails
334```
335
336By default, type_enforced will check for subclasses of a class when validating types. This means that if you pass a subclass of the expected class, it will pass the type check.
337
338Note: Uninitialized class objects that are passed are not checked for subclasses.
339
340```py
341import type_enforced
342
343class Foo:
344    pass
345
346class Bar(Foo):
347    pass
348
349class Baz:
350    pass
351
352@type_enforced.Enforcer
353def my_fn(custom_class: Foo):
354    pass
355
356my_fn(Foo()) # Passes as expected
357my_fn(Bar()) # Passes as expected
358my_fn(Baz()) # Raises TypeError as expected
359```
360
361## What changed in 2.0.0?
362The main changes in version 2.0.0 revolve around migrating towards the standard python typing hint process and away from the original type_enfoced type hints (as type enforced was originally created before the `|` operator was added to python).
363- Support for python3.10 has been dropped.
364- List based union types are no longer supported.
365    - For example `[int, float]` is no longer a supported type hint.
366    - Use `int|float` or `typing.Union[int, float]` instead.
367- Dict types now require two types to be specified.
368    - The first type is the key type and the second type is the value type.
369    - For example, `dict[str, int|float]` or `dict[int, float]` are valid types.
370- Tuple types now allow for `N` types to be specified.
371    - Each item refers to the positional type of each item in the tuple.
372    - Support for ellipsis (`...`) is supported if you only specify two types and the second is the ellipsis type.
373        - For example, `tuple[int, ...]` or `tuple[int|str, ...]` are valid types.
374    - Note: Unions between two tuples are not supported.
375        - For example, `tuple[int, str] | tuple[str, int]` will not work.
376- Constraints and Literals can now be stacked with unions.
377    - For example, `int | Constraint(ge=0) | Constraint(le=5)` will require any passed values to be integers that are greater than or equal to `0` and less than or equal to `5`.
378    - For example, `Literal['a', 'b'] | Literal[1, 2]` will require any passed values that are equal (`==`) to `'a'`, `'b'`, `1` or `2`.
379- Literals now evaluate during the same time as type checking and operate as OR checks.
380    - For example, `int | Literal['a', 'b']` will validate that the type is an int or the value is equal to `'a'` or `'b'`.
381- Constraints are still are evaluated after type checking and operate independently of the type checking.
382
383# Development
384## Running Tests, Prettifying Code, and Updating Docs
385
386Make sure Docker is installed and running.
387
388- Create a docker container and drop into a shell
389    - `./run.sh`
390- Run all tests (see ./utils/test.sh)
391    - `./run.sh test`
392- Prettify the code (see ./utils/prettify.sh)
393    - `./run.sh prettify`
394- Update the docs (see ./utils/docs.sh)
395    - `./run.sh docs`
396
397- Note: You can and should modify the `Dockerfile` to test different python versions."""
398from .enforcer import Enforcer, FunctionMethodEnforcer