An open API service indexing awesome lists of open source software.

https://github.com/pearmaster/json-schema-codegen

Generate C++ or Python3 code from JSON-Schema
https://github.com/pearmaster/json-schema-codegen

Last synced: 2 months ago
JSON representation

Generate C++ or Python3 code from JSON-Schema

Awesome Lists containing this project

README

          

# JSON-Schema Codegen

This python library consumes JSON-Schema and generates C++ or Python code. It generates structures to hold the values defined in the schema, restricting the values according to the schema.

## Python Requirements for Code Generation

These requirements should be satisfied when `pip3` installing `json-schema-codegen`.

* python 3.7
* jinja2
* stringcase

## Installation

```sh
pip3 install json-schema-codegen
```

## C++ Generated Code

### Supported Schema Features in C++ code generation

A C++ class is generated for each schema node according to the schema's `type` property. Schemas without a `type` property, with the exception of combining operators `*Of`, are not supported.

* type: string
* minLength
* maxLength
* pattern
* format=date-time (enforces ISO8601 format)
* format=uuid (enables string object to be populated with a uuid)
* type: string with enum
* type: integer
* maximum
* minimum
* exclusiveMaximum
* exclusiveMinimum
* multipleOf
* type: number
* maximum
* minimum
* exclusiveMaximum
* exclusiveMinimum
* multipleOf
* type: boolean
* type: null
* type: array
* items
* minItems
* maxItems
* type: object
* properties
* required
* allOf
* anyOf
* oneOf

##### References

`$ref` references are supported for array items, object properties, allOf, anyOf, and oneOf. However, the caller must provide a "resolver" class which translates the reference into a class name and namespace.

### Dependencies of the C++ generated code

* boost (boost::optional and boost::variant among others)
* rapidjson 1.1
* C++11

### Usage
See [example_usage.py](./examples/example_usage.py) for a more elaborate example on generating C++ code.

```py
import jsonschemacodegen.cpp as cpp

simpleResolver = cpp.SimpleResolver()
output_dir = "/tmp"

generator = cpp.GeneratorFromSchema(src_output_dir=output_dir,
header_output_dir=output_dir,
resolver=simpleResolver,
namespace=[],
src_usings=[])

sampleSchema = {"type": "string"}

generator.Generate(sampleSchema, 'Example', 'example')
```

## Python Generated Code

A Python3 class is generated for each schema node; the class encapsulating the data described by the schema. The class accepts in its constructor python primative data types that match the format described the the schema. Each class has a `Serializable` method which returns data in a format that can be serialized.

JSON (de-)serialization does not happen in the actual class. This allows for flexibility to use other line-formats, for example, YAML.

### Supported schema features for generating Python code

* type: string
* minLength
* maxLength
* pattern
* enum
* type: integer
* maximum
* minimum
* exclusiveMaximum
* exclusiveMinimum
* multipleOf
* enum
* type: number
* maximum
* minimum
* exclusiveMaximum
* exclusiveMinimum
* multipleOf
* enum
* type: boolean
* type: null
* type: array
* items
* minItems
* maxItems
* type: object
* properties
* required
* allOf
* anyOf
* oneOf
* Component schemas with the `title` property.

### Example usage for generating Python code

For a more elaborate example, see [example_python.py](./examples/example_python.py)

```py
from jsonschemacodegen import python as pygen
import json

with open('schema.json') as fp:
generator = pygen.GeneratorFromSchema('output_dir')
generator.Generate(json.load(fp), 'Example', 'example')
```

This example will create the file `output_dir/example.py` containing the Python3 class `Example` and nested classes as required.

Using the generated code looks like this:
```py
import example
import json

jsonText = '["an example string in an array"]'

obj = example.Example(json.loads(jsonText))

print(json.dumps(obj, default=lambda x: x.Serializable()))
```

## License

GPLv2