Dev

.github/workflows/test.yml

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+# This workflow will install Python dependencies, run tests and lint with a single version of Python
+# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
+
+name: Python application
+
+on:
+  push:
+    branches: [ "main" ]
+  pull_request:
+    branches: [ "main" ]
+
+permissions:
+  contents: read
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v4
+    - name: Set up Python 3.10
+      uses: actions/setup-python@v3
+      with:
+        python-version: "3.10"
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install flake8 pytest
+        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+    - name: Lint with flake8
+      run: |
+        # stop the build if there are Python syntax errors or undefined names
+        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+    - name: Test with pytest
+      run: |
+        pytest
+    - name: Run main
+      run: |
+          python main.py

.gitignore

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+__pycache__/
+data/derived/test.csv
+data/derived/train.csv
+titanic-env/

README.md

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+# Probabilité de survie sur le Titanic
+
+Pour pouvoir utiliser ce projet, il 
+est recommandé de créer un fichier `config.yaml`
+ayant la structure suivante:
+
+```yaml
+jeton_api: ####
+data_path: ####
+```

configuration/config.yaml

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+jeton_api: "$trotskitueleski1917"
+data_path: "https://minio.lab.sspcloud.fr/meilametayebjee/ensae-reproductibilite/data/raw/data.csv"
+train_path: "data/derived/train.csv"
+test_path: "data/derived/test.csv"

docs/main.py

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+"""
+Prediction de la survie d'un individu sur le Titanic
+"""
+
+import argparse
+
+from titanicml.data.import_data import import_yaml_config, process_data
+from titanicml.pipeline.build_pipeline import split, build_pipeline
+from titanicml.models.train_evaluate import evaluate
+
+parser = argparse.ArgumentParser(description="Paramètres du random forest")
+parser.add_argument("--n_trees", type=int, default=20, help="Nombre d'arbres")
+args = parser.parse_args()
+
+N_TREES = args.n_trees
+print("Nombre d'arbres : ", N_TREES)
+
+config = import_yaml_config("configuration/config.yaml")
+
+DATA_PATH = config.get("data_path", "data.csv")
+TRAIN_PATH = config.get("train_path", "train.csv")
+TEST_PATH = config.get("test_path", "test.csv")
+TEST_FRACTION = config.get("test_fraction", 0.1)
+MAX_DEPTH = None
+MAX_FEATURES = "sqrt"
+
+
+# IMPORT ET EXPLORATION DONNEES --------------------------------
+
+TrainingData = process_data(DATA_PATH)
+
+# SPLIT TRAIN/TEST --------------------------------
+
+X_train, X_test, y_train, y_test = split(
+    TrainingData,
+    test_fraction=TEST_FRACTION,
+    train_path=TRAIN_PATH,
+    test_path=TEST_PATH,
+)
+# PIPELINE ----------------------------
+
+# Définition des variables
+numeric_features = ["Age", "Fare"]
+categorical_features = ["Embarked", "Sex"]
+
+pipe = build_pipeline(
+    numeric_features,
+    categorical_features,
+    n_trees=N_TREES,
+    max_depth=MAX_DEPTH,
+    max_features=MAX_FEATURES,
+)
+
+# ESTIMATION ET EVALUATION ----------------------
+
+pipe.fit(X_train, y_train)
+evaluate(pipe, X_test, y_test)

install.sh

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+#!/bin/bash
+# Install Python
+apt-get -y update
+apt-get install -y python3-pip python3-venv
+# Create empty virtual environment
+python3 -m venv titanic
+source titanic/bin/activate
+# Install project dependencies
+pip install -r requirements.txt

pyproject.toml

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+[tool.poetry]
+name = "titanicml"
+version = "0.0.1"
+description = "Awesome Machine Learning project"
+authors = ["Daffy Duck <[email protected]>", "Mickey Mouse"]
+license = "MIT"
+readme = "README.md"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.pytest.ini_options]
+log_cli = true
+log_cli_level = "WARNING"
+log_cli_format = "%(asctime)s [%(levelname)8s] %(message)s (%(filename)s:%(lineno)s)"
+log_cli_date_format = "%Y-%m-%d %H:%M:%S"

requirements.txt

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+contourpy==1.3.0
+cycler==0.12.1
+fonttools==4.53.1
+joblib==1.4.2
+kiwisolver==1.4.7
+matplotlib==3.9.2
+numpy==2.1.1
+packaging==24.1
+pandas==2.2.2
+pillow==10.4.0
+protobuf==4.25.3
+pyarrow==17.0.0
+pyparsing==3.1.4
+python-dateutil==2.9.0.post0
+pytz==2024.1
+PyYAML==6.0.2
+scikit-learn==1.5.1
+scipy==1.14.1
+seaborn==0.13.2
+setuptools==69.5.1
+six==1.16.0
+threadpoolctl==3.5.0
+tzdata==2024.1
+wheel==0.44.0
+zstandard==0.23.0