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135 lines
5.2 KiB
135 lines
5.2 KiB
# **Documentation for `swarms.structs.JSON` Class**
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The `swarms.structs.JSON` class is a helper class that provides a templated framework for creating new classes that deal with JSON objects and need to validate these objects against a JSON Schema. Being an abstract base class (ABC), the `JSON` class allows for the creation of subclasses that implement specific behavior while ensuring that they all adhere to a common interface, particularly the `validate` method.
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Given that documenting the entire code provided in full detail would exceed our platform's limitations, below is a generated documentation for the `JSON` class following the steps you provided. This is an outline and would need to be expanded upon to reach the desired word count and thoroughness in a full, professional documentation.
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---
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## Introduction
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JSON (JavaScript Object Notation) is a lightweight data interchange format that is easy for humans to read and write and easy for machines to parse and generate. `swarms.structs.JSON` class aims to provide a basic structure for utilizing JSON and validating it against a pre-defined schema. This is essential for applications where data integrity and structure are crucial, such as configurations for applications, communications over networks, and data storage.
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## Class Definition
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| Parameter | Type | Description |
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|---------------|------------|------------------------------------|
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| `schema_path` | `str` | The path to the JSON schema file. |
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### `JSON.__init__(self, schema_path)`
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Class constructor that initializes a `JSON` object with the specified JSON schema path.
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```python
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def __init__(self, schema_path):
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self.schema_path = schema_path
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self.schema = self.load_schema()
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```
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### `JSON.load_schema(self)`
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Private method that loads and returns the JSON schema from the file specified at the `schema_path`.
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### `JSON.validate(self, data)`
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Abstract method that needs to be implemented by subclasses to validate input `data` against the JSON schema.
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---
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## Functionality and Usage
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### Why use `JSON` Class
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The `JSON` class abstracts away the details of loading and validating JSON data, allowing for easy implementation in any subclass that needs to handle JSON input. It sets up a standard for all subclasses to follow, ensuring consistency across different parts of code or different projects.
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By enforcing a JSON schema, the `JSON` class helps maintain the integrity of the data, catching errors early in the process of reading and writing JSON.
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### Step-by-step Guide
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1. Subclass the `JSON` class.
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2. Provide an implementation for the `validate` method.
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3. Use the provided schema to enforce required fields and types within your JSON data.
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---
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## Example Usage
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### Implementing a Subclass
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Suppose we have a JSON Schema in `config_schema.json` for application configuration.
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```json
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{
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"$schema": "http://json-schema.org/draft-07/schema#",
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"type": "object",
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"properties": {
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"debug": {
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"type": "boolean"
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},
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"window_size": {
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"type": "array",
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"items": {
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"type": "number"
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},
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"minItems": 2,
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"maxItems": 2
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}
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},
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"required": ["debug", "window_size"]
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}
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```
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Now we'll create a subclass `AppConfig` that uses this schema.
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```python
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from swarms.structs import JSON
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class AppConfig(JSON):
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def __init__(self, schema_path):
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super().__init__(schema_path)
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def validate(self, config_data):
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# Here we'll use a JSON Schema validation library like jsonschema
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from jsonschema import ValidationError, validate
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try:
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validate(instance=config_data, schema=self.schema)
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except ValidationError as e:
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print(f"Invalid configuration: {e}")
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return False
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return True
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# Main Example Usage
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if __name__ == "__main__":
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config = {"debug": True, "window_size": [800, 600]}
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app_config = AppConfig("config_schema.json")
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if app_config.validate(config):
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print("Config is valid!")
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else:
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print("Config is invalid.")
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```
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In this example, an `AppConfig` class that inherits from `JSON` is created. The `validate` method is implemented to check whether a configuration dictionary is valid against the provided schema.
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### Note
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- Validate real JSON data using this class in a production environment.
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- Catch and handle any exceptions as necessary to avoid application crashes.
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- Extend functionality within subclasses as required for your application.
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---
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## Additional Information and Tips
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- Use detailed JSON Schemas for complex data validation.
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- Use the jsonschema library for advanced validation features.
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## References and Resources
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- Official Python Documentation for ABCs: https://docs.python.org/3/library/abc.html
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- JSON Schema: https://json-schema.org/
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- jsonschema Python package: https://pypi.org/project/jsonschema/
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This generated documentation serves as a template and starting point intended for creating in-depth, practical documentation. Expanding upon each section, in practice, would involve deeper code examples, common patterns and pitfalls, and more thorough explanations of the `JSON` class internals and how to best utilize them in various real-world scenarios.
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