├── app
    ├── __init__.py
    ├── california_housing_model.joblib
    ├── __pycache__
    │   ├── server.cpython-311.pyc
    │   └── __init__.cpython-311.pyc
    ├── model.py
    └── server.py
├── .gitignore
├── requirements.txt
├── runserver.py
├── .github
    └── workflows
    │   ├── main.yml
    │   └── GHCR.yml
├── Dockerfile
├── static
    ├── predict.js
    └── style.css
├── templates
    └── index.html
└── README.md


/app/__init__.py:
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1 | 


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/.gitignore:
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1 | venv/
2 | 
3 | 


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/requirements.txt:
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1 | 
2 | numpy
3 | pandas
4 | scikit-learn
5 | flask
6 | joblib
7 | 


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/app/california_housing_model.joblib:
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https://raw.githubusercontent.com/EzioDEVio/MLOps/HEAD/app/california_housing_model.joblib


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/app/__pycache__/server.cpython-311.pyc:
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https://raw.githubusercontent.com/EzioDEVio/MLOps/HEAD/app/__pycache__/server.cpython-311.pyc


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/app/__pycache__/__init__.cpython-311.pyc:
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https://raw.githubusercontent.com/EzioDEVio/MLOps/HEAD/app/__pycache__/__init__.cpython-311.pyc


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/runserver.py:
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1 | 
2 | from waitress import serve
3 | from app.server import app
4 | 
5 | if __name__ == '__main__':
6 |     serve(app, host='0.0.0.0', port=5000)
7 | 


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/.github/workflows/main.yml:
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 1 | 
 2 | name: MLOps with Python application..
 3 | 
 4 | on:
 5 |   #push:
 6 |     branches: [ main ]
 7 |   #pull_request:
 8 |     branches: [ main ]
 9 | 
10 | jobs:
11 |   build:
12 | 
13 |     runs-on: windows-latest
14 | 
15 |     steps:
16 |     - uses: actions/checkout@v2
17 |     - name: Set up Python 3.8
18 |       uses: actions/setup-python@v1
19 |       with:
20 |         python-version: 3.8
21 |     - name: Install dependencies
22 |       run: |
23 |         python -m pip install --upgrade pip
24 |         pip install -r requirements.txt
25 |     - name: Run tests
26 |       run: |
27 |         python -m unittest discover
28 | 


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/Dockerfile:
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 1 | # Use an official Python runtime as a parent image
 2 | FROM python:3.11-slim
 3 | 
 4 | # Set the working directory to /app
 5 | WORKDIR /app
 6 | 
 7 | # Copy the current directory contents into the container at /app
 8 | COPY . .
 9 | 
10 | # Install any needed packages specified in requirements.txt
11 | RUN pip install --no-cache-dir -r requirements.txt gunicorn
12 | 
13 | # Make port 5000 available to the world outside this container
14 | EXPOSE 5000
15 | 
16 | # Define environment variable
17 | ENV NAME World
18 | 
19 | # Run app.py when the container launches
20 | CMD ["gunicorn", "-w", "4", "-b", "0.0.0.0:5000", "app.server:app"]
21 | 
22 | # Create a non-root user and switch to it
23 | RUN adduser --disabled-password --gecos "" appuser
24 | USER appuser
25 | 
26 | # Health check
27 | HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
28 |   CMD curl -f http://localhost:5000/ || exit 1
29 | 


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/app/model.py:
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 1 | 
 2 | import pandas as pd
 3 | from sklearn.datasets import fetch_california_housing
 4 | from sklearn.model_selection import train_test_split
 5 | from sklearn.linear_model import LinearRegression
 6 | from sklearn.metrics import mean_squared_error
 7 | from joblib import dump
 8 | 
 9 | def train_model():
10 |     # Load data
11 |     data = fetch_california_housing()
12 |     df = pd.DataFrame(data.data, columns=data.feature_names)
13 |     df['TARGET'] = data.target
14 | 
15 |     # Split data
16 |     X = df.drop('TARGET', axis=1)
17 |     y = df['TARGET']
18 |     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
19 | 
20 |     # Train model
21 |     model = LinearRegression()
22 |     model.fit(X_train, y_train)
23 | 
24 |     # Save the model
25 |     dump(model, 'app/california_housing_model.joblib')
26 | 
27 |     # Predict & Evaluate
28 |     predictions = model.predict(X_test)
29 |     mse = mean_squared_error(y_test, predictions)
30 |     print(f"Model MSE: {mse}")
31 | 
32 | if __name__ == "__main__":
33 |     train_model()
34 | 


