Update app.py

app.py

@@ -1,56 +1,66 @@
-from flask import Flask, jsonify
-from flask_cors import CORS
-import threading
-import time
-import subprocess
-import sys
-import os
-import json
-
-app = Flask(__name__)
-CORS(app) # Enable CORS so the React frontend can fetch data
-
-def run_scrapers_periodically():
-    """Background thread to run scrapers every 60 minutes."""
-    while True:
-        print(f"\n[{time.strftime('%Y-%m-%d %H:%M:%S')}] Starting scheduled background aggregation...")
-        try:
-            # Run aggregator.py
-            subprocess.run([sys.executable, "aggregator.py"], check=True)
-            # Run ai_training_scraper.py
-            subprocess.run([sys.executable, "ai_training_scraper.py"], check=True)
-            print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] Aggregation complete.")
-        except Exception as e:
-            print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] Aggregation error: {e}")
-        
-        # Wait for 60 minutes
-        time.sleep(3600)
-
-@app.route("/")
-def health_check():
-    return jsonify({"status": "running", "platform": "Firstify Engine"})
-
-@app.route("/api/startups")
-def get_startups():
-    try:
-        with open("data.json", "r") as f:
-            return jsonify(json.load(f))
-    except:
-        return jsonify([])
-
-@app.route("/api/training")
-def get_training():
-    try:
-        with open("training_data.json", "r") as f:
-            return jsonify(json.load(f))
-    except:
-        return jsonify([])
-
-if __name__ == "__main__":
-    # Start the scraping thread
-    threading.Thread(target=run_scrapers_periodically, daemon=True).start()
-    
-    # Start the Flask server
-    # Hugging Face Spaces use port 7860 by default
-    port = int(os.environ.get("PORT", 7860))
-    app.run(host="0.0.0.0", port=port)
+from flask import Flask, jsonify
+from flask_cors import CORS
+import threading
+import time
+import subprocess
+import sys
+import os
+import json
+
+app = Flask(__name__)
+CORS(app) # Enable CORS so the React frontend can fetch data
+
+def run_scrapers_periodically():
+    """Background thread to run scrapers every 60 minutes."""
+    while True:
+        print(f"\n[{time.strftime('%Y-%m-%d %H:%M:%S')}] Starting scheduled background aggregation...")
+        try:
+            # Run aggregator.py
+            subprocess.run([sys.executable, "aggregator.py"], check=True)
+            # Run ai_training_scraper.py
+            subprocess.run([sys.executable, "ai_training_scraper.py"], check=True)
+            # Run upwork_scraper.py
+            subprocess.run([sys.executable, "upwork_scraper.py"], check=True)
+            print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] All scrapers synced successfully.")
+        except Exception as e:
+            print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] Aggregation error: {e}")
+        
+        # Wait for 60 minutes
+        time.sleep(3600)
+
+@app.route("/")
+def health_check():
+    return jsonify({"status": "running", "platform": "Firstify Engine"})
+
+@app.route("/api/startups")
+def get_startups():
+    try:
+        with open("data.json", "r") as f:
+            return jsonify(json.load(f))
+    except:
+        return jsonify([])
+
+@app.route("/api/training")
+def get_training():
+    try:
+        with open("training_data.json", "r") as f:
+            return jsonify(json.load(f))
+    except:
+        return jsonify([])
+
+@app.route("/api/upwork")
+def get_upwork():
+    try:
+        with open("upwork_data.json", "r") as f:
+            return jsonify(json.load(f))
+    except:
+        return jsonify([])
+
+if __name__ == "__main__":
+    # Start the scraping thread
+    threading.Thread(target=run_scrapers_periodically, daemon=True).start()
+    
+    # Start the Flask server
+    # Hugging Face Spaces use port 7860 by default
+    port = int(os.environ.get("PORT", 7860))
+    app.run(host="0.0.0.0", port=port)