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Development
# Install dependencies
npm install
# Run dev server
npm run dev
# Build for production
npm run build
Server Deployment
# SSH to your server
ssh user@your-server-ip
# Navigate to projectcd /opt/reddit-analyzer
# Restart API server
pkill -f gunicorn
nohup gunicorn -w 1 -b 0.0.0.0:5000 api_server_simple:app --timeout 120 > gunicorn.log 2>&1&
Relevant Server Files
File
Description
/opt/reddit-analyzer/api_server_simple.py
Main API server - simplified raw dump approach
/opt/reddit-analyzer/data/
Permanent storage - never deleted, data is merged
/opt/reddit-analyzer/cache/
Quick access cache (copy of data)
/opt/reddit-analyzer/gunicorn.log
Server logs
API Endpoints
Endpoint
Method
Description
/analyze
POST
Fetch/analyze user, merges with existing data
/health
GET
Server health check
/users
GET
List all stored users with stats
Server-side Queueing (New)
To prevent overload and show users their place in line, the frontend now supports server-managed queuing for analysis requests. When enabled on the server, the flow is:
Client POSTs /analyze with {"username":"...","queue":true} and header X-Queue: 1
Server responds immediately with a queued status:
{
"status": "queued", // or "processing"
"request_id": "abc123",
"position": 2, // number in queue (1 = first)
"eta_seconds": 90 // optional
}
Client polls GET /queue/status?request_id=abc123 every ~1.5s until status is done
Server returns the result either embedded in the status { status: 'done', result: {...} } or via GET /queue/result?request_id=abc123
Frontend changes are backward compatible: if the server does not support queueing, /analyze will return the analysis as before.
Minimal Flask server implementation sketch (add to /opt/reddit-analyzer/api_server_simple.py):
# --- queue.py (inline or separate module) ---importthreading, queue, time, uuidfromtypingimportDictjob_q=queue.Queue() # pending jobsstatuses: Dict[str, dict] = {}
defworker_thread(process_fn):
whileTrue:
job=job_q.get()
ifjobisNone:
breakrid=job['request_id']
statuses[rid]['status'] ='processing'try:
result=process_fn(job['payload'])
statuses[rid]['status'] ='done'statuses[rid]['result'] =resultexceptExceptionase:
statuses[rid]['status'] ='error'statuses[rid]['message'] =str(e)
finally:
job_q.task_done()
defqueue_position(rid: str) ->int:
# compute 1-based position; simple O(n) scanitems=list(job_q.queue)
fori, jinenumerate(items, start=1):
ifj['request_id'] ==rid:
returnireturn0# 0 means up next or processing# In your Flask app startup:# start a single worker to guarantee concurrency=1# worker = threading.Thread(target=worker_thread, args=(process_analyze,), daemon=True)# worker.start()# --- in your Flask routes ---@app.route('/analyze', methods=['POST'])defanalyze_route():
data=request.get_json(force=True)
username=data.get('username','').strip()
ifnotusername:
returnjsonify({ 'error': 'username_required' }), 400# If client requests queueing, enqueueifrequest.headers.get('X-Queue') =='1'ordata.get('queue'):
rid=uuid.uuid4().hexpayload= {
'username': username,
'force_refresh': bool(data.get('force_refresh')),
'include_raw': bool(data.get('include_raw')),
'top': int(data.get('top') or0)
}
statuses[rid] = { 'status': 'queued' }
job_q.put({ 'request_id': rid, 'payload': payload })
pos=queue_position(rid)
returnjsonify({ 'status': 'queued', 'request_id': rid, 'position': pos })
# Backward-compatible: process synchronouslyresult=process_analyze({
'username': username,
'force_refresh': bool(data.get('force_refresh')),
'include_raw': bool(data.get('include_raw')),
'top': int(data.get('top') or0)
})
returnjsonify(result)
@app.get('/queue/status')defqueue_status():
rid=request.args.get('request_id','')
s=statuses.get(rid)
ifnots:
returnjsonify({ 'status': 'error', 'message': 'unknown_request' }), 404pos=queue_position(rid)
out= { 'status': s.get('status', 'queued'), 'position': pos }
if'eta_seconds'ins:
out['eta_seconds'] =s['eta_seconds']
ifout['status'] =='done'and'result'ins:
# You can omit result here and serve it from /queue/result insteadpassreturnjsonify(out)
@app.get('/queue/result')defqueue_result():
rid=request.args.get('request_id','')
s=statuses.get(rid)
ifnots:
returnjsonify({ 'status': 'error', 'message': 'unknown_request' }), 404ifs.get('status') !='done':
returnjsonify({ 'status': s.get('status','queued') }), 202returnjsonify(s['result'])
Hook your existing analysis function into process_analyze(payload) so the worker executes it. Keep the worker count at 1 for strict queueing.
Trigger fresh deployment Thu Feb 5 21:34:04 CET 2026
Cache invalidation 1770323964
About
React dashboard for analyzing Reddit user activity, behavior patterns, and content with AI-powered insights. Features content analysis, karma breakdowns, and activity timelines.