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/static/predict.js:
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 1 | 
 2 | document.addEventListener("DOMContentLoaded", function() {
 3 |     var form = document.getElementById("predictionForm");
 4 |     form.addEventListener("submit", function(event) {
 5 |         event.preventDefault(); // Prevent the default form submission
 6 |         var formData = new FormData(form);
 7 |         var requestData = {};
 8 |         formData.forEach(function(value, key) {
 9 |             requestData[key] = value;
10 |         });
11 | 
12 |         fetch('/predict', {
13 |             method: 'POST',
14 |             headers: {
15 |                 'Content-Type': 'application/json',
16 |             },
17 |             body: JSON.stringify(requestData),
18 |         })
19 |         .then(response => response.json())
20 |         .then(data => {
21 |             document.getElementById('predictionResult').textContent = 'Estimated Price: $' + data.prediction[0].toFixed(2);
22 |         })
23 |         .catch((error) => {
24 |             console.error('Error:', error);
25 |             document.getElementById('predictionResult').textContent = 'Error predicting price.';
26 |         });
27 |     });
28 | });
29 | 


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/app/server.py:
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 1 | 
 2 | from flask import Flask, request, jsonify, render_template
 3 | import numpy as np
 4 | import pandas as pd  # Ensure pandas is imported
 5 | from joblib import load
 6 | import os
 7 | 
 8 | # Define the root directory path
 9 | ROOT_PATH = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
10 | 
11 | # Initialize the Flask application
12 | app = Flask(__name__, root_path=ROOT_PATH)
13 | model = load(os.path.join(ROOT_PATH, 'app', 'california_housing_model.joblib'))
14 | 
15 | @app.route('/')
16 | def index():
17 |     # Print the path to the templates directory for debugging
18 |     print(f"Templates directory: {app.template_folder}")
19 |     return render_template('index.html')
20 | 
21 | @app.route('/predict', methods=['POST'])
22 | def predict():
23 |     try:
24 |         data = request.get_json()  # Get data as JSON
25 |         features = [float(data[key]) for key in sorted(data)]  # Convert and sort the data
26 |         feature_names = ['MedInc', 'HouseAge', 'AveRooms', 'AveBedrms', 'Population', 'AveOccup', 'Latitude', 'Longitude']  # Ensure these match your training data
27 |         df = pd.DataFrame([features], columns=feature_names)
28 |         prediction = model.predict(df)
29 |         return jsonify({'prediction': prediction.tolist()})
30 |     except Exception as e:
31 |         print("Error:", str(e))  # Printing the error might give more insights in debugging
32 |         return jsonify({'error': str(e)}), 400
33 | 
34 | if __name__ == '__main__':
35 |     app.run(debug=True)
36 | 


