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app.py

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+import pickle
+import numpy as np
+from flask import Flask, render_template, request
+
+app = Flask(__name__)
+
+
+# Helper function to get location code
+def get_location_code(location):
+    # Define the mapping of locations to integers
+    location_mapping = {
+        'Baguiati': 68,
+        'Barsat': 79,
+        'Behala': 86,
+        'Bhadreswar': 90,
+        'Chkravarti Para': 138,
+        'Dum Dum Park': 175,
+        'Dum Dum': 174,
+        'Garia': 197,
+        'Gariahat': 198,
+        'Hooghly Chinsurah': 237,
+        'Hussainpur': 241,
+        'Joka': 272,
+        'Keshtopur': 320,
+        'Konnagar': 348,
+        'Kutighat': 374,
+        'Lake Gardens': 380,
+        'Madhyamgram': 392,
+        'Madurdaha Hussainpur': 396,
+        'Mukundapur': 450,
+        'Narendrapur': 480,
+        'New Alipore': 493,
+        'New Town': 495,
+        'Rajarhat': 565,
+        'Santoshpur': 604,
+        'Sarsuna': 609,
+        'Sodepur': 719,
+        'Sonarpur': 721,
+        'south dum dum': 842,
+        'Tangra': 737,
+        'Tollygunge': 763,
+        'Ultadanga': 768,
+        'Uttarpara Kotrung': 778
+    }
+    # Return the integer code for the given location, or 0 if location not found
+    return location_mapping.get(location, 0)
+
+
+# Load the trained model
+with open("models/best_xgb_kolkata.pkl", "rb") as f:
+    model = pickle.load(f)
+# Print model information
+# print("Loaded model:", model)
+
+# Define route for index page
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+# Handle prediction request
+@app.route('/predict', methods=['POST'])
+def predict():
+    print("Prediction endpoint triggered")
+    # Get user input from the form
+    area = int(request.form['area'])
+    bedrooms = int(request.form['bedrooms'])
+    location = request.form['location']
+    club_house = 1 if request.form['club-house'] == 'Yes' else 0
+    rain_water_harvesting = 1 if request.form['rain-water-harvesting'] == 'Yes' else 0
+    swimming_pool = 1 if request.form['swimming-pool'] == 'Yes' else 0
+    resale = 1 if request.form['resale'] == 'Yes' else 0
+    cafeteria = 1 if request.form['Cafeteria'] == 'Yes' else 0
+    lift_available = 1 if request.form['LiftAvailable'] == 'Yes' else 0
+    maintenance_staff = 1 if request.form['MaintenanceStaff'] == 'Yes' else 0
+    jogging_track = 1 if request.form['JoggingTrack'] == 'Yes' else 0
+    landscaped_gardens = 1 if request.form['LandscapedGardens'] == 'Yes' else 0
+    vaastu_compliant = 1 if request.form['VaastuCompliant'] == 'Yes' else 0
+    multipurpose_room = 1 if request.form['MultipurposeRoom'] == 'Yes' else 0
+    power_backup = 1 if request.form['PowerBackup'] == 'Yes' else 0
+    indoor_games = 1 if request.form['IndoorGames'] == 'Yes' else 0
