init

.dockerignore

@@ -0,0 +1,6 @@
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+*.git
+*myenv

.github/workflows/deploy.yml

@@ -0,0 +1,38 @@
+name: Deploy to Heroku
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout Code
+      uses: actions/checkout@v3
+
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: 3.9  # Match your app's Python version
+
+    - name: Install Dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -r requirements.txt
+
+    - name: Test Application
+      run: |
+        pytest  # Assuming you have tests configured
+
+    - name: Deploy to Heroku
+      env:
+        HEROKU_API_KEY: ${{ secrets.HEROKU_API_KEY }}
+        HEROKU_APP_NAME: ${{ secrets.HEROKU_APP_NAME }}
+      run: |
+        echo "Deploying to Heroku..."
+        heroku container:login
+        heroku container:push web --app $HEROKU_APP_NAME
+        heroku container:release web --app $HEROKU_APP_NAME

Dockerfile

@@ -0,0 +1,24 @@
+# Use the official Python image as a base
+FROM python:3.9-slim
+
+# Set environment variables to prevent Python from writing .pyc files and buffer outputs
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PYTHONUNBUFFERED=1
+
+# Set the working directory inside the container
+WORKDIR /app
+
+# Copy the requirements file to the container
+COPY requirements.txt /app/requirements.txt
+
+# Install the Python dependencies
+RUN pip install -r /app/requirements.txt
+
+# Copy the application code to the container
+COPY . /app
+
+# Expose the port the app runs on
+EXPOSE 8000
+
+# Ensure the application runs on Heroku's dynamic port
+CMD ["sh", "-c", "uvicorn main:app --host 0.0.0.0 --port $PORT"]

