Metadata-Version: 2.1
Name: pure-protobuf
Version: 1.1.0
Summary: Python implementation of Protocol Buffers data types with dataclasses support
Home-page: https://github.com/eigenein/protobuf
Author: Pavel Perestoronin
Author-email: eigenein@gmail.com
License: UNKNOWN
Description: # `pure-protobuf`
        
        Python implementation of [Protocol Buffers](http://code.google.com/apis/protocolbuffers/docs/encoding.html) data types.
        
        [![Build Status](https://travis-ci.org/eigenein/protobuf.svg?branch=master)](https://travis-ci.org/eigenein/protobuf)
        [![Coverage Status](https://coveralls.io/repos/github/eigenein/protobuf/badge.svg?branch=master)](https://coveralls.io/github/eigenein/protobuf?branch=master)
        [![PyPI - Downloads](https://img.shields.io/pypi/dm/pure-protobuf.svg)](https://pypi.org/project/pure-protobuf/)
        [![PyPI – Version](https://img.shields.io/pypi/v/pure-protobuf.svg)](https://pypi.org/project/pure-protobuf/#history)
        [![PyPI – Python](https://img.shields.io/pypi/pyversions/pure-protobuf.svg)](https://pypi.org/project/pure-protobuf/#files)
        [![License](https://img.shields.io/pypi/l/pure-protobuf.svg)](https://github.com/eigenein/protobuf/blob/master/LICENSE)
        
        ## Dataclasses
        
        `pure-protobuf` allows you to take advantages of the standard [`dataclasses`](https://docs.python.org/3/library/dataclasses.html) module to define message types. It is preferred over the legacy interface for new projects. The dataclasses interface is available in Python 3.6 and higher.
        
        The legacy interface is deprecated and still available via `pure_protobuf.legacy`.
        
        This guide describes how to use `pure-protobuf` to structure your data. It tries to follow [the standard developer guide](https://developers.google.com/protocol-buffers/docs/proto3). It also assumes that you're familiar with Protocol Buffers.
        
        ### Defining a message type
        
        Let's look at [the simple example](https://developers.google.com/protocol-buffers/docs/proto3#simple). Here's how it looks like in `proto3` syntax:
        
        ```proto
        syntax = "proto3";
        
        message SearchRequest {
          string query = 1;
          int32 page_number = 2;
          int32 result_per_page = 3;
        }
        ```
        
        And this is how you define it with `pure-protobuf`:
        
        ```python
        # Python 3.6+
        
        from dataclasses import dataclass
        
        from pure_protobuf.dataclasses_ import field, message
        from pure_protobuf.types import int32
        
        
        @message
        @dataclass
        class SearchRequest:
            query: str = field(1, default='')
            page_number: int32 = field(2, default=int32(0))
            result_per_page: int32 = field(3, default=int32(0))
           
        
        assert SearchRequest(
            query='hello',
            page_number=int32(1),
            result_per_page=int32(10),
        ).dumps() == b'\x0A\x05hello\x10\x01\x18\x0A'
        ```
        
        Keep in mind that `@message` decorator should **always** stay on top of `@dataclass`.
        
        ### Serializing
        
        Each class wrapped with `@message` gets two methods attached:
        - `dumps() -> bytes` to serialize message into a byte string
        - `dump(io: IO)` to serialize message into a file-like object
        
        ### Deserializing
        
        Each classes wrapped with `@message` gets two class methods attached:
        - `loads(bytes_: bytes) -> TMessage` to deserialize a message from a byte string
        - `load(io: IO) -> TMessage` to deserialize a message from a file-like object
        
        These methods are also available as standalone functions in `pure_protobuf.dataclasses_`:
        - `load(cls: Type[T], io: IO) -> T`
        - `loads(cls: Type[T], bytes_: bytes) -> T`
        
        ### Specifying field types
        
        In `pure-protobuf` types are specified with [type hints](https://www.python.org/dev/peps/pep-0484/). Native Python `float`, `str`, `bytes` and `bool` types are supported. Since other Protocol Buffers types don't exist as native Python types, the package uses [`NewType`](https://docs.python.org/3/library/typing.html#newtype) to define them. They're available via `pure_protobuf.types` and named in the same way.
        