+    washing_machine = 1 if request.form['WashingMachine'] == 'Yes' else 0
+    car_parking = 1 if request.form['CarParking'] == 'Yes' else 0
+    sports_facility = 1 if request.form['SportsFacility'] == 'Yes' else 0
+    gymnasium = 1 if request.form['Gymnasium'] == 'Yes' else 0
+
+    # Preprocess user input
+    location_code = get_location_code(location)
+
+    # Print received form data
+    '''
+    print("Received Form Data:")
+    print("Area:", area)
+    print("Bedrooms:", bedrooms)
+    print("Location:", location)
+    print("Club House:", club_house)
+    print("Rain Water Harvesting:", rain_water_harvesting)
+    print("Swimming Pool:", swimming_pool)
+    print("Resale:", resale)
+    print("Cafeteria:", cafeteria)
+    print("Lift Available:", lift_available)
+    print("Maintenance Staff:", maintenance_staff)
+    print("Jogging Track:", jogging_track)
+    print("Landscaped Gardens:", landscaped_gardens)
+    print("Vaastu Compliant:", vaastu_compliant)
+    print("Multipurpose Room:", multipurpose_room)
+    print("Power Backup:", power_backup)
+    print("Indoor Games:", indoor_games)
+    print("Washing Machine:", washing_machine)
+    print("Car Parking:", car_parking)
+    print("Sports Facility:", sports_facility)
+    print("Gymnasium:", gymnasium)
+    '''
+    # Make prediction
+    features = np.array([[area, swimming_pool, resale, club_house, rain_water_harvesting, cafeteria, lift_available,
+                          maintenance_staff, location_code, jogging_track, landscaped_gardens, bedrooms,
+                          vaastu_compliant, multipurpose_room, power_backup, indoor_games, washing_machine, car_parking,
+                          sports_facility, gymnasium]])
+    predicted_price = model.predict(features)[0]
+    print("Predicted Price:", predicted_price)
+
+    # Return prediction result
+    return render_template('index.html', predicted_price=predicted_price)
+
+
+if __name__ == '__main__':
+
+    app.run(debug=True)

requirements.txt

@@ -0,0 +1,206 @@
+absl-py==2.1.0
+annotated-types==0.6.0
+anyio==4.2.0
+argon2-cffi==23.1.0
+argon2-cffi-bindings==21.2.0
+arrow==1.3.0
+asttokens==2.4.1
+astunparse==1.6.3
+async-lru==2.0.4
+attrs==23.2.0
+autopep8==2.0.4
+autoviz==0.1.806
+Babel==2.14.0
+beautifulsoup4==4.12.3
+bleach==6.1.0
+bokeh==2.4.3
+Brotli==1.1.0
+cachetools==5.3.2
+certifi==2024.2.2
+cffi==1.16.0
+charset-normalizer==3.3.2
+click==8.1.7
+colorcet==3.0.1
+comm==0.2.1
+contourpy==1.2.0
+cycler==0.12.1
+dacite==1.8.1
+dash==2.15.0
+dash-bootstrap-components==1.3.1
+dash-colorscales==0.0.4
+dash-core-components==2.0.0
+dash-daq==0.5.0
+dash-html-components==2.0.0
+dash-table==5.0.0
+debugpy==1.8.0
+decorator==5.1.1
+defusedxml==0.7.1
+dtale==3.10.0
+emoji==2.10.1
+et-xmlfile==1.1.0
+exceptiongroup==1.2.0
+executing==2.0.1
+fastjsonschema==2.19.1
+Flask==2.2.5
+Flask-Compress==1.14
+flask-ngrok==0.0.25
+flatbuffers==23.5.26
+fonttools==4.48.1
+fqdn==1.5.1