IRIS.csv

@@ -0,0 +1,151 @@
+sepal_length,sepal_width,petal_length,petal_width,species
+5.1,3.5,1.4,0.2,Iris-setosa
+4.9,3,1.4,0.2,Iris-setosa
+4.7,3.2,1.3,0.2,Iris-setosa
+4.6,3.1,1.5,0.2,Iris-setosa
+5,3.6,1.4,0.2,Iris-setosa
+5.4,3.9,1.7,0.4,Iris-setosa
+4.6,3.4,1.4,0.3,Iris-setosa
+5,3.4,1.5,0.2,Iris-setosa
+4.4,2.9,1.4,0.2,Iris-setosa
+4.9,3.1,1.5,0.1,Iris-setosa
+5.4,3.7,1.5,0.2,Iris-setosa
+4.8,3.4,1.6,0.2,Iris-setosa
+4.8,3,1.4,0.1,Iris-setosa
+4.3,3,1.1,0.1,Iris-setosa
+5.8,4,1.2,0.2,Iris-setosa
+5.7,4.4,1.5,0.4,Iris-setosa
+5.4,3.9,1.3,0.4,Iris-setosa
+5.1,3.5,1.4,0.3,Iris-setosa
+5.7,3.8,1.7,0.3,Iris-setosa
+5.1,3.8,1.5,0.3,Iris-setosa
+5.4,3.4,1.7,0.2,Iris-setosa
+5.1,3.7,1.5,0.4,Iris-setosa
+4.6,3.6,1,0.2,Iris-setosa
+5.1,3.3,1.7,0.5,Iris-setosa
+4.8,3.4,1.9,0.2,Iris-setosa
+5,3,1.6,0.2,Iris-setosa
+5,3.4,1.6,0.4,Iris-setosa
+5.2,3.5,1.5,0.2,Iris-setosa
+5.2,3.4,1.4,0.2,Iris-setosa
+4.7,3.2,1.6,0.2,Iris-setosa
+4.8,3.1,1.6,0.2,Iris-setosa
+5.4,3.4,1.5,0.4,Iris-setosa
+5.2,4.1,1.5,0.1,Iris-setosa
+5.5,4.2,1.4,0.2,Iris-setosa
+4.9,3.1,1.5,0.1,Iris-setosa
+5,3.2,1.2,0.2,Iris-setosa
+5.5,3.5,1.3,0.2,Iris-setosa
+4.9,3.1,1.5,0.1,Iris-setosa
+4.4,3,1.3,0.2,Iris-setosa
+5.1,3.4,1.5,0.2,Iris-setosa
+5,3.5,1.3,0.3,Iris-setosa
+4.5,2.3,1.3,0.3,Iris-setosa
+4.4,3.2,1.3,0.2,Iris-setosa
+5,3.5,1.6,0.6,Iris-setosa
+5.1,3.8,1.9,0.4,Iris-setosa
+4.8,3,1.4,0.3,Iris-setosa
+5.1,3.8,1.6,0.2,Iris-setosa
+4.6,3.2,1.4,0.2,Iris-setosa
+5.3,3.7,1.5,0.2,Iris-setosa
+5,3.3,1.4,0.2,Iris-setosa
+7,3.2,4.7,1.4,Iris-versicolor
+6.4,3.2,4.5,1.5,Iris-versicolor
+6.9,3.1,4.9,1.5,Iris-versicolor
+5.5,2.3,4,1.3,Iris-versicolor
+6.5,2.8,4.6,1.5,Iris-versicolor
+5.7,2.8,4.5,1.3,Iris-versicolor
+6.3,3.3,4.7,1.6,Iris-versicolor
+4.9,2.4,3.3,1,Iris-versicolor
+6.6,2.9,4.6,1.3,Iris-versicolor
+5.2,2.7,3.9,1.4,Iris-versicolor
+5,2,3.5,1,Iris-versicolor
+5.9,3,4.2,1.5,Iris-versicolor
+6,2.2,4,1,Iris-versicolor
+6.1,2.9,4.7,1.4,Iris-versicolor
+5.6,2.9,3.6,1.3,Iris-versicolor
+6.7,3.1,4.4,1.4,Iris-versicolor
+5.6,3,4.5,1.5,Iris-versicolor
+5.8,2.7,4.1,1,Iris-versicolor
+6.2,2.2,4.5,1.5,Iris-versicolor
+5.6,2.5,3.9,1.1,Iris-versicolor
+5.9,3.2,4.8,1.8,Iris-versicolor
+6.1,2.8,4,1.3,Iris-versicolor
+6.3,2.5,4.9,1.5,Iris-versicolor
+6.1,2.8,4.7,1.2,Iris-versicolor
+6.4,2.9,4.3,1.3,Iris-versicolor
+6.6,3,4.4,1.4,Iris-versicolor
+6.8,2.8,4.8,1.4,Iris-versicolor
+6.7,3,5,1.7,Iris-versicolor
+6,2.9,4.5,1.5,Iris-versicolor
+5.7,2.6,3.5,1,Iris-versicolor
+5.5,2.4,3.8,1.1,Iris-versicolor
+5.5,2.4,3.7,1,Iris-versicolor
+5.8,2.7,3.9,1.2,Iris-versicolor
+6,2.7,5.1,1.6,Iris-versicolor
+5.4,3,4.5,1.5,Iris-versicolor
+6,3.4,4.5,1.6,Iris-versicolor
+6.7,3.1,4.7,1.5,Iris-versicolor
+6.3,2.3,4.4,1.3,Iris-versicolor
+5.6,3,4.1,1.3,Iris-versicolor
+5.5,2.5,4,1.3,Iris-versicolor
+5.5,2.6,4.4,1.2,Iris-versicolor
+6.1,3,4.6,1.4,Iris-versicolor
+5.8,2.6,4,1.2,Iris-versicolor
+5,2.3,3.3,1,Iris-versicolor
+5.6,2.7,4.2,1.3,Iris-versicolor
+5.7,3,4.2,1.2,Iris-versicolor
+5.7,2.9,4.2,1.3,Iris-versicolor
+6.2,2.9,4.3,1.3,Iris-versicolor
+5.1,2.5,3,1.1,Iris-versicolor
+5.7,2.8,4.1,1.3,Iris-versicolor
+6.3,3.3,6,2.5,Iris-virginica
+5.8,2.7,5.1,1.9,Iris-virginica
+7.1,3,5.9,2.1,Iris-virginica
+6.3,2.9,5.6,1.8,Iris-virginica
+6.5,3,5.8,2.2,Iris-virginica
+7.6,3,6.6,2.1,Iris-virginica
+4.9,2.5,4.5,1.7,Iris-virginica
+7.3,2.9,6.3,1.8,Iris-virginica
+6.7,2.5,5.8,1.8,Iris-virginica
+7.2,3.6,6.1,2.5,Iris-virginica
+6.5,3.2,5.1,2,Iris-virginica
+6.4,2.7,5.3,1.9,Iris-virginica
+6.8,3,5.5,2.1,Iris-virginica
+5.7,2.5,5,2,Iris-virginica
+5.8,2.8,5.1,2.4,Iris-virginica
+6.4,3.2,5.3,2.3,Iris-virginica
+6.5,3,5.5,1.8,Iris-virginica
+7.7,3.8,6.7,2.2,Iris-virginica
+7.7,2.6,6.9,2.3,Iris-virginica
+6,2.2,5,1.5,Iris-virginica
+6.9,3.2,5.7,2.3,Iris-virginica
+5.6,2.8,4.9,2,Iris-virginica
+7.7,2.8,6.7,2,Iris-virginica
+6.3,2.7,4.9,1.8,Iris-virginica
+6.7,3.3,5.7,2.1,Iris-virginica
+7.2,3.2,6,1.8,Iris-virginica
+6.2,2.8,4.8,1.8,Iris-virginica
+6.1,3,4.9,1.8,Iris-virginica
+6.4,2.8,5.6,2.1,Iris-virginica
+7.2,3,5.8,1.6,Iris-virginica
+7.4,2.8,6.1,1.9,Iris-virginica
+7.9,3.8,6.4,2,Iris-virginica
+6.4,2.8,5.6,2.2,Iris-virginica
+6.3,2.8,5.1,1.5,Iris-virginica
+6.1,2.6,5.6,1.4,Iris-virginica
+7.7,3,6.1,2.3,Iris-virginica
+6.3,3.4,5.6,2.4,Iris-virginica
+6.4,3.1,5.5,1.8,Iris-virginica
+6,3,4.8,1.8,Iris-virginica
+6.9,3.1,5.4,2.1,Iris-virginica
+6.7,3.1,5.6,2.4,Iris-virginica
+6.9,3.1,5.1,2.3,Iris-virginica
+5.8,2.7,5.1,1.9,Iris-virginica
+6.8,3.2,5.9,2.3,Iris-virginica
+6.7,3.3,5.7,2.5,Iris-virginica
+6.7,3,5.2,2.3,Iris-virginica
+6.3,2.5,5,1.9,Iris-virginica
+6.5,3,5.2,2,Iris-virginica
+6.2,3.4,5.4,2.3,Iris-virginica
+5.9,3,5.1,1.8,Iris-virginica

