Update appli19b

.github/workflows/prod.yaml

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+name: Construction image Docker
+
+on: 
+  push:
+    branches:
+      - main
+      - dev
+    tags:
+      - 'v*.*.*'
+
+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: Docker meta
+        id: meta
+        uses: docker/metadata-action@v5
+        with:
+          images: linogaliana/application-correction
+
+      -
+        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: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}

.github/workflows/test.yaml

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+name: Python package
+
+on:
+  push:
+    branches:
+      - main
+      - dev
+
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          # latest python minor
+          python-version: '3.x'
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r requirements.txt
+          pip install pylint
+      - name: Lint
+        run: |
+          pylint src --fail-under=6
+      - name: Test Python code
+        run: python train.py

.gitignore

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+config.yaml
+__pycache__/
+data/**/*.csv
+titanic/
+model.joblib

Dockerfile

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+FROM ubuntu:22.04
+WORKDIR ${HOME}/titanic
+# Install Python
+RUN apt-get -y update && \
+    apt-get install -y python3-pip
+# Install project dependencies
+COPY requirements.txt .
+RUN pip install -r requirements.txt
+COPY train.py .
+COPY src ./src
+COPY api ./api
+CMD ["bash", "-c", "./api/run.sh"]

README.md

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+# Probabilité de survie sur le Titanic [![Construction image Docker](https://github.com/ensae-reproductibilite/application-correction/actions/workflows/prod.yaml/badge.svg)](https://github.com/ensae-reproductibilite/application-correction/actions/workflows/prod.yaml)
+
+Pour pouvoir utiliser ce projet, il 
+est recommandé de créer un fichier `config.yaml`
+ayant la structure suivante:
+
+```yaml
+jeton_api: ####
+data_path: https://minio.lab.sspcloud.fr/lgaliana/ensae-reproductibilite/data/raw/data.csv
+```
+
+Pour installer les dépendances
+
+```bash
+pip install -r requirements.txt
+```

api/main.py

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+"""A simple API to expose our trained RandomForest model for Tutanic survival."""
+from fastapi import FastAPI
+from joblib import load
+
+import pandas as pd
+
+model = load('model.joblib')
+
+app = FastAPI(
+    title="Prédiction de survie sur le Titanic",
+    description=
+    "<b>Application de prédiction de survie sur le Titanic</b> 🚢 <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 = "Survived 🎉" if int(model.predict(df)) == 1 else "Dead ⚰️"
+
+    return prediction

api/run.sh

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+#/bin/bash
+python3 train.py
+uvicorn api.main:app --reload --host "0.0.0.0" --port 5000