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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 :: 3"
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        "description": "# Hydras\n\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\nHydras versions up to (and including) `v2.*` supported both Python2 and Python3.\nNewer version dropped Python2 support entirely.\n\n## Roadmap\n\nThis a list of features we want to implement before releasing Hydras 3.0\n\n* Add a bitfield-implementation\n* Enum as bit-flags\n\nContributions are welcome.\n\n## Example\n\nThe 'examples' directory is old, not informative, and in pretty bad shape, but the CI does make sure\nthat the code there is working.\n\nInstead, here's \n\n```python\nfrom hydras import *\n\n\nclass Opcodes(Enum, underlying_type=u8):\n    KEEP_ALIVE = 3\n    DATA = 15\n\nclass Header(Struct):\n    opcode = Opcodes\n    data_length = u32\n\nclass DataPacket(Struct):\n    # A nested structure. \"data_length = 128\" sets the default DataLength value for `Header`s inside `DataPacket`s\n    header = Header(dict(opcode=Opcodes.DATA, \n                         data_length=128))\n\n    # Creates an array of bytes with a length of 128 bytes.\n    payload = u8[128]\n\n    # You can override the constructor, but you must keep an \"overload\" that receives no arguments.\n    # Even without this being defined, the class could have been used the same: `DataPacket(payload=...)`\n    # This constructor also sets the `data_length` property\n    def __init__(self, initial_values: dict = None):\n        # Must call the base ctor in order to initialize the data members\n        super(DataPacket, self).__init__(initial_values)\n\n        if 'payload' in initial_values:\n            self.header.data_length = len(payload)\n\nif __name__ == '__main__':\n    packet = DataPacket()\n\n    # You can transform the object into a byte string using the `serialize` method.\n    zeroes = packet.serialize()  # => b'\\x0f\\x80\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00'\n    # Alternatively,\n    zeroes = bytes(packet)\n\n    # You can also modify the object naturally.\n    packet.payload = bytes(range(128))\n    saw_tooth = packet.serialize()  # => b'\\x0f\\x80\\x00\\x00\\x00\\x00\\x01\\x02\\x03\\x04\\x05\\x06\\x07\\x08\\t\\n\\x0b\\x0c\\r\\x0e\\x0f\\x10\\x11\\x12\\x13\\x14\\x15\\x16\\x17\\x18\\x19\\x1a\\x1b\\x1c\\x1d\\x1e\\x1f !\"#$%&\\'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~\\x7f'\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?\n\nIn the core of the library, there are two types of objects: `Serializer` and `Struct`.\n\n`Serializer` is an object that can convert between common python objects (e.g. `int` and `float`) and to and from `bytes`.\n`Serializer`s are mostly supplied by the library, but can also be written by the user.\n\nA simple example of a `Serializer` is `u8`; a more complex example is `EnumClass` which requires more user involvement.\n\n`Struct` is an aggregate of named members, where each has a concrete type associated with it (which is either a `Serializer` or another `Struct`).\n\n`Struct`s are always defined by the user.\n\nThe developer can thus declare a struct using the following notation:\n\n```python\nclass <StructName>(Struct):\n    <member_name> = <StructType|SerializerType>(<default_value>)\n```\n\nFor example:\n\n```python\nclass Message(Struct):\n  TimeOfDay = u64          # This creates a u64 formatter. Parentheses are optional.\n  DataLength = u8(128)     # A default value is optional\n\nMessage().serialize() #=> b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x80'\n```\n\n## Types\n\n### Primitive Types\n\n\"Primitive\" types are integers and floating-point numbers, and are named similarly to Rust's primitive types.\n\nIntegers come in signed and unsigned variants with bitsizes of 8, 16, 32, 64: `u8, i8, u16, etc...`\n\nFloating point are named `f32` and `f64`.\n\nWhen serializing, the endianness of a primitive is set to that of the \"target\" arch (as configured by the user); \nthe user can instead specify field-specific endianness by using the `_be` or `_le` variants (e.g. `u32_be`).