Create backend.py

data_analytics_platform/backend.py

@@ -0,0 +1,39 @@
+import pandas as pd
+import numpy as np
+from flask import Flask, jsonify, request
+from flask_cors import CORS
+from sqlalchemy import create_engine
+
+app = Flask(__name__)
+CORS(app)
+
+# Database connection
+engine = create_engine('postgresql://user:password@host:port/dbname')
+
+# Load data from database
+def load_data():
+    data = pd.read_sql_table('pi_coin_data', engine)
+    return data
+
+# API endpoint to retrieve real-time data
+@app.route('/api/data', methods=['GET'])
+def get_data():
+    data = load_data()
+    return jsonify(data.to_dict(orient='records'))
+
+# API endpoint to retrieve aggregated data
+@app.route('/api/aggregated_data', methods=['GET'])
+def get_aggregated_data():
+    data = load_data()
+    aggregated_data = data.groupby('date').agg({'price': 'mean', 'volume': 'sum'})
+    return jsonify(aggregated_data.to_dict(orient='records'))
+
+# API endpoint to retrieve listing progress data
+@app.route('/api/listing_progress', methods=['GET'])
+def get_listing_progress():
+    data = load_data()
+    listing_progress = data.groupby('listing_status').size().reset_index(name='count')
+    return jsonify(listing_progress.to_dict(orient='records'))
+
+if __name__ == '__main__':
+    app.run(debug=True)