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/static/style.css:
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 1 | 
 2 | body, html {
 3 |     height: 100%;
 4 |     margin: 0;
 5 |     font-family: Arial, sans-serif;
 6 |     background-color: #eaeaea;
 7 | }
 8 | 
 9 | .wrapper {
10 |     min-height: 100%;
11 |     position: relative;
12 |     padding-bottom: 50px; /* Footer height */
13 | }
14 | 
15 | header {
16 |     background-color: #004b97;
17 |     color: #fff;
18 |     padding: 10px 0;
19 |     text-align: center;
20 | }
21 | 
22 | header h1 {
23 |     margin: 0;
24 | }
25 | 
26 | .form-container {
27 |     width: 60%;
28 |     margin: 30px auto;
29 |     background: #fff;
30 |     padding: 20px;
31 |     box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
32 |     border-radius: 8px;
33 | }
34 | 
35 | .input-group {
36 |     margin-bottom: 10px;
37 | }
38 | 
39 | .input-group label {
40 |     display: block;
41 |     margin-bottom: 5px;
42 | }
43 | 
44 | .input-group input {
45 |     width: 100%;
46 |     padding: 8px;
47 |     margin-bottom: 10px;
48 |     border: 1px solid #ccc;
49 |     border-radius: 4px;
50 | }
51 | 
52 | .submit-btn button {
53 |     width: 100%;
54 |     padding: 10px;
55 |     border: none;
56 |     background-color: #5cb85c;
57 |     color: white;
58 |     font-size: 16px;
59 |     cursor: pointer;
60 |     border-radius: 4px;
61 |     transition: background-color 0.3s;
62 | }
63 | 
64 | .submit-btn button:hover {
65 |     background-color: #4cae4c;
66 | }
67 | 
68 | footer {
69 |     position: absolute;
70 |     width: 100%;
71 |     height: 50px; /* Footer height */
72 |     background-color: #333;
73 |     color: #fff;
74 |     text-align: center;
75 |     bottom: 0;
76 |     left: 0;
77 | }
78 | 
79 | footer p {
80 |     margin: 0;
81 |     padding: 15px;
82 | }
83 | 
84 | /* Add this to your existing style.css content */
85 | .prediction-result {
86 |     margin-top: 20px;
87 |     padding: 10px;
88 |     background-color: #f8f9fa;
89 |     border: 1px solid #ddd;
90 |     text-align: center;
91 |     font-size: 1.2em;
92 |     color: #333;
93 | }
94 | 


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/.github/workflows/GHCR.yml:
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 1 | name: Build and Push Docker image to Github Container Registry
 2 | 
 3 | on:
 4 |   #push:
 5 |     branches:
 6 |       - main
 7 | 
 8 | concurrency:
 9 |   group: ghcr-build-${{ github.ref }}
10 |   cancel-in-progress: true
11 | 
12 | jobs:
13 |   build-and-push:
14 |     runs-on: ubuntu-latest
15 |     outputs:
16 |       image_tag: ${{ steps.set_output.outputs.image_tag }} # This will set the output for the job
17 |     steps:
18 |       - name: Check out the code
19 |         uses: actions/checkout@v2
20 | 
21 |       - name: Log in to GitHub Container Registry
22 |         uses: docker/login-action@v1
23 |         with:
24 |           registry: ghcr.io
25 |           username: ${{ secrets.DOCKER_USERNAME }}
26 |           password: ${{ secrets.DOCKER_PASSWORD }}
27 | 
28 |       - name: Set lowercase repository owner and set image tag
29 |         id: set_output
30 |         run: |
31 |           REPO_OWNER=$(echo ${{ github.repository_owner }} | awk '{print tolower($0)}')
32 |           IMAGE_TAG="v1.2.1"
33 |           echo "REPO_OWNER=$REPO_OWNER" >> $GITHUB_ENV
34 |           echo "IMAGE_TAG=$IMAGE_TAG" >> $GITHUB_ENV
35 |           echo "::set-output name=image_tag::$IMAGE_TAG"  # This sets the output for image tag
36 | 
37 |       - name: Build Docker image with specific tag
38 |         run: |
39 |           echo "Building Image: ghcr.io/${{ env.REPO_OWNER }}/ghcr-realestateapp:${{ env.IMAGE_TAG }}"
40 |           docker build . -t ghcr.io/${{ env.REPO_OWNER }}/ghcr-realestateapp:${{ env.IMAGE_TAG }}
41 | 
42 |       - name: Push Docker image to GitHub Container Registry
43 |         run: |
44 |           echo "Pushing Image: ghcr.io/${{ env.REPO_OWNER }}/ghcr-realestateapp:${{ env.IMAGE_TAG }}"
45 |           docker push ghcr.io/${{ env.REPO_OWNER }}/ghcr-realestateapp:${{ env.IMAGE_TAG }}
46 | 
47 |       - name: Tag and push Docker image with commit SHA
48 |         run: |
49 |           echo "Tagging and Pushing SHA: ${{ github.sha }}"
50 |           docker tag ghcr.io/${{ env.REPO_OWNER }}/ghcr-realestateapp:${{ env.IMAGE_TAG }} ghcr.io/${{ env.REPO_OWNER }}/ghcr-realestateapp:${{ github.sha }}
51 |           docker push ghcr.io/${{ env.REPO_OWNER }}/ghcr-realestateapp:${{ github.sha }}
52 | 


