protobuf_to_pydantic 0.0.1

Convert Protobuf-generated Python objects to Pydantic.BaseModel objects with parameter checksum

protobuf_to_pydantic

Convert Protobuf-generated Python objects to Pydantic.BaseModel objects with parameter checksum

NOTE: Only support proto3

1.installation

pip install protobuf_to_pydantic

2.Quick Start

2.1gen runtime obj

protobuf_to_pydantic can generate the corresponding pydantic.BaseModel object at runtime based on the Message object.

For example, the User Message in the following Protobuf file:

syntax = "proto3";
package user;

enum SexType {
  man = 0;
  women = 1;
}

message UserMessage {
  string uid=1;
  int32 age=2;
  float height=3;
  SexType sex=4;
  bool is_adult=5;
  string user_name=6;
}

protobuf to pydantic can read the corresponding Python object at runtime and convert it to the corresponding pydantic.Base Model:

from typing import Type
from protobuf_to_pydantic import msg_to_pydantic_model
from pydantic import BaseModel

# import protobuf gen python obj
from example.python_example_proto_code.example_proto.demo import demo_pb2


UserModel: Type[BaseModel] = msg_to_pydantic_model(demo_pb2.UserMessage)
print(
    {
        k: v.field_info
        for k, v in UserModel.__fields__.items()
    }
)

# output
# {
#   'uid': FieldInfo(default='', extra={}), 
#   'age': FieldInfo(default=0, extra={}), 
#   'height': FieldInfo(default=0.0, extra={}), 
#   'sex': FieldInfo(default=0, extra={}),
#   'is_adult': FieldInfo(default=False, extra={}), 
#   'user_name': FieldInfo(default='', extra={})
#  }

2.2.validate

The message generated according to protobuf carries very little information, and there is not enough information to make the generated pydantic.Base Model with parameter verification function.

At present, protobuf to pydantic obtains other information of Message in three ways, so that the generated pydantic.Base Model object has the function of parameter verification.

2.2.1.Text Comment

使用者可以在protobuf文件中为每个字段编写符合protobuf_to_pydantic要求的注释来为protobuf_to_pydantic提供参数校验信息，比如下面这个例子

syntax = "proto3";
package user;

enum SexType {
  man = 0;
  women = 1;
}

// user info
message UserMessage {
  // p2p: {"miss_default": true, "example": "10086"}
  // p2p: {"title": "UID"}
  string uid=1; // p2p: {"description": "user union id"}
  // p2p: {"example": 18, "title": "use age", "ge": 0}
  int32 age=2;
  // p2p: {"ge": 0, "le": 2.5}
  float height=3;
  SexType sex=4;
  bool is_adult=5;
  // p2p: {"description": "user name"}
  // p2p: {"default": "", "min_length": 1, "max_length": "10", "example": "so1n"}
  string user_name=6;
}

在这个例子中，每个可以被protobuf_to_pydantic使用的注释都是以p2p:开头，并在后面跟着一个完整的Json字符串，这个字符串里面的都是对应字段的校验信息。 比如UserMessage中的uid附带了如下4个信息：

• miss_default: 表示生成的字段不带有默认值
• example: 表示生成的字段的示例值为10086
• title: 表示字段的名称为UID
• description: 表示字段的文档描述为user union id

Note: 目前只支持单行注释且一个完整的Json数据不能换行。

当拥有这些信息后，protobuf_to_pydantic在把Message生成对应的Pydantic.BaseModel对象时都会为每个字段带上对应的信息，如下:

from typing import Type
from protobuf_to_pydantic import msg_to_pydantic_model
from pydantic import BaseModel

# import protobuf gen python obj
from example.python_example_proto_code.example_proto.demo import demo_pb2

UserModel: Type[BaseModel] = msg_to_pydantic_model(demo_pb2.UserMessage, parse_msg_desc_method=demo_pb2)
print(
    {
        k: v.field_info
        for k, v in UserModel.__fields__.items()
    }
)
# output
# {
#   'uid': FieldInfo(default=PydanticUndefined, title='UID', description='user union id', extra={'example': '10086'}), 
#   'age': FieldInfo(default=0, title='use age', ge=0, extra={'example': 18}), 
#   'height': FieldInfo(default=0.0, ge=0, le=2, extra={}), 
#   'sex': FieldInfo(default=0, extra={}), 
#   'is_adult': FieldInfo(default=False, extra={}), 
#   'user_name': FieldInfo(default='', description='user name', min_length=1, max_length=10, extra={'example': 'so1n'})
# }

2.2.1.By pyi file

由于Python中负责把protobuf文件专为Python代码时并不会把Message的注释带到生成的Python代码中，所以在上面的示例通过把Message对象所属的模块传入parse_msg_desc_method中， 使得protobuf_to_pydantic可以通过读取Message对应的pyi文件的注释来获取Message对象的附加信息。

from typing import Type
from protobuf_to_pydantic import msg_to_pydantic_model
from pydantic import BaseModel

# import protobuf gen python obj
from example.python_example_proto_code.example_proto.demo import demo_pb2

UserModel: Type[BaseModel] = msg_to_pydantic_model(demo_pb2.UserMessage, parse_msg_desc_method=demo_pb2)
print(
    {
        k: v.field_info
        for k, v in UserModel.__fields__.items()
    }
)
# output
# {
#   'uid': FieldInfo(default=PydanticUndefined, title='UID', description='user union id', extra={'example': '10086'}), 
#   'age': FieldInfo(default=0, title='use age', ge=0, extra={'example': 18}), 
#   'height': FieldInfo(default=0.0, ge=0, le=2, extra={}), 
#   'sex': FieldInfo(default=0, extra={}), 
#   'is_adult': FieldInfo(default=False, extra={}), 
#   'user_name': FieldInfo(default='', description='user name', min_length=1, max_length=10, extra={'example': 'so1n'})
# }

