httpd: remove memory profiling code
Remove objgraph/pympler imports, gc.get_objects() caching, and memory_samples tracking. Keep basic RSS tracking for dashboard.
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117
httpd.py
117
httpd.py
@@ -58,32 +58,14 @@ _LIB_CACHE = {}
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# Cache for dashboard static files (HTML, CSS, JS)
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_STATIC_CACHE = {}
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# Optional memory profiling (installed via requirements.txt)
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try:
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import objgraph
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_has_objgraph = True
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except ImportError:
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_has_objgraph = False
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try:
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from pympler import muppy, summary
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_has_pympler = True
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except ImportError:
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_has_pympler = False
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# Memory tracking for leak detection
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_memory_samples = []
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_memory_sample_max = 60 # Keep last 60 samples (5 min at 5s intervals)
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_peak_rss = 0
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_start_rss = 0
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# Cache for expensive operations
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_gc_objects_cache = {'value': 0, 'time': 0}
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_gc_objects_ttl = 30 # seconds
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_db_health_cache = {'value': {}, 'time': 0}
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_db_health_ttl = 10 # seconds
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# Simple RSS tracking for dashboard
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_peak_rss = 0
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_start_rss = 0
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# Worker registry for distributed testing
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import hashlib
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import random
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@@ -669,39 +651,26 @@ def get_system_stats():
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stats['proc_rss'] = 0
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stats['proc_threads'] = 0
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# Memory leak detection
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global _memory_samples, _peak_rss, _start_rss
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# Simple RSS tracking for dashboard
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global _peak_rss, _start_rss
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rss = stats.get('proc_rss', 0)
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if rss > 0:
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if _start_rss == 0:
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_start_rss = rss
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if rss > _peak_rss:
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_peak_rss = rss
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_memory_samples.append((time.time(), rss))
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if len(_memory_samples) > _memory_sample_max:
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_memory_samples.pop(0)
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stats['proc_rss_peak'] = _peak_rss
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stats['proc_rss_start'] = _start_rss
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stats['proc_rss_growth'] = rss - _start_rss if _start_rss > 0 else 0
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# GC stats for leak detection
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# GC generation counts (fast - no object iteration)
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try:
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gc_counts = gc.get_count()
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stats['gc_count_gen0'] = gc_counts[0]
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stats['gc_count_gen1'] = gc_counts[1]
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stats['gc_count_gen2'] = gc_counts[2]
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# Cache gc.get_objects() - expensive call (~23ms)
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global _gc_objects_cache
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now = time.time()
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if now - _gc_objects_cache['time'] > _gc_objects_ttl:
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_gc_objects_cache['value'] = len(gc.get_objects())
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_gc_objects_cache['time'] = now
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stats['gc_objects'] = _gc_objects_cache['value']
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except Exception as e:
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_log('gc stats error: %s' % e, 'debug')
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except Exception:
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stats['gc_count_gen0'] = stats['gc_count_gen1'] = stats['gc_count_gen2'] = 0
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stats['gc_objects'] = 0
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return stats
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@@ -1438,76 +1407,6 @@ class ProxyAPIServer(threading.Thread):
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return json.dumps({'count': row[0] if row else 0}), 'application/json', 200
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except Exception as e:
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return json.dumps({'error': str(e)}), 'application/json', 500
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elif path == '/api/memory':
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# Memory profiling endpoint (localhost only)
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if not is_localhost(remote_addr):
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return json.dumps({'error': 'not available'}), 'application/json', 404
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try:
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mem = {}
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# Process memory from /proc/self/status
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try:
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with open('/proc/self/status', 'r') as f:
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for line in f:
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if line.startswith('Vm'):
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parts = line.split()
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key = parts[0].rstrip(':')
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mem[key] = int(parts[1]) * 1024 # Convert to bytes
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except IOError:
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pass
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# GC stats
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gc_stats = {
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'collections': gc.get_count(),
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'threshold': gc.get_threshold(),
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'objects': len(gc.get_objects()),
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}
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# Object type counts (top 20)
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type_counts = {}
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for obj in gc.get_objects():
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t = type(obj).__name__
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type_counts[t] = type_counts.get(t, 0) + 1
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top_types = sorted(type_counts.items(), key=lambda x: -x[1])[:20]
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# Memory samples history
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samples = []
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for ts, rss in _memory_samples[-30:]:
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samples.append({'time': int(ts), 'rss': rss})
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result = {
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'process': mem,
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'gc': gc_stats,
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'top_types': [{'type': t, 'count': c} for t, c in top_types],
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'samples': samples,
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'peak_rss': _peak_rss,
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'start_rss': _start_rss,
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'has_objgraph': _has_objgraph,
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'has_pympler': _has_pympler,
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}
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# Objgraph most common types (if available)
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if _has_objgraph:
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try:
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result['objgraph_common'] = objgraph.most_common_types(limit=15)
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except Exception as e:
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result['objgraph_error'] = str(e)
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# Pympler summary (if available)
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if _has_pympler:
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try:
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all_objects = muppy.get_objects()
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sum_table = summary.summarize(all_objects)
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result['pympler_summary'] = [
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{'type': row[0], 'count': row[1], 'size': row[2]}
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for row in sum_table[:20]
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]
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except Exception as e:
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result['pympler_error'] = str(e)
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return json.dumps(result, indent=2), 'application/json', 200
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except Exception as e:
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return json.dumps({'error': str(e)}), 'application/json', 500
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elif path == '/health':
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return json.dumps({'status': 'ok', 'version': __version__, 'timestamp': int(time.time())}), 'application/json', 200
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