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        "description": "***********\nValidate It\n***********\n\nDataclass Validators.\n\ntypeforced decorator\n--------------------\nDataclasses module does not control types in runtime. With `validateit` you can force user to give propert date with propert type.\n`validateit` provides a class decorator for runtime typecheck. You have to decorate your dataclass with `@typeforced`.\n\n.. code-block:: python\n\n    >>> @typeforced\n    ... @dataclass\n    ... class Item:\n    ...     name: str\n    ...     idx : int\n    ...     owners : List[str]\n    ...\n    >>>\n\nLets try to create a valid Item\n\n.. code-block:: python\n\n    >>> Item(\"Sword\", 1, [\"damla\"])\n    Item(name='Sword', idx=1, owners=['damla'])\n\nFunny part :) Lets give int value to name field. \n\n.. code-block:: python\n\n    >>> Item(1515, 1, [\"damla\"])\n    TypeError: Unexpected type for 'name' (expected <class 'str'> but found <class 'int'>)\n\nAs you can see `typeguard` raised a TypeError because it expects a string but we give it an integer. \n\nLets make another example. Give a set object instead of List[str].\n\n.. code-block:: python\n\n    >>> Item(\"Sword\", 1, {\"damla\"})\n    TypeError: Unexpected type for 'owners' (expected typing.List[str] but found <class 'set'>)\n\nTypeValidator\n-------------\nValidates types for specific fields instead of all fields (if you want to check types of all fields in runtime use `typeforced`).\n\nLets make an pet. We must force user to give name as string but we dont care type of `idx`.\n\n.. code-block:: python\n    \n    >>> @dataclass\n    ... class Pet:\n    ...     idx: int\n    ...     name: str = field(default=TypeValidator())\n    ... \n    >>> Pet(15, \"Minnos\")\n    Pet(idx=15, name='Minnos')\n    >>> Pet(15, 1313)\n    TypeError: Unexpected type for 'name' (expected <class 'str'> but found <class 'int'>)\n    >>> Pet(\"fifteen\", \"Minnos\") # No error cuz it is not runtime typevalidated.\n    Pet(idx='fifteen', name='Minnos')\n\nIntegerValidator\n----------------\nSome integer specific validations. Can take `max` , `min` , `max_digits`, `min_digits`\n\n.. code-block:: python\n    \n    >>> @dataclass\n    ... class Integer:\n    ...     number : int = field(default=IntegerValidator(min=15, max=150))\n    ...     point  : int = field(default=IntegerValidator(min_digits=1, max_digits=10))\n    ...     def __str__(self):\n    ...         return f\"{self.number}.{self.point}\"\n    ... \n    >>> str(Integer(20, 3333))\n    '20.3333'\n    >>> Integer(14, 3333)\n    ValueError: Integer is not bigger than 15 (minimum limit)\n    >>> Integer(160, 3333)\n    ValueError: Integer is bigger than 150 (maximum limit)\n    >>> Integer(20, 339933993399339)\n    ValueError: Integer doesn't capable of having maximum 10 digits.\n    \nStringValidator\n---------------\nSome string specific validations. Can take `max_chars` , `max_chars` , `startswith`, `endswith`\n\n.. code-block:: python\n\n    >>> @dataclass\n    ... class Person:\n    ...     name: str = field(default=StringValidator(min_chars=5, max_chars=10))\n    ...     surname: str = field(default=StringValidator(startswith='a', endswith='n'))\n    ... \n    >>> Person(\"damla\", \"altun\")\n    Person(name='damla', surname='altun')\n    >>> Person(\"daml\", \"altun\")\n    ValueError: String doesn't capable of having minimum 5 chars.\n    >>> Person(\"damlaaaaaaaaa\", \"altun\")\n    ValueError: String doesn't capable of having maximum 10 chars.\n    >>> Person(\"damla\", \"xaltun\")\n    ValueError: String isn't starts with a\n    >>> Person(\"damla\", \"altunx\")\n    ValueError: String isn't ends with n",
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