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/templates/index.html:
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 1 | <!DOCTYPE html>
 2 | <html lang="en">
 3 | <head>
 4 |     <meta charset="UTF-8">
 5 |     <meta name="viewport" content="width=device-width, initial-scale=1.0">
 6 |     <title>Real Estate Price Predictor</title>
 7 |     <link rel="stylesheet" href="/static/style.css">
 8 |     <script src="/static/predict.js"></script>
 9 | </head>
10 | <body>
11 |     <div class="wrapper">
12 |         <header>
13 |             <h1>Home Price Estimator</h1>
14 |         </header>
15 |         <main>
16 |             <form id="predictionForm">
17 |                 <div class="input-group">
18 |                     <label for="MedInc">Median Income:</label>
19 |                     <input type="text" id="MedInc" name="MedInc" placeholder="Median Income" required>
20 |                 </div>
21 |                 <div class="input-group">
22 |                     <label for="HouseAge">House Age:</label>
23 |                     <input type="text" id="HouseAge" name="HouseAge" placeholder="House Age" required>
24 |                 </div>
25 |                 <div class="input-group">
26 |                     <label for="AveRooms">Average Rooms:</label>
27 |                     <input type="text" id="AveRooms" name="AveRooms" placeholder="Average Rooms" required>
28 |                 </div>
29 |                 <div class="input-group">
30 |                     <label for="AveBedrms">Average Bedrooms:</label>
31 |                     <input type="text" id="AveBedrms" name="AveBedrms" placeholder="Average Bedrooms" required>
32 |                 </div>
33 |                 <div class="input-group">
34 |                     <label for="Population">Population:</label>
35 |                     <input type="text" id="Population" name="Population" placeholder="Population" required>
36 |                 </div>
37 |                 <div class="input-group">
38 |                     <label for="AveOccup">Average Occupancy:</label>
39 |                     <input type="text" id="AveOccup" name="AveOccup" placeholder="Average Occupancy" required>
40 |                 </div>
41 |                 <div class="input-group">
42 |                     <label for="Latitude">Latitude:</label>
43 |                     <input type="text" id="Latitude" name="Latitude" placeholder="Latitude" required>
44 |                 </div>
45 |                 <div class="input-group">
46 |                     <label for="Longitude">Longitude:</label>
47 |                     <input type="text" id="Longitude" name="Longitude" placeholder="Longitude" required>
48 |                 </div>
49 |                 <div class="submit-btn">
50 |                     <button type="submit">Predict</button>
51 |                 </div>
52 |             </form>
53 |             <div id="predictionResult" class="prediction-result"></div>
54 |         </main>
55 |         <footer>
56 |             <p>&copy; 2024 Real Estate Price Predictor</p>
57 |         </footer>
58 |     </div>
59 | </body>
60 | </html>
61 | 


