10c9e0d854
Complete restructure from patterns/examples/reference to technology-focused directories: • Created technology-specific directories with comprehensive documentation: - /tdarr/ - Transcoding automation with gaming-aware scheduling - /docker/ - Container management with GPU acceleration patterns - /vm-management/ - Virtual machine automation and cloud-init - /networking/ - SSH infrastructure, reverse proxy, and security - /monitoring/ - System health checks and Discord notifications - /databases/ - Database patterns and troubleshooting - /development/ - Programming language patterns (bash, nodejs, python, vuejs) • Enhanced CLAUDE.md with intelligent context loading: - Technology-first loading rules for automatic context provision - Troubleshooting keyword triggers for emergency scenarios - Documentation maintenance protocols with automated reminders - Context window management for optimal documentation updates • Preserved valuable content from .claude/tmp/: - SSH security improvements and server inventory - Tdarr CIFS troubleshooting and Docker iptables solutions - Operational scripts with proper technology classification • Benefits achieved: - Self-contained technology directories with complete context - Automatic loading of relevant documentation based on keywords - Emergency-ready troubleshooting with comprehensive guides - Scalable structure for future technology additions - Eliminated context bloat through targeted loading 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
155 lines
3.0 KiB
Markdown
155 lines
3.0 KiB
Markdown
# Python Debugging Reference
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## Common Error Patterns
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### ImportError / ModuleNotFoundError
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```bash
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# Check Python path
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python -c "import sys; print('\n'.join(sys.path))"
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# Check installed packages
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pip list
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pip show <package_name>
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# Install missing packages
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pip install -r requirements.txt
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pip install <package_name>
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```
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### Virtual Environment Issues
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```bash
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# Check current environment
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which python
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which pip
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# Recreate virtual environment
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rm -rf venv/
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python -m venv venv
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source venv/bin/activate # Linux/Mac
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# venv\Scripts\activate # Windows
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pip install -r requirements.txt
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```
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### Memory Issues
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```python
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import tracemalloc
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import psutil
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import os
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# Memory profiling
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tracemalloc.start()
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# ... your code ...
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current, peak = tracemalloc.get_traced_memory()
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print(f"Current memory usage: {current / 1024 / 1024:.1f} MB")
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print(f"Peak memory usage: {peak / 1024 / 1024:.1f} MB")
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# System memory
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process = psutil.Process(os.getpid())
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print(f"RSS memory: {process.memory_info().rss / 1024 / 1024:.1f} MB")
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```
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## Debugging Tools
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### Using pdb debugger
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```python
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import pdb
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def problematic_function():
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x = 10
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pdb.set_trace() # Execution will pause here
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y = x * 2
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return y
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# Or use breakpoint() in Python 3.7+
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def modern_debug():
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x = 10
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breakpoint() # Same as pdb.set_trace()
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return x
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```
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### Logging setup
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```python
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import logging
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# Configure logging
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logging.basicConfig(
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level=logging.DEBUG,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler('debug.log'),
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logging.StreamHandler()
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]
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)
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logger = logging.getLogger(__name__)
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def example_function():
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logger.debug("Starting function")
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try:
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result = risky_operation()
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logger.info(f"Operation successful: {result}")
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return result
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except Exception as e:
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logger.error(f"Operation failed: {e}", exc_info=True)
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raise
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```
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## Performance Debugging
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### Profile code execution
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```python
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import cProfile
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import pstats
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# Profile a function
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cProfile.run('your_function()', 'profile_output.prof')
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# Analyze results
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stats = pstats.Stats('profile_output.prof')
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stats.sort_stats('cumulative').print_stats(10)
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```
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### Line-by-line profiling
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```bash
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# Install line_profiler
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pip install line_profiler
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# Add @profile decorator to functions
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# Run with:
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kernprof -l -v your_script.py
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```
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### Check for memory leaks
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```python
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import gc
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import objgraph
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# Show most common types
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objgraph.show_most_common_types()
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# Track object growth
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objgraph.show_growth()
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```
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## Database Debugging
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### SQLAlchemy query debugging
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```python
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import logging
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# Enable SQL query logging
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logging.basicConfig()
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logging.getLogger('sqlalchemy.engine').setLevel(logging.INFO)
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logging.getLogger('sqlalchemy.dialects').setLevel(logging.DEBUG)
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logging.getLogger('sqlalchemy.pool').setLevel(logging.DEBUG)
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```
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### Connection issues
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```python
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# Test database connection
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try:
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engine.connect()
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print("Database connection successful")
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except Exception as e:
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print(f"Database connection failed: {e}")
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``` |