+fsspec==2024.2.0
+future==0.18.3
+gast==0.5.4
+google-auth==2.28.0
+google-auth-oauthlib==1.2.0
+google-pasta==0.2.0
+grpcio==1.60.1
+h11==0.14.0
+h5py==3.10.0
+holoviews==1.14.9
+htmlmin==0.1.12
+httpcore==1.0.2
+httpx==0.26.0
+hvplot==0.7.3
+idna==3.6
+ImageHash==4.3.1
+importlib-metadata==7.0.1
+importlib-resources==6.1.1
+ipykernel==6.29.1
+ipython==8.18.1
+isoduration==20.11.0
+itsdangerous==2.1.2
+jedi==0.19.1
+Jinja2==3.1.3
+joblib==1.3.2
+json5==0.9.14
+jsonpointer==2.4
+jsonschema==4.21.1
+jsonschema-specifications==2023.12.1
+jupyter-events==0.9.0
+jupyter-lsp==2.2.2
+jupyter_client==8.6.0
+jupyter_core==5.7.1
+jupyter_server==2.12.5
+jupyter_server_terminals==0.5.2
+jupyterlab==4.1.0
+jupyterlab_server==2.25.2
+kaleido==0.2.1
+keras==2.15.0
+kiwisolver==1.4.5
+libclang==16.0.6
+llvmlite==0.41.1
+lz4==4.3.3
+Markdown==3.5.2
+MarkupSafe==2.1.5
+matplotlib==3.7.4
+matplotlib-inline==0.1.6
+missingno==0.5.2
+mistune==3.0.2
+ml-dtypes==0.2.0
+multimethod==1.11
+nbclient==0.9.0
+nbconvert==7.15.0
+nbformat==5.9.2
+nest-asyncio==1.6.0
+networkx==3.2.1
+nltk==3.8.1
+notebook==7.0.7
+notebook_shim==0.2.3
+numba==0.58.1
+numpy==1.24.4
+oauthlib==3.2.2
+openpyxl==3.1.2
+opt-einsum==3.3.0
+overrides==7.7.0
+packaging==23.2
+pandas==2.2.0
+pandas-dq==1.29
+pandas-profiling==3.6.6
+pandocfilters==1.5.1
+panel==0.14.4
+param==1.13.0
+parso==0.8.3
+patsy==0.5.6
+pexpect==4.9.0
+phik==0.12.4
+pillow==10.2.0
+platformdirs==4.2.0
+plotly==5.18.0
+prometheus-client==0.19.0
+prompt-toolkit==3.0.43
+protobuf==4.25.3
+psutil==5.9.8
+ptyprocess==0.7.0
+pure-eval==0.2.2
+pyamg==5.0.1
+pyarrow==15.0.0
+pyasn1==0.5.1
+pyasn1-modules==0.3.0
+pycodestyle==2.11.1
+pycparser==2.21
+pyct==0.5.0
+pydantic==2.6.1
+pydantic-settings==2.1.0
+pydantic_core==2.16.2
+Pygments==2.17.2
+pyparsing==3.1.1
+python-dateutil==2.8.2
+python-dotenv==1.0.1
+python-json-logger==2.0.7
+pytz==2024.1
+pyviz_comms==3.0.1
+PyWavelets==1.5.0
+PyYAML==6.0.1
+pyzmq==25.1.2
+referencing==0.33.0
+regex==2023.12.25
+requests==2.31.0
+requests-oauthlib==1.3.1
+retrying==1.3.4
+rfc3339-validator==0.1.4
+rfc3986-validator==0.1.1
+rpds-py==0.17.1
+rsa==4.9
+scikit-learn==1.4.0
+scipy==1.11.4
+seaborn==0.12.2
+Send2Trash==1.8.2
+six==1.16.0
+sniffio==1.3.0
+soupsieve==2.5
+squarify==0.4.3
+stack-data==0.6.3
+statsmodels==0.14.1
+strsimpy==0.2.1
+sweetviz==2.3.1
+tabulate==0.9.0
+tangled-up-in-unicode==0.2.0
+tenacity==8.2.3
+termcolor==2.4.0
+terminado==0.18.0
+textblob==0.17.1
+threadpoolctl==3.2.0
+tinycss2==1.2.1
+tomli==2.0.1
+tornado==6.4
+tqdm==4.66.2
+traitlets==5.14.1
+typeguard==4.1.5
+types-python-dateutil==2.8.19.20240106
+typing_extensions==4.9.0
+tzdata==2023.4
+uri-template==1.3.0
+urllib3==2.2.0
+visions==0.7.5
+wcwidth==0.2.13
+webcolors==1.13
+webencodings==0.5.1
+websocket-client==1.7.0
+Werkzeug==3.0.1
+wordcloud==1.9.3
+wrapt==1.14.1
+xarray==2024.1.1
+xgboost==1.6.2
+xlrd==2.0.1
+ydata-profiling==4.6.4
+zipp==3.17.0