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/README.md:
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  1 | [![MLOps with Python application](https://github.com/EzioDEVio/MLOps/actions/workflows/main.yml/badge.svg)](https://github.com/EzioDEVio/MLOps/actions/workflows/main.yml)   [![Build and Push Docker image to Github Container Registry](https://github.com/EzioDEVio/MLOps/actions/workflows/GHCR.yml/badge.svg)](https://github.com/EzioDEVio/MLOps/actions/workflows/GHCR.yml)
  2 | ![Stars](https://img.shields.io/github/stars/EzioDEVio/MLOps?style=social)
  3 | ![MIT License](https://img.shields.io/github/license/EzioDEVio/MLOps)
  4 | ![Repo Size](https://img.shields.io/github/repo-size/EzioDEVio/MLOps)
  5 | ![Last Commit](https://img.shields.io/github/last-commit/EzioDEVio/MLOps?color=blue)
  6 | 
  7 | # MLOps Application for Real Estate Price Prediction
  8 | 
  9 | This project demonstrates the application of Machine Learning Operations (MLOps) principles to a real estate price prediction model. It includes setting up a Flask application to serve predictions from a trained model and deploying this application using Docker and integrating it into a CI/CD workflow.
 10 | 
 11 | ## Project Structure
 12 | 
 13 | - `app/`: Contains the Flask application files.
 14 |   - `server.py`: The Flask server file with API endpoints.
 15 | - `models/`: Contains the trained model file.
 16 |   - `california_housing_model.joblib`: Pre-trained scikit-learn model.
 17 | - `templates/`: HTML files for the application frontend.
 18 | - `static/`: CSS and JS files for the frontend.
 19 | - `Dockerfile`: Contains all the commands to assemble the app Docker image.
 20 | - `requirements.txt`: List of packages required for the application.
 21 | 
 22 | ## Setup and Installation
 23 | 
 24 | ### Prerequisites
 25 | 
 26 | - Python 3.8+
 27 | - pip
 28 | - virtualenv (optional)
 29 | 
 30 | ### Local Setup
 31 | 
 32 | 1. **Clone the Repository:**
 33 | 
 34 |    ```bash
 35 |    git clone https://github.com/EzioDEVio/MLOps.git
 36 |    cd MLOps
 37 |    ```
 38 | 
 39 | 2. **Create and Activate a Virtual Environment (optional):**
 40 | 
 41 |    Windows:
 42 |    ```bash
 43 |    python -m venv venv
 44 |    venv\Scripts\activate
 45 |    ```
 46 | 
 47 |    macOS/Linux:
 48 |    ```bash
 49 |    python3 -m venv venv
 50 |    source venv/bin/activate
 51 |    ```
 52 | 
 53 | 3. **Install Dependencies:**
 54 | 
 55 |    ```bash
 56 |    pip install -r requirements.txt
 57 |    ```
 58 | 
 59 | 4. **Run the Application:**
 60 | 
 61 |    ```bash
 62 |    python app/server.py
 63 |    ```
 64 | 
 65 |    Visit `http://127.0.0.1:5000` in your web browser to view the app.
 66 | 
 67 | ## Docker Deployment
 68 | 
 69 | 1. **Build the Docker Image:**
 70 | 
 71 |    ```bash
 72 |    docker build -t mlops-app .
 73 |    ```
 74 | 
 75 | 2. **Run the Docker Container:**
 76 | 
 77 |    ```bash
 78 |    docker run -p 5000:5000 mlops-app
 79 |    ```
 80 | 
 81 |    The application should now be accessible at `http://localhost:5000`.
 82 | 
 83 | ## CI/CD Integration
 84 | 
 85 | This project uses GitHub Actions for Continuous Integration and Continuous Deployment (CI/CD).
 86 | 
 87 | ### Workflow
 88 | 
 89 | 1. **Continuous Integration:**
 90 | 
 91 |    - Build the Docker image.
 92 |    - Run tests (add your tests in the workflow).
 93 | 
 94 | 2. **Continuous Deployment:**
 95 | 
 96 |    - Push the Docker image to a registry (e.g., Docker Hub).
 97 |    - Deploy the image to a cloud service (e.g., AWS, Azure).
 98 | 
 99 | ### Setup GitHub Actions
100 | 
101 | 1. **Create a `.github/workflows` directory in your repository.**
102 | 
103 | 2. **Add a workflow file (e.g., `ci-cd.yml`):**
104 | 
105 |    ```yaml
106 |    name: CI/CD Pipeline
107 | 
108 |    on:
109 |      push:
110 |        branches: [ main ]
111 |      pull_request:
112 |        branches: [ main ]
113 | 
114 |    jobs:
115 |      build:
116 |        runs-on: ubuntu-latest
117 |        steps:
118 |        - uses: actions/checkout@v2
119 |        - name: Set up Python
120 |          uses: actions/setup-python@v2
121 |          with:
122 |            python-version: '3.8'
123 |        - name: Install dependencies
124 |          run: |
125 |            python -m pip install --upgrade pip
126 |            pip install -r requirements.txt
127 |        - name: Build Docker image
128 |          run: docker build -t mlops-app .
129 |        # Add additional steps for testing and deployment
130 |    ```
131 | 
132 | ## Contributing
133 | 
134 | Contributions to this project are welcome! Please fork the repository and submit a pull request with your proposed changes.
135 | 
136 | ## License
137 | 
138 | MIT.
139 | 
140 | 
141 | .
142 | 


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