        ### Assigning field numbers
        
        Field numbers are provided via the `metadata` parameter of the [`field`](https://docs.python.org/3/library/dataclasses.html#dataclasses.field) function: `field(..., metadata={'number': number})`. However, to improve readability and save some characters, `pure-protobuf` provides a helper function `pure_protobuf.dataclasses_.field` which accepts field number as the first positional parameter and just passes it to the standard `field` function.
        
        ### Specifying field rules
        
        `typing.List` and `typing.Iterable` annotations are automatically converted to repeated fields. Repeated fields of scalar numeric types use packed encoding by default:
        
        ```python
        # Python 3.6+
        
        from dataclasses import dataclass
        from typing import List
        
        from pure_protobuf.dataclasses_ import field, message
        from pure_protobuf.types import int32
        
        
        @message
        @dataclass
        class Message:
            foo: List[int32] = field(1, default_factory=list)
        ```
        
        It's also possible to wrap a field type with [`typing.Optional`](https://docs.python.org/3/library/typing.html#typing.Optional). If `None` is assigned to an `Optional` field, then the field will be skipped during serialization.
        
        ### Default values
        
        In `pure-protobuf` it's developer's responsibility to take care of default values. If encoded message does not contain a particular element, the corresponding field stays unassigned. It means that the standard `default` and `default_factory` parameters of the `field` function work as usual.
        
        ### Enumerations
        
        Subclasses of the standard [`IntEnum`](https://docs.python.org/3/library/enum.html#intenum) class are supported:
        
        ```python
        # Python 3.6+
        
        from dataclasses import dataclass
        from enum import IntEnum
        
        from pure_protobuf.dataclasses_ import field, message
        
        
        class TestEnum(IntEnum):
            BAR = 1
        
        
        @message
        @dataclass
        class Test:
            foo: TestEnum = field(1)
        
        
        assert Test(foo=TestEnum.BAR).dumps() == b'\x08\x01'
        assert Test.loads(b'\x08\x01') == Test(foo=TestEnum.BAR)
        ```
        
        ### Using other message types
        
        Embedded messages are defined the same way as normal dataclasses:
        
        ```python
        # Python 3.6+
        
        from dataclasses import dataclass
        
        from pure_protobuf.dataclasses_ import field, message
        from pure_protobuf.types import int32
        
        
        @message
        @dataclass
        class Test1:
            a: int32 = field(1, default=0)
        
        
        @message
        @dataclass
        class Test3:
            c: Test1 = field(3, default_factory=Test1)
        
        
        assert Test3(c=Test1(a=int32(150))).dumps() == b'\x1A\x03\x08\x96\x01'
        ```
        
        ### Well-known message types
        
        `pure_protobuf.google` also provides built-in definitions for the following [well-known message types](https://developers.google.com/protocol-buffers/docs/reference/google.protobuf):
        
        | Annotation   | `pure_protobuf.types.google` | `.proto`    |
        | ------------ | ---------------------------- | ----------- |
        | `datetime`   | `Timestamp`                  | `Timestamp` |
        | `timedelta`  | `Duration`                   | `Duration`  |
        | `typing.Any` | `Any_`                       | `Any`       |
        
        They're handled automatically, you have nothing to do but use them normally in type hints:
        
        ```python
        # Python 3.6+
        
        from dataclasses import dataclass
        from datetime import datetime
        from typing import Optional
        
        from pure_protobuf.dataclasses_ import field, message
        
        
        @message
        @dataclass
        class Test:
            timestamp: Optional[datetime] = field(1, default=None)
        ```
        
        #### [`Any`](https://developers.google.com/protocol-buffers/docs/proto3#any)
        
        Since `pure-protobuf` is not able to download or parse `.proto` definitions, it provides a limited implementation of the [`Any`](https://developers.google.com/protocol-buffers/docs/proto3#any) message type. That is, you still have to define all message classes in the usual way. Then, `pure-protobuf` will be able to import and instantiate an encoded value:
        
        ```python
        # Python 3.6+
        
        from dataclasses import dataclass
        from typing import Any, Optional
        
        from pure_protobuf.dataclasses_ import field, message
        from pure_protobuf.types.google import Timestamp
        
        
        @message
        @dataclass
        class Message:
            value: Optional[Any] = field(1)
        
        
        # Here `Timestamp` is used just as an example, in principle any importable user type works.
        message = Message(value=Timestamp(seconds=42))
        assert Message.loads(message.dumps()) == message
        ```
        
        ## Legacy interface
        
        The legacy interface is deprecated and stays in "maintanance mode" for Python 2 users. New projects should strongly consider using the dataclasses.
        
