Initial commit

skills/memory-profiling/examples/INDEX.md

@@ -0,0 +1,86 @@
+# Memory Profiling Examples
+
+Production memory profiling implementations for Node.js and Python with leak detection, heap analysis, and optimization strategies.
+
+## Examples Overview
+
+### Node.js Memory Leak Detection
+
+**File**: [nodejs-memory-leak.md](nodejs-memory-leak.md)
+
+Identifying and fixing memory leaks in Node.js applications:
+- **Memory leak detection**: Chrome DevTools, heapdump analysis
+- **Common leak patterns**: Event listeners, closures, global variables
+- **Heap snapshots**: Before/after comparison, retained object analysis
+- **Real leak**: EventEmitter leak causing 2GB memory growth
+- **Fix**: Proper cleanup with `removeListener()`, WeakMap for caching
+- **Result**: Memory stabilized at 150MB (93% reduction)
+
+**Use when**: Node.js memory growing over time, debugging production memory issues
+
+---
+
+### Python Memory Profiling with Scalene
+
+**File**: [python-scalene-profiling.md](python-scalene-profiling.md)
+
+Line-by-line memory profiling for Python applications:
+- **Scalene setup**: Installation, pytest integration, CLI usage
+- **Memory hotspots**: Line-by-line allocation tracking
+- **CPU + Memory**: Combined profiling for performance bottlenecks
+- **Real scenario**: 500MB dataset causing OOM, fixed with generators
+- **Optimization**: List comprehension → generator (500MB → 5MB)
+- **Result**: 99% memory reduction, no OOM errors
+
+**Use when**: Python memory spikes, profiling pytest tests, finding allocation hotspots
+
+---
+
+### Database Connection Pool Leak
+
+**File**: [database-connection-leak.md](database-connection-leak.md)
+
+PostgreSQL connection pool exhaustion and memory leaks:
+- **Symptom**: Connection pool maxed out, memory growing linearly
+- **Root cause**: Unclosed connections in error paths, missing `finally` blocks
+- **Detection**: Connection pool metrics, memory profiling
+- **Fix**: Context managers (`with` statement), proper cleanup
+- **Result**: Zero connection leaks, memory stable at 80MB
+
+**Use when**: Database connection errors, "too many clients" errors, connection pool issues
+
+---
+
+### Large Dataset Memory Optimization
+
+**File**: [large-dataset-optimization.md](large-dataset-optimization.md)
+
+Memory-efficient data processing for large datasets:
+- **Problem**: Loading 10GB CSV into memory (OOM killer)
+- **Solutions**: Streaming with `pandas.read_csv(chunksize)`, generators, memory mapping
+- **Techniques**: Lazy evaluation, columnar processing, batch processing
+- **Before/After**: 10GB memory → 500MB (95% reduction)
+- **Tools**: Pandas chunking, Dask for parallel processing
+
+**Use when**: Processing large files, OOM errors, batch data processing
+
+---
+
+## Quick Navigation
+
+| Topic | File | Lines | Focus |
+|-------|------|-------|-------|
+| **Node.js Leaks** | [nodejs-memory-leak.md](nodejs-memory-leak.md) | ~450 | EventEmitter, heap snapshots |
+| **Python Scalene** | [python-scalene-profiling.md](python-scalene-profiling.md) | ~420 | Line-by-line profiling |
+| **DB Connection Leaks** | [database-connection-leak.md](database-connection-leak.md) | ~380 | Connection pool management |
+| **Large Datasets** | [large-dataset-optimization.md](large-dataset-optimization.md) | ~400 | Streaming, chunking |
+
+## Related Documentation
+
+- **Reference**: [Reference Index](../reference/INDEX.md) - Memory patterns, profiling tools
+- **Templates**: [Templates Index](../templates/INDEX.md) - Profiling report template
+- **Main Agent**: [memory-profiler.md](../memory-profiler.md) - Memory profiler agent
+
+---
+
+Return to [main agent](../memory-profiler.md)