[English](README.md)|[简体中文](README_ZH.md)
# protobuf-pydantic-gen
A tool for converting between Pydantic models and Protobuf messages, enabling the generation of Pydantic `BaseModel` classes from `.proto` files.
## Features
- Supports conversion of Protobuf basic types to Python basic types.
- Converts Protobuf definition language to Pydantic `BaseModel` classes.
- Converts Protobuf definition language to `sqlmodel` ORM models.
- Implements `to_protobuf` and `from_protobuf` methods for `BaseModel` classes, facilitating bidirectional conversion between Pydantic models and Protobuf messages.
- Allows specifying `Pydantic BaseModel Field` parameters in Protobuf descriptor files.
## Installation
```shell
pip install protobuf-pydantic-gen
```
## Example
```protobuf
syntax = "proto3";
import "google/protobuf/descriptor.proto";
import "protobuf_pydantic_gen/pydantic.proto";
import "google/protobuf/timestamp.proto";
import "google/protobuf/any.proto";
import "constant.proto";
import "example2.proto";
package pydantic_example;
message Nested {
string name = 1[(pydantic.field) = {description: "Name of the example",example: "'ohn Doe",alias: "full_name",default: "John Doe",max_length:128,primary_key:true}];
}
message Example {
option (pydantic.database) = {
as_table: true
table_name: "users",
compound_index:{
indexs:["name","age"],
index_type:"UNIQUE",
name:"uni_name_age"
},
compound_index:{
indexs:["name"],
index_type:"PRIMARY",
name:"index_name"
}
};
string name = 1[(pydantic.field) = {description: "Name of the example",alias: "full_name",default: "John Doe",max_length:128,primary_key:true}];
optional int32 age = 2 [(pydantic.field) = {description: "Age of the example",alias: "years",default: "30"}];
repeated string emails = 3 [(pydantic.field) = {description: "Emails of the example",default:"[]"}];
repeated Example2 examples = 9 [(pydantic.field) = {description: "Nested message",sa_column_type:"JSON"}];
map<string, google.protobuf.Any> entry = 4 [(pydantic.field) = {description: "Properties of the example",default:"{}"}];
Nested nested=8[(pydantic.field) = {description: "Nested message",sa_column_type:"JSON"}];
google.protobuf.Timestamp created_at = 5 [(pydantic.field) = {description: "Creation date of the example",default: "datetime.datetime.now()",required: true}];
ExampleType type = 6 [(pydantic.field) = {description: "Type of the example",default: "ExampleType.TYPE1",sa_column_type:"Enum[ExampleType]"}];
float score = 7 [(pydantic.field) = {description: "Score of the example",default: "0.0",gt: 0.0,le: 100.0,field_type: "Integer"}];
}
```
## Usage
```shell
python3 -m grpc_tools.protoc --proto_path=./protos -I=./protos -I=./ \
--python_out=./pb --pyi_out=./pb --grpc_python_out=./pb --pydantic_out=./models \
"./protos/example.proto"
```
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"description": "[English](README.md)|[\u7b80\u4f53\u4e2d\u6587](README_ZH.md) \n\n# protobuf-pydantic-gen\n\nA tool for converting between Pydantic models and Protobuf messages, enabling the generation of Pydantic `BaseModel` classes from `.proto` files.\n\n## Features\n\n- Supports conversion of Protobuf basic types to Python basic types.\n- Converts Protobuf definition language to Pydantic `BaseModel` classes.\n- Converts Protobuf definition language to `sqlmodel` ORM models.\n- Implements `to_protobuf` and `from_protobuf` methods for `BaseModel` classes, facilitating bidirectional conversion between Pydantic models and Protobuf messages.\n- Allows specifying `Pydantic BaseModel Field` parameters in Protobuf descriptor files.\n\n## Installation\n\n```shell\npip install protobuf-pydantic-gen\n```\n## Example\n```protobuf\nsyntax = \"proto3\";\n\nimport \"google/protobuf/descriptor.proto\";\nimport \"protobuf_pydantic_gen/pydantic.proto\";\nimport \"google/protobuf/timestamp.proto\";\nimport \"google/protobuf/any.proto\";\nimport \"constant.proto\";\nimport \"example2.proto\";\npackage pydantic_example;\nmessage Nested {\n\n string name = 1[(pydantic.field) = {description: \"Name of the example\",example: \"'ohn Doe\",alias: \"full_name\",default: \"John Doe\",max_length:128,primary_key:true}];\n}\nmessage Example {\n option (pydantic.database) = { \n as_table: true\n table_name: \"users\",\n compound_index:{\n indexs:[\"name\",\"age\"],\n index_type:\"UNIQUE\",\n name:\"uni_name_age\"\n },\n compound_index:{\n indexs:[\"name\"],\n index_type:\"PRIMARY\",\n name:\"index_name\"\n }\n };\n\n string name = 1[(pydantic.field) = {description: \"Name of the example\",alias: \"full_name\",default: \"John Doe\",max_length:128,primary_key:true}];\n optional int32 age = 2 [(pydantic.field) = {description: \"Age of the example\",alias: \"years\",default: \"30\"}];\n repeated string emails = 3 [(pydantic.field) = {description: \"Emails of the example\",default:\"[]\"}];\n repeated Example2 examples = 9 [(pydantic.field) = {description: \"Nested message\",sa_column_type:\"JSON\"}];\n map<string, google.protobuf.Any> entry = 4 [(pydantic.field) = {description: \"Properties of the example\",default:\"{}\"}];\nNested nested=8[(pydantic.field) = {description: \"Nested message\",sa_column_type:\"JSON\"}];\n google.protobuf.Timestamp created_at = 5 [(pydantic.field) = {description: \"Creation date of the example\",default: \"datetime.datetime.now()\",required: true}];\n ExampleType type = 6 [(pydantic.field) = {description: \"Type of the example\",default: \"ExampleType.TYPE1\",sa_column_type:\"Enum[ExampleType]\"}];\n float score = 7 [(pydantic.field) = {description: \"Score of the example\",default: \"0.0\",gt: 0.0,le: 100.0,field_type: \"Integer\"}];\n}\n\n```\n## Usage\n\n```shell\npython3 -m grpc_tools.protoc --proto_path=./protos -I=./protos -I=./ \\\n--python_out=./pb --pyi_out=./pb --grpc_python_out=./pb --pydantic_out=./models \\\n\"./protos/example.proto\"\n\n```\n",
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