add more tweaks for stability for more users at the same time working in it
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@@ -28,4 +28,4 @@ USER appuser
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EXPOSE 5000
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ENTRYPOINT ["/app/entrypoint.sh"]
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CMD ["gunicorn", "--bind", "0.0.0.0:5000", "--workers", "4", "--timeout", "120", "app:app"]
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CMD ["gunicorn", "--config", "/app/gunicorn.conf.py", "app:app"]
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45
backend/gunicorn.conf.py
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45
backend/gunicorn.conf.py
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@@ -0,0 +1,45 @@
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"""
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Gunicorn configuratie voor de Leerdoelen Tracker.
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Belasting voor deze app:
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~264 gebruikers totaal (12 scholen × ~22 per school)
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Piekgebruik: 50-80 gelijktijdig tijdens studiedagen
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~2-3 requests/seconde op piekmomenten
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Worker formule: (2 × CPU-cores) + 1
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Voor een typische VPS met 2 vCPU: 5 workers
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Elke worker kan 1 request tegelijk afhandelen (sync worker).
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Met 4 workers + 2 threads = effectief 8 gelijktijdige requests —
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ruim voldoende voor deze schaal.
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"""
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import multiprocessing
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import os
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# ── Workers ───────────────────────────────────────────────────────────────────
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# Instelbaar via env voor flexibiliteit op grotere of kleinere servers
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workers = int(os.environ.get('GUNICORN_WORKERS', multiprocessing.cpu_count() * 2 + 1))
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threads = int(os.environ.get('GUNICORN_THREADS', 2))
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worker_class = 'gthread' # threads-based: beter voor I/O-bound Flask apps
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# ── Binding ───────────────────────────────────────────────────────────────────
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bind = '0.0.0.0:5000'
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# ── Timeouts ──────────────────────────────────────────────────────────────────
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timeout = 60 # worker killed na 60s — voorkomt hangende processen
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graceful_timeout = 30 # tijd om lopende requests af te werken bij restart
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keepalive = 5 # HTTP keep-alive seconden (nginx hergebruikt connecties)
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# ── Logging ───────────────────────────────────────────────────────────────────
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accesslog = '-' # stdout → docker logs
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errorlog = '-' # stderr → docker logs
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loglevel = os.environ.get('LOG_LEVEL', 'info')
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access_log_format = '%(h)s %(l)s %(u)s %(t)s "%(r)s" %(s)s %(b)s %(D)sµs'
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# ── Worker lifecycle ──────────────────────────────────────────────────────────
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# Herstart workers na N requests — voorkomt memory leaks over tijd
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max_requests = 1000
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max_requests_jitter = 100 # willekeurige offset voorkomt gelijktijdige restarts
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# ── Process naam ──────────────────────────────────────────────────────────────
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proc_name = 'leerdoelen-tracker'
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@@ -6,6 +6,13 @@ Eén bron van waarheid. Geen andere plek in de app definieert vaknamen.
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import os
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import json
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import re
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import threading
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# In-memory cache: { vak_id: {'data': {...}, 'mtime': float} }
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# Geïnvalideerd bij upload/delete — voorkomt schijf-I/O bij elke request
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_cache: dict = {}
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_cache_lock = threading.Lock()
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_INDEX_KEY = "__index__"
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DOELEN_DIR = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'doelen')
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@@ -49,7 +56,45 @@ def list_installed_vakken():
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])
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def _cache_get(key):
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path = os.path.join(DOELEN_DIR, 'index.json' if key == _INDEX_KEY else f'{key}.json')
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if not os.path.exists(path):
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return None
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try:
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mtime = os.path.getmtime(path)
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except OSError:
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return None
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with _cache_lock:
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entry = _cache.get(key)
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if entry and entry['mtime'] == mtime:
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return entry['data']
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return None
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def _cache_set(key, data):
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path = os.path.join(DOELEN_DIR, 'index.json' if key == _INDEX_KEY else f'{key}.json')
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try:
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mtime = os.path.getmtime(path)
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except OSError:
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return
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with _cache_lock:
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_cache[key] = {'data': data, 'mtime': mtime}
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def cache_invalidate(vak_id=None):
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"""Verwijder één of alle entries uit de cache (aanroepen na upload/delete)."""
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with _cache_lock:
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if vak_id:
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_cache.pop(vak_id, None)
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_cache.pop(_INDEX_KEY, None)
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else:
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_cache.clear()
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def load_index():
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cached = _cache_get(_INDEX_KEY)
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if cached:
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return cached
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path = os.path.join(DOELEN_DIR, 'index.json')
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if not os.path.exists(path):
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rebuild_index()
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@@ -58,18 +103,23 @@ def load_index():
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for vak in data.get('vakken', []):
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vak['naam'] = vak_naam(vak['id'])
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data['vakken'].sort(key=lambda v: v['naam'])
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_cache_set(_INDEX_KEY, data)
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return data
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def load_vak(vak_id):
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if not is_valid_vak_id(vak_id):
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return None
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cached = _cache_get(vak_id)
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if cached:
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return cached
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path = get_doelen_path(vak_id)
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if not os.path.exists(path):
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return None
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with open(path, encoding='utf-8') as f:
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data = json.load(f)
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data['vakNaam'] = vak_naam(vak_id)
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_cache_set(vak_id, data)
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return data
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@@ -102,6 +152,7 @@ def save_vak(vak_id, data):
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path = get_doelen_path(vak_id)
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with open(path, 'w', encoding='utf-8') as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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cache_invalidate(vak_id)
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rebuild_index()
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@@ -110,6 +161,7 @@ def delete_vak(vak_id):
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if not os.path.exists(path):
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return False
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os.remove(path)
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cache_invalidate(vak_id)
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rebuild_index()
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return True
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@@ -1,5 +1,3 @@
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version: '3.9'
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services:
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db:
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image: postgres:16-alpine
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@@ -52,6 +50,11 @@ services:
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BASE_URL: ${BASE_URL:-http://localhost}
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ORG_NAME: ${ORG_NAME:-GO! Scholengroep}
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REDIS_URL: redis://:${REDIS_PASSWORD:-changeme_redis}@redis:6379/0
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# Gunicorn tuning — standaard: (2 × CPU) + 1 workers, 2 threads per worker
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# Pas aan op basis van je server: 2 vCPU → 5 workers, 4 vCPU → 9 workers
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GUNICORN_WORKERS: ${GUNICORN_WORKERS:-5}
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GUNICORN_THREADS: ${GUNICORN_THREADS:-2}
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LOG_LEVEL: ${LOG_LEVEL:-info}
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volumes:
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- ./doelen:/app/doelen:ro # JSON doelen bestanden (read-only)
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ports:
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