Appli18 dev

.github/workflows/docker.yaml

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+name: Construction image Docker
+
+on:
+  push:
+    branches:
+      - main
+      - dev
+
+
+jobs:
+  docker:
+    runs-on: ubuntu-latest
+    steps:
+      -
+        name: Set up QEMU
+        uses: docker/setup-qemu-action@v3
+      -
+        name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+      -
+        name: Login to Docker Hub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+      -
+        name: Build and push
+        uses: docker/build-push-action@v5
+        with:
+          push: true
+          tags: remiguy/application:latest

.github/workflows/test.yaml

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+name: Python package
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v6
+
+      - name: Set up Python
+        uses: actions/setup-python@v6
+        with:
+          # latest python minor
+          python-version: '3.x'
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install uv
+          uv sync
+
+      - name: Test code quality
+        run: |
+          uv sync
+          uv run --with pylint pylint src --fail-under=5
+
+      - name: Test that code runs smoothly
+        env:
+          JETON_API: ${{ secrets.JETON_API }}
+        run: uv run train.py
+
+      - name: Upload recording.log artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: log-file
+          path: recording.log
+          if-no-files-found: warn

.gitignore

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+config.yaml
+__pycache__/
+.env
+*.log
+data/
+model.skops

Dockerfile

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+FROM ubuntu:22.04
+
+# Install Python
+RUN apt-get -y update && \
+    apt-get install -y python3-pip curl
+
+# Install uv
+RUN curl -LsSf https://astral.sh/uv/install.sh | sh
+ENV PATH="/root/.local/bin/:$PATH"
+
+# Install project dependencies
+COPY pyproject.toml .
+RUN uv sync
+
+COPY app ./app
+COPY train.py .
+COPY src ./src
+CMD ["bash", "-c", "./app/run.sh"]

README.md

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+# Probabilité de survie sur le Titanic
+
+Pour pouvoir utiliser ce projet, il 
+est recommandé de créer un fichier `.env`
+ayant la structure suivante:
+
+```yaml
+JETON_API="####" #renseigner la valeur pertinente
+```

app/api.py

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+"""A simple API to expose our trained RandomForest model for Tutanic survival."""
+
+from fastapi import FastAPI
+import skops.io as sio
+import pandas as pd
+
+unknown_types = sio.get_untrusted_types(file="model.skops")
+model = sio.load("model.skops", trusted=unknown_types)
+
+app = FastAPI(
+    title="Prédiction de survie sur le Titanic",
+    description="Application de prédiction de survie sur le Titanic 🚢 <br>Une version par API pour faciliter la réutilisation du modèle 🚀"
+    + '<br><br><img src="https://media.vogue.fr/photos/5faac06d39c5194ff9752ec9/1:1/w_2404,h_2404,c_limit/076_CHL_126884.jpg" width="200">',
+)
+
+
+@app.get("/", tags=["Welcome"])
+def show_welcome_page():
+    """
+    Show welcome page with model name and version.
+    """
+
+    return {
+        "Message": "API de prédiction de survie sur le Titanic",
+        "Model_name": "Titanic ML",
+        "Model_version": "0.1",
+    }
+
+
+@app.get("/predict", tags=["Predict"])
+async def predict(
+    sex: str = "female", age: float = 29.0, fare: float = 16.5, embarked: str = "S"
+) -> str:
+    """ """
+
+    df = pd.DataFrame(
+        {
+            "Sex": [sex],
+            "Age": [age],
+            "Fare": [fare],
+            "Embarked": [embarked],
+        }
+    )
+
+    prediction = int(model.predict(df)[0])
+
+    prediction = "Survived 🎉" if prediction == 1 else "Dead ⚰️"
+
+    return prediction

app/run.sh

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+uv run train.py
+uv run uvicorn app.api:app --host "0.0.0.0"

deployment/deployment.yaml

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+#| filename: "deployment/deployment.yaml"
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: titanic-deployment
+  labels:
+    app: titanic
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: titanic
+  template:
+    metadata:
+      labels:
+        app: titanic
+    spec:
+      containers:
+      - name: titanic
+        image: remiguy/application:latest
+        ports:
+        - containerPort: 8000
+        env:
+        - name: JETON_API
+          valueFrom:
+            secretKeyRef:
+              name: api-jeton
+              key: JETON_API

deployment/ingress.yaml

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+#| filename: "deployment/ingress.yaml"
+apiVersion: networking.k8s.io/v1
+kind: Ingress
+metadata:
+  name: titanic-ingress
+spec:
+  ingressClassName: nginx
+  tls:
+  - hosts:
+    - remtita.lab.sspcloud.fr
+  rules:
+  - host: remtita.lab.sspcloud.fr
+    http:
+      paths:
+      - path: /
+        pathType: Prefix
+        backend:
+          service:
+            name: titanic-service
+            port:
+              number: 80

deployment/service.yaml

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+apiVersion: v1
+kind: Service
+metadata:
+  name: titanic-service
+spec:
+  selector:
+    app: titanic
+  ports:
+    - protocol: TCP
+      port: 80
+      targetPort: 8000

install.sh

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+#!/usr/bin/env bash
+
+# Ensure everything is installed
+sudo apt-get -y update
+sudo apt-get install -y python3-pip python3-venv curl
+
+# Install uv
+curl -LsSf https://astral.sh/uv/install.sh | sh
+
+# Restore environment
+uv sync