Feature/uv

.github/workflows/ci.yml

@@ -0,0 +1,57 @@
+name: CI
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    branches: [ master ]
+
+jobs:
+  ruff:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: chartboost/ruff-action@v1
+
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.10', '3.11', '3.12']
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install uv
+        run: |
+          curl -LsSf https://astral.sh/uv/install.sh | sh
+          echo "$HOME/.cargo/bin" >> $GITHUB_PATH
+
+      - name: Create and activate virtual environment
+        run: |
+          uv venv
+          echo "${{ github.workspace }}/.venv/bin" >> $GITHUB_PATH
+
+      - name: Install dependencies
+        run: |
+          uv pip install 'setuptools[pkg_resources]'
+          uv pip install -e ".[test]"
+
+      - name: Run tests with coverage
+        run: |
+          uv pip install pytest-cov
+          pytest -s tests/ --cov=numerblox --cov-report term-missing
+
+      - name: Build wheel
+        run: |
+          uv pip install build
+          python -m build --wheel
+
+      - name: Install built wheel
+        run: |
+          uv pip install dist/*.whl

.github/workflows/codecov.yml

@@ -6,34 +6,44 @@ on:
     - master
 
 jobs:
-  build:
+  ruff:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+  coverage:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.11']
+        python-version: ['3.12']
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python-version }}
+    - name: Install uv
+      run: |
+        curl -LsSf https://astral.sh/uv/install.sh | sh
+        echo "$HOME/.cargo/bin" >> $GITHUB_PATH
+    - name: Create and activate virtual environment
+      run: |
+        uv venv
+        echo "${{ github.workspace }}/.venv/bin" >> $GITHUB_PATH
     - name: Install dependencies
       run: |
-        python -m pip install --upgrade pip
-        python -m pip install poetry
-        poetry config virtualenvs.create false --local
-        poetry install
+        uv pip install 'setuptools[pkg_resources]'
+        uv pip install -e ".[test]"
     - name: Run tests
       run: |
-        poetry run pytest -s tests/ --cov=numerblox --cov-report term-missing --cov-report=xml
+        uv pip install pytest pytest-cov
+        pytest -s tests/ --cov=numerblox --cov-report term-missing --cov-report=xml
     - name: Upload coverage to Codecov
       uses: codecov/codecov-action@v3
       env:
         CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
       with:
-        directory: ./coverage/reports/
+        files: ./coverage.xml
         fail_ci_if_error: false
         verbose: true
-        files: ./coverage.xml
-

.github/workflows/deploy-mkdocs.yml

@@ -10,20 +10,30 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout
-        uses: actions/checkout@v2
+        uses: actions/checkout@v3
 
       - name: Set up Python
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
-          python-version: '3.11'
+          python-version: '3.12'
+
+      - name: Install uv
+        run: |
+          curl -LsSf https://astral.sh/uv/install.sh | sh
+          echo "$HOME/.cargo/bin" >> $GITHUB_PATH
+
+      - name: Create and activate virtual environment
+        run: |
+          uv venv
+          echo "${{ github.workspace }}/.venv/bin" >> $GITHUB_PATH
 
       - name: Install dependencies
         run: |
-          pip install poetry
-          poetry install
+          uv pip install 'setuptools[pkg_resources]'
+          uv pip install mkdocs mkdocs-material
 
       - name: Build the MkDocs site
-        run: poetry run mkdocs build
+        run: mkdocs build
 
       - name: Deploy to GitHub Pages
         uses: peaceiris/actions-gh-pages@v3

docs/numerframe.md

@@ -84,8 +84,6 @@ X, y = df.get_feature_target_pair(multi_target=True)
 
 # Fetch data for specified eras
 X, y = df.get_era_batch(eras=['0001', '0002'])
-# Optionally get Tensorflow tensors for NN training
-X, y = nf.get_era_batch(eras=['0001', '0002'], convert_to_tf=True)
 
 # Since every operation returns a NumerFrame they can be chained.
 # An example chained operation is getting features and targets for the last 2 eras.

examples/end_to_end.ipynb

@@ -29,15 +29,16 @@
     }
    ],
    "source": [
-    "from xgboost import XGBRegressor\n",
-    "from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor\n",
+    "from sklearn.compose import ColumnTransformer, make_column_transformer\n",
     "from sklearn.model_selection import TimeSeriesSplit\n",
     "from sklearn.pipeline import make_pipeline\n",
-    "from sklearn.compose import make_column_transformer, ColumnTransformer\n",
-    "from numerblox.preprocessing import GroupStatsPreProcessor\n",
-    "from numerblox.meta import CrossValEstimator, make_meta_pipeline\n",
+    "from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor\n",
+    "from xgboost import XGBRegressor\n",
+    "\n",
     "from numerblox.ensemble import NumeraiEnsemble, PredictionReducer\n",
-    "from numerblox.neutralizers import FeatureNeutralizer"
+    "from numerblox.meta import CrossValEstimator, make_meta_pipeline\n",
+    "from numerblox.neutralizers import FeatureNeutralizer\n",
+    "from numerblox.preprocessing import GroupStatsPreProcessor"
    ]
   },
   {
@@ -623,13 +624,10 @@
    ],
    "source": [
     "# Preprocessing\n",
-    "gpp = GroupStatsPreProcessor(groups=['sunshine', 'rain'])\n",
+    "gpp = GroupStatsPreProcessor(groups=[\"sunshine\", \"rain\"])\n",
     "fncv3_selector = ColumnSelector(fncv3_cols)\n",
     "\n",
-    "preproc_pipe = ColumnTransformer([\n",
-    "    ('gpp', gpp, X.columns.tolist()),\n",
-    "    ('fncv3_selector', fncv3_selector, fncv3_cols)\n",
-    "    ])\n",
+    "preproc_pipe = ColumnTransformer([(\"gpp\", gpp, X.columns.tolist()), (\"fncv3_selector\", fncv3_selector, fncv3_cols)])\n",
     "\n",
     "# Model\n",
     "xgb = DecisionTreeRegressor()\n",
@@ -708,7 +706,7 @@
    "outputs": [],
    "source": [
     "model = DecisionTreeClassifier()\n",
-    "crossval1 = CrossValEstimator(estimator=model, cv=TimeSeriesSplit(n_splits=3), predict_func='predict_proba')\n",
+    "crossval1 = CrossValEstimator(estimator=model, cv=TimeSeriesSplit(n_splits=3), predict_func=\"predict_proba\")\n",
     "pred_rud = PredictionReducer(n_models=3, n_classes=5)\n",
     "ens2 = NumeraiEnsemble(donate_weighted=True)\n",
     "neut2 = FeatureNeutralizer(proportion=0.5)\n",
@@ -1808,7 +1806,7 @@
     "pipes = []\n",
     "for i in range(3):\n",
     "    model = XGBRegressor()\n",
-    "    crossval = CrossValEstimator(estimator=model, cv=TimeSeriesSplit(n_splits=5), predict_func='predict')\n",
+    "    crossval = CrossValEstimator(estimator=model, cv=TimeSeriesSplit(n_splits=5), predict_func=\"predict\")\n",
     "    pipe = make_pipeline(crossval)\n",
     "    pipes.append(pipe)\n",
     "\n",