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docs/developer/coding_standards.rst

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+Coding Standards
+===============
+
+This document outlines the coding standards and best practices for contributing to the AI-Writer project.
+
+Code Style
+---------
+
+AI-Writer follows the PEP 8 style guide for Python code with some additional guidelines:
+
+1. **Indentation**
+   
+   * Use 4 spaces for indentation (no tabs)
+   * Continuation lines should align with the opening delimiter or be indented by 4 spaces
+
+2. **Line Length**
+   
+   * Maximum line length is 100 characters
+   * For docstrings and comments, limit to 80 characters
+
+3. **Imports**
+   
+   * Group imports in the following order:
+     1. Standard library imports
+     2. Related third-party imports
+     3. Local application/library specific imports
+   * Within each group, imports should be sorted alphabetically
+   * Use absolute imports rather than relative imports
+
+   Example:
+
+   .. code-block:: python
+
+      # Standard library
+      import os
+      import sys
+      from typing import Dict, List, Optional
+      
+      # Third-party
+      import numpy as np
+      import pandas as pd
+      import streamlit as st
+      
+      # Local
+      from lib.database import models
+      from lib.utils import helpers
+
+4. **Naming Conventions**
+   
+   * Classes: `CamelCase`
+   * Functions and variables: `snake_case`
+   * Constants: `UPPER_CASE`
+   * Private methods and variables: `_leading_underscore`
+   * Protected methods and variables: `__double_leading_underscore`
+
+5. **String Formatting**
+   
+   * Use f-strings for string formatting when possible
+   * For older Python versions, use `.format()` method
+   * Avoid using `%` formatting
+
+   Example:
+
+   .. code-block:: python
+
+      # Preferred
+      name = "World"
+      greeting = f"Hello, {name}!"
+      
+      # Acceptable
+      greeting = "Hello, {}!".format(name)
+      
+      # Avoid
+      greeting = "Hello, %s!" % name
+
+Documentation
+------------
+
+1. **Docstrings**
+   
+   * Use Google-style docstrings
+   * All modules, classes, and functions should have docstrings
+   * Include type hints in function signatures
+
+   Example:
+
+   .. code-block:: python
+
+      def generate_content(prompt: str, max_tokens: int = 100) -> str:
+          """Generate content using the AI model.
+          
+          Args:
+              prompt: The input prompt for content generation.
+              max_tokens: Maximum number of tokens to generate.
+              
+          Returns:
+              The generated content as a string.
+              
+          Raises:
+              ValueError: If the prompt is empty or max_tokens is negative.
+          """
+          if not prompt:
+              raise ValueError("Prompt cannot be empty")
+          
+          if max_tokens < 0:
+              raise ValueError("max_tokens must be a positive integer")
+          
+          # Implementation...
+          return generated_content
+
+2. **Comments**
+   
+   * Use comments sparingly and only when necessary
+   * Focus on explaining "why" rather than "what"
+   * Keep comments up-to-date with code changes
+
+3. **Type Hints**
+   
+   * Use type hints for all function parameters and return values
+   * Use `Optional` for parameters that can be None
+   * Use `Union` for parameters that can be multiple types
+   * Use `Any` only when absolutely necessary
+
+   Example:
+
+   .. code-block:: python
+
+      from typing import Dict, List, Optional, Union
+      
+      def process_data(
+          data: Union[Dict[str, str], List[str]],
+          config: Optional[Dict[str, str]] = None
+      ) -> List[str]:
+          """Process the input data."""
+          # Implementation...
+          return processed_data
+
+Error Handling
+-------------
+
+1. **Exceptions**
+   
+   * Use specific exception types rather than generic exceptions
+   * Handle exceptions at the appropriate level
+   * Include meaningful error messages
+   * Log exceptions with appropriate context
+
+   Example:
+
+   .. code-block:: python
+
+      try:
+          result = api_client.fetch_data(query)
+      except ConnectionError as e:
+          logger.error(f"Failed to connect to API: {e}")
+          raise ServiceUnavailableError("API service is currently unavailable") from e
+      except ValueError as e:
+          logger.warning(f"Invalid query parameter: {e}")
+          raise InvalidParameterError(f"Invalid query parameter: {e}") from e
+
+2. **Validation**
+   
+   * Validate input parameters early
+   * Use assertions for internal checks (not for input validation)
+   * Return meaningful error messages for invalid inputs
+
+Testing
+------
+
+1. **Test Coverage**
+   
+   * Aim for at least 80% test coverage for new code
+   * Write unit tests for all new functions and classes
+   * Include integration tests for complex interactions
+
+2. **Test Organization**
+   
+   * Place tests in the `tests/` directory
+   * Mirror the package structure in the test directory
+   * Name test files with `test_` prefix
+
+3. **Test Naming**
+   
+   * Use descriptive test names that explain what is being tested
+   * Follow the pattern `test_<function_name>_<scenario>_<expected_result>`
+
+   Example:
+
+   .. code-block:: python
+
+      def test_generate_content_empty_prompt_raises_value_error():
+          """Test that generate_content raises ValueError for empty prompts."""
+          with pytest.raises(ValueError, match="Prompt cannot be empty"):
+              generate_content("")
+
+Performance Considerations
+------------------------
+
+1. **Resource Usage**
+   
+   * Be mindful of memory usage, especially for large datasets
+   * Use generators and iterators for large data processing
+   * Consider using async functions for I/O-bound operations
+
+2. **Optimization**
+   
+   * Optimize for readability first, then performance
+   * Document performance-critical sections
+   * Include benchmarks for performance-sensitive code
+
+Security Best Practices
+---------------------
+
+1. **API Keys and Secrets**
+   
+   * Never hardcode API keys or secrets
+   * Use environment variables or secure storage
+   * Implement proper access controls for sensitive data
+
+2. **Input Validation**
+   
+   * Validate and sanitize all user inputs
+   * Use parameterized queries for database operations
+   * Implement proper authentication and authorization
+
+3. **Dependency Management**
+   
+   * Keep dependencies up-to-date
+   * Regularly check for security vulnerabilities
+   * Pin dependency versions for reproducibility