main.py

@@ -0,0 +1,85 @@
+from fastapi import FastAPI, Form, Request
+from fastapi.responses import HTMLResponse, JSONResponse
+from fastapi.staticfiles import StaticFiles
+import logging
+import joblib
+import numpy as np
+import pandas as pd
+import os
+import uvicorn
+
+
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+    handlers=[logging.StreamHandler()]
+)
+
+logger = logging.getLogger("FastAPI Iris Predictor")
+
+try:
+    model = joblib.load("model.pkl")
+    logger.info("Model loaded successfully.")
+except Exception as e:
+    logger.error("Failed to load the model: %s", e)
+    raise RuntimeError("Model loading failed.") from e
+
+app = FastAPI()
+
+# Mount static folder for serving static files like CSS, HTML
+app.mount("/static", StaticFiles(directory="static"), name="static")
+
+
+species_mapping = {0: "Iris Setosa", 1: "Iris Versicolor", 2: "Iris Virginica"}
+
+@app.get("/", response_class=HTMLResponse)
+async def home():
+    try: 
+    # Serve the home page
+        with open("static/index.html", "r") as file:
+            logger.info("Home page served.")
+            return file.read()
+    except Exception as e:
+        logger.error("Error serving home page: %s", e)
+        return HTMLResponse(content="Error loading the home page.", status_code=500)
+
+@app.get("/predict", response_class=HTMLResponse)
+async def predict():
+    # Serve the prediction page
+    try:
+        with open("static/predict.html", "r") as file:
+            logger.info("Prediction page served.")
+            return file.read()
+    except Exception as e:
+        logger.error("Error serving prediction page: %s", e)
+        return HTMLResponse(content="Error loading the prediction page.", status_code=500)
+
+@app.post("/predict")
+async def predict_species(
+    sepal_length: float = Form(...), 
+    sepal_width: float = Form(...), 
+    petal_length: float = Form(...), 
+    petal_width: float = Form(...)
+):
+    feature_names = ["sepal_length", "sepal_width", "petal_length", "petal_width"]
+    try: 
+        input_df = pd.DataFrame([[sepal_length, sepal_width, petal_length, petal_width]], columns=feature_names)
+        logger.info("Input data received: %s", input_df)
+
+        # Predict using the model
+        prediction = model.predict(input_df)[0]
+
+        # Get the species name
+        species = species_mapping.get(prediction, "Unknown")
+        logger.info("Prediction made: %s", species)
+
+        return { "prediction": species}
+    except Exception as e:
+        logger.error("Error making prediction: %s", e)
+        return JSONResponse(content={"error": "Failed to make a prediction"}, status_code=500)
+
+if __name__ == "__main__":
+    port = int(os.getenv("PORT", 8000))  # Use Heroku's PORT 
+    uvicorn.run(app, host="0.0.0.0", port=port)
+ 

requirements.txt

@@ -0,0 +1,10 @@
+fastapi
+joblib
+numpy
+pandas
+pydantic
+pytest
+httpx
+uvicorn
+scikit-learn
+python-multipart

static/index.html

@@ -0,0 +1,18 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Iris Prediction Home</title>
+    <link rel="stylesheet" href="/static/styles.css">  
+    
+</head>
+<body>
+    <div class="container">
+        <h1>Welcome to Iris Species Predictor</h1>
+        <p>This application predicts the species of an Iris flower based on its features.</p>
+        <a href="/predict" class="button">Go to Prediction</a>
+        <p>&copy; Meta Brains. All rights reserved.</p>
+    </div>
+</body>
+</html>

