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import joblib
import pandas as pd
from flask import Flask, request, jsonify
# Initialize Flask app with a name
app = Flask("Telecom Customer Churn Predictor")
# Load the trained churn prediction model
model = joblib.load("churn_prediction_model_v1_0.joblib")
# Define a route for the home page
@app.get('/')
def home():
return "Welcome to the Telecom Customer Churn Prediction API"
# Define an endpoint to predict churn for a single customer
@app.post('/v1/customer')
def predict_churn():
# Get JSON data from the request
customer_data = request.get_json()
# Extract relevant customer features from the input data
sample = {
'SeniorCitizen': customer_data['SeniorCitizen'],
'Partner': customer_data['Partner'],
'Dependents': customer_data['Dependents'],
'tenure': customer_data['tenure'],
'PhoneService': customer_data['PhoneService'],
'InternetService': customer_data['InternetService'],
'Contract': customer_data['Contract'],
'PaymentMethod': customer_data['PaymentMethod'],
'MonthlyCharges': customer_data['MonthlyCharges'],
'TotalCharges': customer_data['TotalCharges']
}
# Convert the extracted data into a DataFrame
input_data = pd.DataFrame([sample])
# Make a churn prediction using the trained model
prediction = model.predict(input_data).tolist()[0]
# Map prediction result to a human-readable label
prediction_label = "churn" if prediction == 1 else "not churn"
# Return the prediction as a JSON response
return jsonify({'Prediction': prediction_label})
# Define an endpoint to predict churn for a batch of customers
@app.post('/v1/customerbatch')
def predict_churn_batch():
# Get the uploaded CSV file from the request
file = request.files['file']
# Read the file into a DataFrame
input_data = pd.read_csv(file)
# Make predictions for the batch data and convert raw predictions into a readable format
predictions = [
'Churn' if x == 1
else "Not Churn"
for x in model.predict(input_data.drop("customerID",axis=1)).tolist()
]
cust_id_list = input_data.customerID.values.tolist()
output_dict = dict(zip(cust_id_list, predictions))
return output_dict
# Run the Flask app in debug mode
if __name__ == '__main__':
app.run(debug=True)
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