注：该功能需要在通过Protobuf文件生成对应的Python代码时有使用mypy-protobuf插件，且指定的pyi文件输出路径与生成的Python代码路径时，才能生效

2.2.2.By Protobuf file

NOTE: 需要提前安装lark库

如果生成Message的原始Protobuf文件存在与项目中， 那么可以设置parse_msg_desc_method的值为Message生成时指定的根目录路径， 这样protobuf_to_pydantic就可以通过Protobuf生成对应Python对象时指定的路径来获取到Message对象的protobuf文件路径，再通过解析protobuf文件获取到Message的附带信息。

比如protobuf_to_pydantic的项目结构如下:

.protobuf_to_pydantic/
├── example/
│ ├── python_example_proto_code/
│ └── example_proto/
├── protobuf_to_pydantic/
└── / 

其中protobuf文件存放在example/example_proto文件中，然后在example目录下通过如下命令生成protobuf对应的Python代码文件:

python -m grpc_tools.protoc
  --python_out=./python_example_proto_code \
  --grpc_python_out=./python_example_proto_code \
  -I. \

那么此时需要填写的路径就是./protobuf_to_pydantic/example。

from typing import Type
from protobuf_to_pydantic import msg_to_pydantic_model
from pydantic import BaseModel

# import protobuf gen python obj
from example.python_example_proto_code.example_proto.demo import demo_pb2

UserModel: Type[BaseModel] = msg_to_pydantic_model(
    demo_pb2.UserMessage, parse_msg_desc_method="./protobuf_to_pydantic/example"
)
print(
    {
        k: v.field_info
        for k, v in UserModel.__fields__.items()
    }
)
# output
# {
#   'uid': FieldInfo(default=PydanticUndefined, title='UID', description='user union id', extra={'example': '10086'}), 
#   'age': FieldInfo(default=0, title='use age', ge=0, extra={'example': 18}), 
#   'height': FieldInfo(default=0.0, ge=0, le=2, extra={}), 
#   'sex': FieldInfo(default=0, extra={}), 
#   'is_adult': FieldInfo(default=False, extra={}), 
#   'user_name': FieldInfo(default='', description='user name', min_length=1, max_length=10, extra={'example': 'so1n'})
# }

2.2.2.Protobuf Field Option(PGV)

2.2.3.By PGV

Note 正在开发中...

这是最推荐的方式，该方式参考了protoc-gen-validate项目，大多数Protobuf文件API参考了protoc-gen-validate项目

2.2.4.其它参数支持

protobuf_to_pydantic除了支持FieldInfo的参数外，还支持下面几种参数:

• miss_default：默认情况下，生成对应pydantic.BaseModel对象中每个字段的默认值与Message中每个字段的默认值是一样的。不过可以通过设置miss_default为true来取消默认值的设置，需要注意的是在设置miss_default为true的情况下，default参数将失效。
• enable: 默认情况下， pydantic.BaseModel会把Message中的每个字段都进行转换，如果有些字段不想被转换，可以设置enable为false

Note FieldInfo支持的参数见:https://pydantic-docs.helpmanual.io/usage/types/#constrained-types

2.3.gen python code

In addition to generating the corresponding pydantic.Base Model object at runtime, protobuf to pydantic supports converting the runtime pydantic.Base Model object to Python code text (only applicable to protobuf to pydantic generated pydantic.Base Model object),

Among them, protobuf_to_pydantic.pydantic_model_to_py_code is used to generate code text, protobuf_to_pydantic.pydantic_model_to_py_file is used to generate code files, and the example of protobuf_to_pydantic.pydantic_model_to_py_file is as follows:

from protobuf_to_pydantic import msg_to_pydantic_model, pydantic_model_to_py_file

# import protobuf gen python obj
from example.python_example_proto_code.example_proto.demo import demo_pb2

# gen code: url: https://github.com/so1n/protobuf_to_pydantic/blob/master/example/demo_gen_code.py
pydantic_model_to_py_file(
    "./demo_gen_code.py",
    msg_to_pydantic_model(demo_pb2.NestedMessage),
)

# gen code: url: https://github.com/so1n/protobuf_to_pydantic/blob/master/example/demo_gen_code_by_pyi.py 
pydantic_model_to_py_file(
    "./demo_gen_code_by_pyi.py",
    msg_to_pydantic_model(demo_pb2.NestedMessage, parse_msg_desc_method=demo_pb2),
)

# gen code: url: https://github.com/so1n/protobuf_to_pydantic/blob/master/example/demo_gen_code_by_protobuf_field.py
pydantic_model_to_py_file(
    "./demo_gen_code_by_protobuf_field.py",
    msg_to_pydantic_model(
        demo_pb2.NestedMessage, parse_msg_desc_method="/home/so1n/github/protobuf_to_pydantic/example"
    ),
)

The specific generated code can be viewed through the corresponding url. It should be noted that if proto buf to pydantic checks that the current environment is installed with isort and autoflake, it will format the code through them by default.