static/predict.html

@@ -0,0 +1,57 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Iris Prediction</title>
+    <link rel="stylesheet" href="/static/styles.css">
+    <script>
+        // JavaScript function to handle the form submission
+        async function submitForm(event) {
+            event.preventDefault();  // Prevent the default form submission
+
+            // Get the form data
+            const formData = new FormData(event.target);
+
+            // Prepare the data to send to the FastAPI endpoint
+            const data = new URLSearchParams();
+            for (const [key, value] of formData.entries()) {
+                data.append(key, value);
+            }
+
+            // Send the data to FastAPI via POST request
+            const response = await fetch("/predict", {
+                method: "POST",
+                body: data
+            });
+
+            // Get the JSON response and update the result on the page
+            const result = await response.json();
+            document.getElementById("prediction").innerText = "Predicted Species: " + result.prediction;
+        }
+    </script>
+</head>
+<body>
+    <div class="container">
+        <h1>Predict Iris Species</h1>
+        <form onsubmit="submitForm(event)">
+            <label for="sepal_length">Sepal Length (cm):</label>
+            <input type="number" step="0.1" name="sepal_length" id="sepal_length" required>
+
+            <label for="sepal_width">Sepal Width (cm):</label>
+            <input type="number" step="0.1" name="sepal_width" id="sepal_width" required>
+
+            <label for="petal_length">Petal Length (cm):</label>
+            <input type="number" step="0.1" name="petal_length" id="petal_length" required>
+
+            <label for="petal_width">Petal Width (cm):</label>
+            <input type="number" step="0.1" name="petal_width" id="petal_width" required>
+
+            <button type="submit" class="button">Predict</button>
+        </form>
+
+        <!-- Display prediction result here -->
+        <div id="prediction"></div>
+    </div>
+</body>
+</html>

static/styles.css

@@ -0,0 +1,65 @@
+body {
+    font-family: Arial, sans-serif;
+    background: linear-gradient(135deg, #87CEEB, #FFDEE9);
+    margin: 0;
+    padding: 0;
+}
+
+.container {
+    text-align: center;
+    margin: 50px auto;
+    max-width: 600px;
+    background: white;
+    padding: 20px;
+    border-radius: 10px;
+    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2);
+}
+
+h1 {
+    color: #333;
+}
+
+p {
+    color: #555;
+}
+
+form {
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+}
+
+form label {
+    margin-top: 10px;
+    font-weight: bold;
+}
+
+form input {
+    margin: 10px 0;
+    padding: 10px;
+    width: 80%;
+    border: 1px solid #ccc;
+    border-radius: 5px;
+}
+
+.button {
+    display: inline-block;
+    background: #4CAF50;
+    color: white;
+    padding: 10px 20px;
+    margin: 20px 0;
+    text-decoration: none;
+    border-radius: 5px;
+    transition: background 0.3s;
+}
+
+.button:hover {
+    background: #45a049;
+}
+
+.result {
+    margin-top: 20px;
+    font-size: 1.2em;
+    color: #333;
+    font-weight: bold;
+}

test_integration.py

@@ -0,0 +1,27 @@
+import pytest
+from fastapi.testclient import TestClient
+from main import app
+
+client = TestClient(app)
+
+def test_home_endpoint():
+    """Test if the home page loads successfully."""
+    response = client.get("/")
+    assert response.status_code == 200, "Failed to load the home page."
+
+def test_predict_page_endpoint():
+    """Test if the prediction page loads successfully."""
+    response = client.get("/predict")
+    assert response.status_code == 200, "Failed to load the prediction page."
+
+def test_predict_species_endpoint():
+    """Test if the predict endpoint works."""
+    payload = {
+        "sepal_length": 5.1,
+        "sepal_width": 3.5,
+        "petal_length": 1.4,
+        "petal_width": 0.2
+    }
+    response = client.post("/predict", data=payload)
+    assert response.status_code == 200, "Failed to predict species."
+    assert "prediction" in response.json(), "Response missing prediction field." 

test_unit.py

@@ -0,0 +1,15 @@
+import pytest
+import pandas as pd
+from main import model, species_mapping
+
+
+def test_model_prediction():
+    # Arrange: Create a test input DataFrame
+    input_df = pd.DataFrame([[5.1, 3.5, 1.4, 0.2]], columns=["sepal_length", "sepal_width", "petal_length", "petal_width"])
+    
+    # Act: Perform prediction
+    prediction = model.predict(input_df)[0]
+    species = species_mapping.get(prediction, "Unknown")
+    
+    # Assert: Check prediction result
+    assert species == "Iris Setosa", "The prediction did not return the expected result."