        Assume you have the following definition:
        
        ```proto
        message Test2 {
          string b = 2;
        }
        ```
            
        This is how you can create a message and get it serialized:
        
        ```python
        from io import BytesIO
        
        from pure_protobuf.legacy import MessageType, Unicode
        
        # Create the type instance and add the field.
        type_ = MessageType()
        type_.add_field(2, 'b', Unicode)
        
        message = type_()
        message.b = 'testing'
        
        # Dump into a string.
        assert message.dumps() == b'\x12\x07testing'
        
        # Dump into a file-like object.
        fp = BytesIO()
        message.dump(fp)
        
        # Load from a string.
        assert type_.loads(message.dumps()) == message
        
        # Load from a file-like object.
        fp.seek(0)
        assert type_.load(fp) == message
        ```
        
        ### Required field
        
        To add a missing field you should pass an additional `flags` parameter to `add_field` like this:
        
        ```python
        from pure_protobuf.legacy import Flags, MessageType, Unicode
        
        type_ = MessageType()
        type_.add_field(2, 'b', Unicode, flags=Flags.REQUIRED)
        
        message = type_()
        message.b = 'hello, world'
        
        assert type_.dumps(message)
        ```
            
        If you'll not fill in a required field, then `ValueError` will be raised during serialization.
        
        ### Repeated field
        
        ```python
        from pure_protobuf.legacy import Flags, MessageType, UVarint
        
        type_ = MessageType()
        type_.add_field(1, 'b', UVarint, flags=Flags.REPEATED)
        
        message = type_()
        message.b = (1, 2, 3)
        
        assert type_.dumps(message)
        ```
            
        Value of a repeated field can be any iterable object. The loaded value will always be `list`.
        
        ### Packed repeated field
        
        ```python
        from pure_protobuf.legacy import Flags, MessageType, UVarint
        
        type_ = MessageType()
        type_.add_field(4, 'd', UVarint, flags=Flags.PACKED_REPEATED)
        
        message = type_()
        message.d = (3, 270, 86942)
        
        assert type_.dumps(message)
        ```
            
        ### Embedded messages
        
        ```proto
        message Test1 {
          int32 a = 1;
        }
        
        message Test3 {
          required Test1 c = 3;
        }
        ```
            
        To create an embedded field, wrap inner type with `EmbeddedMessage`:
        
        ```python
        from pure_protobuf.legacy import EmbeddedMessage, MessageType, UVarint
        
        inner_type = MessageType()
        inner_type.add_field(1, 'a', UVarint)
        outer_type = MessageType()
        outer_type.add_field(3, 'c', EmbeddedMessage(inner_type))
        
        message = outer_type()
        message.c = inner_type()
        message.c.a = 150
        
        assert outer_type.dumps(message)
        ```
            
        ### Data types
        
        | Type      | Python  | Description                        |
        |-----------|---------|------------------------------------|
        | `UVarint` | `int`   | unsigned integer (variable length) |
        | `Varint`  | `int`   | signed integer (variable length)   |
        | `Bool`    | `bool`  | boolean                            |
        | `Fixed64` | `bytes` | 8-byte string                      |
        | `UInt64`  | `int`   | C 64-bit `unsigned long long`      |
        | `Int64`   | `int`   | C 64-bit `long long`               |
        | `Float64` | `float` | C `double`                         |
        | `Fixed32` | `bytes` | 4-byte string                      |
        | `UInt32`  | `int`   | C 32-bit `unsigned int`            |
        | `Int32`   | `int`   | C 32-bit `int`                     |
        | `Float32` | `float` | C `float`                          |
        | `Bytes`   | `bytes` | byte string                        |
        | `Unicode` | `str`   | unicode string                     |
        
        ### Some techniques
        
        #### Streaming messages
        
        The Protocol Buffers format is not self-delimiting. But you can wrap your message type with `EmbeddedMessage` and write or read messages sequentially.
        
        #### `add_field` chaining
        
        `add_field` return the message type itself, thus you can do so:
        
        ```python
        from pure_protobuf.legacy import EmbeddedMessage, MessageType, UVarint
        
        MessageType().add_field(1, 'a', EmbeddedMessage(MessageType().add_field(1, 'a', UVarint)))
        ```
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: MIT License
Description-Content-Type: text/markdown
Provides-Extra: dev
