prompt-library/development/documentation-generator.md

Documentation Generator

Description

Automatically generates comprehensive documentation from code, including API documentation, README files, inline comments, and user guides. Supports multiple programming languages and documentation formats.

Usage

Provide your code and specify the type of documentation needed. Works best with well-structured code that has clear function/class definitions. Specify the target audience and format requirements.

Prompt

Generate comprehensive documentation for the following code. Please create:

1. **API Documentation**
   - Function/method signatures
   - Parameter descriptions with types
   - Return value specifications
   - Usage examples
   - Error conditions

2. **Inline Comments**
   - Code explanation comments
   - Complex logic breakdown
   - Algorithm descriptions
   - Performance considerations

3. **README Section** (if applicable)
   - Purpose and overview
   - Installation/setup instructions
   - Basic usage examples
   - Configuration options

4. **User Guide Elements**
   - Step-by-step usage instructions
   - Common use cases
   - Troubleshooting tips
   - Best practices

Documentation requirements:
- Target audience: [developers/end-users/technical writers]
- Format: [Markdown/JSDoc/Sphinx/other]
- Documentation style: [comprehensive/concise/beginner-friendly]

Code to document:

[YOUR CODE HERE]

Additional context:
[PROJECT PURPOSE, DEPENDENCIES, SPECIAL REQUIREMENTS]

Example Input

```python
import requests
import json
from typing import Dict, List, Optional

class WeatherAPI:
    def __init__(self, api_key: str, base_url: str = "https://api.weather.com"):
        self.api_key = api_key
        self.base_url = base_url
    
    def get_current_weather(self, city: str, units: str = "metric") -> Dict:
        endpoint = f"{self.base_url}/current"
        params = {
            "city": city,
            "units": units,
            "api_key": self.api_key
        }
        response = requests.get(endpoint, params=params)
        response.raise_for_status()
        return response.json()
    
    def get_forecast(self, city: str, days: int = 5) -> List[Dict]:
        endpoint = f"{self.base_url}/forecast"
        params = {
            "city": city,
            "days": days,
            "api_key": self.api_key
        }
        response = requests.get(endpoint, params=params)
        response.raise_for_status()
        return response.json()["forecast"]

## Example Output

```markdown
# WeatherAPI Documentation

## Overview
The WeatherAPI class provides a simple interface to fetch current weather data and forecasts for any city using a weather service API.

## Installation
```bash
pip install requests

Quick Start

from weather_api import WeatherAPI

# Initialize the API client
weather = WeatherAPI(api_key="your_api_key_here")

# Get current weather
current = weather.get_current_weather("New York")
print(f"Temperature: {current['temperature']}°C")

# Get 7-day forecast
forecast = weather.get_forecast("London", days=7)
for day in forecast:
    print(f"{day['date']}: {day['temperature']}°C, {day['description']}")

API Reference

Class: WeatherAPI

Constructor

WeatherAPI(api_key: str, base_url: str = "https://api.weather.com")

Parameters:

• api_key (str): Your API key for the weather service
• base_url (str, optional): Base URL for the weather API. Defaults to "https://api.weather.com"

Example:

weather = WeatherAPI("your_api_key", "https://custom-weather-api.com")

get_current_weather()

get_current_weather(city: str, units: str = "metric") -> Dict

Retrieves current weather conditions for the specified city.

Parameters:

• city (str): Name of the city to get weather for
• units (str, optional): Temperature units ("metric", "imperial", "kelvin"). Defaults to "metric"

Returns:

• Dict: Weather data containing temperature, humidity, description, etc.

Raises:

• requests.HTTPError: If the API request fails
• requests.ConnectionError: If unable to connect to the API

Example:

weather_data = weather.get_current_weather("Tokyo", units="imperial")
temp_f = weather_data["temperature"]  # Temperature in Fahrenheit

get_forecast()

get_forecast(city: str, days: int = 5) -> List[Dict]

Retrieves weather forecast for the specified city.

Parameters:

• city (str): Name of the city to get forecast for
• days (int, optional): Number of days to forecast (1-10). Defaults to 5

Returns:

• List[Dict]: List of daily forecast data

Raises:

• requests.HTTPError: If the API request fails
• ValueError: If days parameter is outside valid range

Example:

forecast = weather.get_forecast("Paris", days=3)
tomorrow = forecast[1]  # Second day (tomorrow)

Error Handling

All methods may raise HTTP-related exceptions. Implement proper error handling:

try:
    weather_data = weather.get_current_weather("InvalidCity")
except requests.HTTPError as e:
    print(f"API error: {e}")
except requests.ConnectionError:
    print("Unable to connect to weather service")

Best Practices

• Store your API key securely (environment variables)
• Implement rate limiting to avoid API quota issues
• Cache responses when appropriate to reduce API calls
• Validate city names before making requests

## Variations
- **API-Only**: Focus only on API documentation with technical details
- **User Manual**: Create end-user focused documentation with tutorials
- **Inline Comments**: Generate only code comments and docstrings
- **Architecture Docs**: Create high-level system architecture documentation

## Tips
- Include the programming language for language-specific documentation standards
- Specify if you need examples for specific use cases
- Mention any existing documentation standards or tools used in your project
- Provide context about the intended users of the documentation

## Related Prompts
- `code-review.md` - For improving code before documenting
- `architecture-planner.md` - For system-level documentation
- `test-case-generator.md` - For creating documented test examples

## Tags
`documentation` `api-docs` `comments` `readme` `development` `technical-writing`