import re
from typing import Dict
from .base import BasePRWaiter, BasePromptBuilder, BasePRAnalyzer


class StandardPRWaiter(BasePRWaiter):
    """Standard PR waiter that checks for basic CI completion."""

    def wait_for_analysis_ready(
        self, github_client, pr_number: int, timeout: int = 600
    ) -> Dict:
        """Wait for CI checks to complete before analysis."""
        # For now, just proceed immediately for general repos
        # In the future, this could check for CI status, required reviews, etc.
        pr_data = github_client.get_pr_details(pr_number)
        return pr_data


class PythonGeneralPromptBuilder(BasePromptBuilder):
    """Python/General code review prompt builder."""

    def __init__(self):
        self.base_prompt = self._get_python_general_prompt_template()

    def _get_python_general_prompt_template(self) -> str:
        """Get the Python/general code review prompt template."""
        return """# Python/General Code Review Prompt

You are an AI assistant tasked with reviewing a pull request for a Python project. You will be given the PR title, description, and code diff. Perform a thorough review, focusing on the following key areas:

1. **Code Quality & Best Practices**
   - Follow Python PEP 8 style guidelines and naming conventions
   - Ensure proper error handling and exception management
   - Check for code clarity, readability, and maintainability
   - Verify appropriate use of Python idioms and patterns
   - Look for potential performance issues or inefficient algorithms
   - Ensure proper documentation (docstrings, comments) where needed

2. **Architecture & Design**
   - Assess if the code follows good software design principles (SOLID, DRY, etc.)
   - Check for proper separation of concerns and modularity
   - Evaluate the overall structure and organization of the code
   - Ensure new functionality integrates well with existing codebase
   - Look for opportunities to reduce complexity and improve maintainability

3. **Security Considerations**
   - Check for potential security vulnerabilities (SQL injection, XSS, etc.)
   - Ensure sensitive data is not exposed in logs or error messages
   - Verify proper input validation and sanitization
   - Check for hardcoded secrets, passwords, or API keys
   - Ensure secure defaults and proper access controls

4. **Testing & Reliability**
   - Verify that new functionality has appropriate test coverage
   - Check if existing tests are updated for changes
   - Look for edge cases that might not be covered
   - Ensure error conditions are properly tested
   - Check that tests are meaningful and not just for coverage

5. **Dependencies & Compatibility**
   - Review any new dependencies added to the project
   - Check for version compatibility issues
   - Ensure dependencies are necessary and well-maintained
   - Look for potential conflicts with existing dependencies
   - Verify that requirements are properly documented

After analyzing the PR against the above points, **separate your feedback into two categories**: **Blocking Issues** and **Suggestions for Improvement**.

- **Blocking Issues** should detail any problems that **must** be addressed before merging. These include security vulnerabilities, breaking changes, test failures, or significant architectural problems.

- **Suggestions for Improvement** should cover optional improvements that would enhance code quality, performance, or maintainability but don't necessarily block the merge.

**Tone and style**: Present your feedback in a **constructive and helpful manner**. Focus on explaining the reasoning behind suggestions and provide specific examples or alternatives where possible.

**Output format**: Use clear markdown formatting with headers for "Blocking Issues" and "Suggestions for Improvement". If there are no blocking issues, state "No blocking issues found" before proceeding to suggestions.

PR Title:
{pr_title}

PR Description:
{pr_body}

Code Changes:
{diff}

Comments (if any):
{comments}
"""

    def build_prompt(self, pr_data: Dict) -> str:
        """Build the complete prompt with PR data."""
        return self.base_prompt.format(
            pr_title=pr_data['pr_title'],
            pr_body=pr_data['pr_body'],
            diff=pr_data['diff'],
            comments='\n'.join(
                [comment['body'] for comment in pr_data.get('comments', [])]
            ),
        )


class PythonGeneralPRAnalyzer(BasePRAnalyzer):
    """Python/General code PR analyzer."""

    def post_process_analysis(self, analysis: str) -> str:
        """Standard post-processing for general repos."""
        # De-emphasize headers for GitHub formatting
        return re.sub(r'^#{1,3}(?= )', '####', analysis, flags=re.MULTILINE)