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    "info": {
        "author": "Gilad Naaman",
        "author_email": "gilad@naaman.io",
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        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 3"
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        "description": "# Hydras #\n[![Build Status](https://travis-ci.org/Gilnaa/Hydras.svg?branch=master)](https://travis-ci.org/Gilnaa/Hydras)\n\n'*Hydras*' is a python library that allows the developer to create structured binary data according to simple rules,\nsomewhat similar to how C does it with a struct.\n\nWhy \"Hydras\"? `Hydra` was taken.\n\n\n## Example ##\n```python\nclass Header(Struct):\n  Opcode = uint8_t(4)       # The `opcode`'s default value will now be `4`\n  DataLength = uint32_t()\n\nclass DataPacket(Struct):\n  # A nested structure. \"DataLength = 128\" sets the default DataLength value for `Header`s inside `DataPacket`s\n  Header = Header(DataLength=128)\n  # Creates an array of bytes with a length of 128 bytes.\n  Payload = Array(length = 128)\n\n  # To override the constructor it must be able to override the default ctor (1 argument)\n  def __init__(self, opcode=0):\n    # Must call the base ctor\n    super(DataPacket, self).__init__()\n    self.Header.Opcode = opcode\n\nif __name__ == '__main__':\n  packet = DataPacket()\n  # After you create the object, you can ignore the formatting rules, and assign the data directly to the properties.\n  packet.Header.Opcode = DATAPACKET_OPCODE\n\n  # You can transform the object into a byte string using the `serialize` method.\n  data_to_send = packet.serialize() # => b'\\x04\\x80\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...'\n  some_socket.send(data_to_send)\n\n  packet.Payload = '\\xFF' * 128\n  data_to_send = packet.serialize() # => b'\\x04\\x80\\x00\\x00\\x00\\xFF\\xFF\\xFF\\xFF\\xFF\\xFF\\xFF\\xFF...'\n\n  # . . .\n\n  # You can parse raw byte strings into an object using the deserialize class method.\n  received_data = some_socket.recv(len(packet))\n  parsed_packet = DataPacket.deserialize(received_data)\n```\n\nYou can find more examples in the examples directory.\n\n## How does it work? ##\nIn the core of the library, there are two types of objects: `TypeFormatter` and `Struct`.\n\n`TypeFormatter` is a formatting object, and can parse and format values of a specified type.\n`Struct` is a structure object, which enables you to define rules for object serialization.\n\nThe developer can thus declare a class using the following notation:\n```python\nclass <StructName>(Struct):\n  <member_name> = <TypeClass>(<default_value>)\n```\nor\n```python\nclass Message(Struct):\n  TimeOfDay = uint64_t      # This creates a u64 formatter. Parentheses are optional.\n  DataLength = uint8_t(128)   # A default value is optional\n\nMessage().serialize() #=> b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x80'\n```\n\nThe declared data members are in fact (due to python's syntax), static.\nWhen a class object is created, the constructor (deep) copies each of the formatters' `default_value`s into an instance variable in the same name,\nso some transparency is achieved by \"tricking\" the user into thinking no formatters are involved:\n```\nClass members:\n  TimeOfDay:  uint64_t (default_value = 0)\n  DataLength: uint8_t  (default_value = 128)\nObject members:\n  TimeOfDay:  0\n  DataLength: 128\n```\n\nWhen the object is serialized, the object's data is cross-referenced with the class's formatters.\nAll of the integers are internally converted using python's `struct.pack` function.\n\n## Validators ##\nA validator object can be assigned to a struct data member to define validation rules.\nWhen deserializing an object from binary data, the framework will validate the values\nusing the user-defined validation-rules.\n\nIf an invalid value is encountered, a ValueError is raised.\n\n```python\nclass MeIsValidated(Struct):\n    member = int8_t(0, validator=RangeValidator(-15, 15))\n\n...\n\nMeIsValidated.deserialize('\\x10')  # => ValueError: The deserialized data is invalid.\n```\n\nThere are a few built-in validators defined for the following rules:\n - RangeValidator: Range check\n - ExactValueValidator: Exact value check\n - BitSizeValidator: Bit-Length check\n - CustomValidator: Lambda validation (receives a user function.)\n - TrueValidator & FalseValidator: Dummy validators (always true / always false)\n\nMore validators can be defined by subclassing the Validator class.\n\n### Lambda Validators ###\nThe user can use a lambda expression (or any function) instead of a validator object as validation rule.\n\n```python\nclass MeIsLambda(Struct):\n    member = int8_t(0, validator=lambda value: value % 3 == 0)\n```\n\n## Hooks ##\nA `Struct` derived class can implement hooks.\n### before_serialize ###\nThis method will be called before a serialization is about to occur.\n\n**Note**: This method will not be called if either `HydraSettings.dry_run` is True,\nor `serialize` is called with `dry_run=True`\n\n### after_serialize ###\nThis method will be called after a serialization has occurd.\n\n**Note**: This method will not be called if either `HydraSettings.dry_run` is True,\nor `serialize` is called with `dry_run=True`\n\n### validate ###\nCalled after a de-serialization is completed.\nIf it returns a `False`y value, the `deserialize` raises an error.\n\nIf not overriden by the user in a custom Struct class, the method\nwill validate using the type formatters' validators.\n\nThe user can, of course, override the method to add custom validations,\nand then invoke the original validate method.\n\n**Note**: No errors will be raised if `HydraSettings.validate` is set to `False`.\n\n\n",
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