\n\n### Enums\n\nEnums are closed sets of named values. By default they are serialized as if their underlying type is `u32` \n\n```python\nfrom hydras import *\n\n\nclass MyEnum(Enum):\n    a = 1\n    b = auto()\n    c = 10\n    d = auto()\n\nclass SmallerEnum(Enum, underlying_type=u8):\n    a = 1\n    b = auto()\n    c = 10\n    d = auto()\n\nclass MyStruct(Struct):\n    e = MyEnum\n    se = SmallerEnum(SmallerEnum.c)\n\nif __name__ == '__main__':\n    print(MyStruct().serialize())  # => b'\\x01\\x00\\x00\\x00\\x0C'\n```\n\n### Arrays\n\nAn array can be created by appending a `[size]` or `[min_size:max_size]` to another type.\nThe type of a `serializer[size]` expression is itself a serializer type.\n\nThe python-value of an array can be either `list` or a `tuple`; if the value is shorter than\nthat of the array, it will be padded with zeroes on serialization.\n\nWhen the type of the array is u8, the python value can also be `bytes` and `bytearray`. \n\nFor example:\n\n```python\nfrom hydras import *\nclass Foo(Struct):\n    # Fixed length-arrays\n    byte_array = u8[32]\n    array_with_uniform_default_value = u16(57)[4]\n    array_with_nonuniform_default_value = u16[4]([1, 2, 3, 4])\n\n\nif __name__ == '__main__':\n    f = Foo()\n    f.byte_array = b'123'  # This will be padded with zeroes\n```\n\nIf the default value of the array is a `bytes` or `bytearray` object, Hydras will deserialize to that type.\n\n```python\nfrom hydras import *\nclass Bar(Struct):\n    byte_array = u8[4](default_value=bytearray())\n\n\nif __name__ == '__main__':\n    print(Bar.deserialize(b'\\x00\\x11\\x22\\x33').byte_array)\n    # => bytearray(b'\\x00\\x01\\x02\\x03')\n```\n\nVariable-length arrays can be created by giving a slice as the size of the array.\n\n```python\n# Variable-length array with at least 5 members\nu8[5:]\n# Variable-length array with up to 5 members (inclusive)\nu8[:5]\n# Variable-length array with between 6 and 8 members\nu8[6:8]\n# Unbound array\nu8[:]\n```\n\nVariable-length arrays, being VSTs (read more below), must be placed last in a struct.\nWhen deserializing, the tail of the buffer will be given to the array to parse. \nThe tail must match the VLA's size specification or an error will be raised.\n\n### Variable-length types\n\nVariable-length types (VST) can only be placed as the last member of a struct. \n\nThe most basic variable-length type is a VLA (Variable-length array; seen above).\nA struct whose last member is a VST is also a VST.\n\n### Mixins ###\nWith `Mixin`s, you can copy one struct's fields into another, losing the first structs identity.\nYou can also prefix the the implanted fields' names with a constant string.\n```python\nclass Aggregate(Struct):\n    version = u8\n\nclass Struct1(Struct):\n    magic = u32\n    _ag = Mixin(Aggregate)\n\nclass Struct2(Struct):\n    magic = u32\n    version = u16\n    _ag = Mixin(Aggregate, prefix='agg_')\n\nassert list(Struct1._hydras_members()) == ['magic', 'version']\nassert list(Struct2._hydras_members()) == ['magic', 'version', 'agg_version']\n``` \n\n## Endianness\n\nIntegral fields not suffixed with `_be` or `_le` will take the endianness of the \"target\".\nThe target endian by default is the same as that of the host machine, but can be configured by modifying `HydraSettings`\nor by specifying serialization-time settings.\n\n## Validators\n\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 = i8(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\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\n\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 = i8(0, validator=lambda value: value % 3 == 0)\n```\n\n## Hooks\n\nA `Struct` derived class can implement hooks.\n\n### before_serialize\n\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\n\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\n\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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