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# JSON schema
JSON schemata are a powerful tool for expressing the expected structure of your input. You can use it to validate your input before you even send it to your C++ backend, which will result in better UX.
It can also be used for code generation. For instance, tools such as https://app.quicktype.io/ allow you to generate code in multiple programming languages from the JSON schema (even though the validations are usually omitted).
If you are interacting with Python, we warmly recommend https://docs.pydantic.dev/latest/integrations/datamodel_code_generator/. This allows you to generate Pydantic dataclasses, including the validation, from the JSON schema.
Note that this is only supported for JSON, not for other formats.
## Basic idea
Suppose you have a struct like this:
```cpp
struct Person {
std::string first_name;
std::string last_name;
rfl::Email email;
std::vector<Person> children;
float salary;
};
```
You can generate a JSON schema like this:
```cpp
const std::string json_schema = rfl::json::to_schema<Person>(rfl::json::pretty);
```
You do not have to pass `rfl::json::pretty`, but for the purposes of this documentation it is better to do so.
This will result in the following JSON schema:
```json
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$ref": "#/definitions/Person",
"definitions": {
"Person": {
"type": "object",
"properties": {
"children": {
"type": "array",
"items": {
"$ref": "#/definitions/Person"
}
},
"email": {
"type": "string",
"pattern": "^[a-zA-Z0-9._%+\\-]+@[a-zA-Z0-9.\\-]+\\.[a-zA-Z]{2,}$"
},
"first_name": {
"type": "string"
},
"last_name": {
"type": "string"
},
"salary": {
"type": "number"
}
},
"required": [
"children",
"email",
"first_name",
"last_name",
"salary"
]
}
}
}
```
You can insert this into the tools mentioned above and see the generated code.
## Adding descriptions
JSON schemata also often contain descriptions. reflect-cpp supports this as well.
```cpp
struct Person {
std::string first_name;
std::string last_name;
rfl::Description<"Must be a proper email in the form xxx@xxx.xxx.",
rfl::Email>
email;
rfl::Description<
"The person's children. Pass an empty array for no children.",
std::vector<Person>>
children;
float salary;
};
```
```cpp
const std::string json_schema = rfl::json::to_schema<Person>(rfl::json::pretty);
```
```json
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$ref": "#/definitions/Person",
"definitions": {
"Person": {
"type": "object",
"properties": {
"children": {
"type": "array",
"description": "The person's children. Pass an empty array for no children.",
"items": {
"$ref": "#/definitions/Person"
}
},
"email": {
"type": "string",
"description": "Must be a proper email in the form xxx@xxx.xxx.",
"pattern": "^[a-zA-Z0-9._%+\\-]+@[a-zA-Z0-9.\\-]+\\.[a-zA-Z]{2,}$"
},
"first_name": {
"type": "string"
},
"last_name": {
"type": "string"
},
"salary": {
"type": "number"
}
},
"required": [
"children",
"email",
"first_name",
"last_name",
"salary"
]
}
}
}
```
You also add a description to the entire JSON schema:
```cpp
const std::string json_schema = rfl::json::to_schema<
rfl::Description<"JSON schema that describes the required "
"attributes for the person class.",
Person>>(rfl::json::pretty);
```
```json
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$ref": "#/definitions/Person",
"description": "JSON schema that describes the required attributes for the person class.",
"definitions": {
"Person": {
"type": "object",
"properties": {
"children": {
"type": "array",
"description": "The person's children. Pass an empty array for no children.",
"items": {
"$ref": "#/definitions/Person"
}
},
"email": {
"type": "string",
"description": "Must be a proper email in the form xxx@xxx.xxx.",
"pattern": "^[a-zA-Z0-9._%+\\-]+@[a-zA-Z0-9.\\-]+\\.[a-zA-Z]{2,}$"
},
"first_name": {
"type": "string"
},
"last_name": {
"type": "string"
},
"salary": {
"type": "number"
}
},
"required": [
"children",
"email",
"first_name",
"last_name",
"salary"
]
}
}
}
```
|
