[Feature] add memory optimization, weighted regression

.github/CODEOWNERS

@@ -0,0 +1,2 @@
+# ALL
+@RektPunk

.github/workflows/ci.yaml

@@ -0,0 +1,33 @@
+name: Rust CI
+
+on:
+  pull_request:
+    types: [opened, reopened, synchronize]
+  push:
+    branches:
+      - main
+
+env:
+  CARGO_TERM_COLOR: always
+
+jobs:
+  quality-check:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v6
+      - name: Install Rust
+        uses: dtolnay/rust-toolchain@stable
+        with:
+          components: rustfmt, clippy
+
+      - name: Rust Cache
+        uses: Swatinem/rust-cache@v2
+
+      - name: Check Formatting
+        run: cargo fmt --check
+
+      - name: Run Clippy
+        run: cargo clippy -- -D warnings
+
+      - name: Run Tests
+        run: cargo test --verbose --release

.github/workflows/pyci.yaml

@@ -0,0 +1,36 @@
+name: Tests
+
+on:
+  pull_request:
+    types: [opened, reopened, synchronize]
+  push:
+    branches:
+      - main
+
+jobs:
+  run-pytest:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v6
+
+      - name: Set up python
+        uses: actions/setup-python@v6
+        with:
+          python-version: "3.10"
+
+      - name: Install Rust
+        uses: dtolnay/rust-toolchain@stable
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v7
+
+      - name: Install dependencies
+        run: uv sync --all-extras --dev
+
+      - name: Build and Install Extension
+        run: uvx maturin develop --release
+
+      - name: Run tests
+        run: uv run pytest python/tests/

.github/workflows/release.yaml

@@ -0,0 +1,65 @@
+name: Publish to PyPI
+
+on:
+  push:
+    tags:
+      - "v*.*.*"
+
+permissions:
+  contents: read
+
+jobs:
+  build_wheels:
+    name: Build wheels on ${{ matrix.os }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ubuntu-latest, windows-latest, macos-latest]
+
+    steps:
+      - uses: actions/checkout@v6
+      - uses: actions/setup-python@v6
+        with:
+          python-version: "3.10"
+
+      - name: Build wheels
+        uses: PyO3/maturin-action@v1
+        with:
+          command: build
+          args: --release --out dist
+          manylinux: auto
+          sccache: "true"
+
+      - name: Upload wheels
+        uses: actions/upload-artifact@v7
+        with:
+          name: wheels-${{ matrix.os }}
+          path: dist
+
+  publish:
+    name: Publish to PyPI
+    runs-on: ubuntu-latest
+    needs: [build_wheels]
+    steps:
+      - uses: actions/checkout@v6
+
+      - name: Download all wheels
+        uses: actions/download-artifact@v8
+        with:
+          path: dist
+          pattern: wheels-*
+          merge-multiple: true
+
+      - name: Build sdist
+        uses: PyO3/maturin-action@v1
+        with:
+          command: sdist
+          args: --out dist
+
+      - name: Publish to PyPI
+        uses: PyO3/maturin-action@v1
+        env:
+          MATURIN_PYPI_TOKEN: ${{ secrets.PYPI_TOKEN }}
+        with:
+          command: upload
+          args: --non-interactive --skip-existing dist/*

.gitignore

@@ -12,3 +12,14 @@ target
 # Generated by cargo mutants
 # Contains mutation testing data
 **/mutants.out*/
+
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+*.whl
+.python-version
+
+dist/
+.venv
+.DS_Store

Cargo.toml

@@ -1,9 +1,15 @@
 [package]
 name = "xuplift"
-version = "0.1.0"
+version = "0.0.1"
 edition = "2024"
 
+[lib]
+name = "xuplift"
+crate-type = ["cdylib", "rlib"]
+
 [dependencies]
 faer = "0.24.0"
+numpy = "0.28.0"
+pyo3 = { version = "0.28.3", features = ["extension-module", "abi3-py38"] }
 rand = "0.10.0"
 rayon = "1.11.0"

README.md

@@ -10,6 +10,17 @@
   </a>
 </p>
 
-Explainable uplift modeling via linearized kernel feature maps.
+Explainable uplift modeling via linearized kernel feature maps, providing a collection of meta-learners.
 
-WIP
+# Installation
+Install using pip:
+```bash
+pip install xuplift
+```
+
+# Features
+- Regressor: High-performance regression engine for outcome and residual modeling.
+- Classifier: Optimized binary classifier for precise propensity score estimation.
+- RLearner: Advanced residual-on-residual estimator with built-in 2-fold cross-fitting to ensure unbiased treatment effect estimation.
+- XLearner: Optimized cross-learner designed to handle significantly unbalanced treatment groups.
+- TLearner/SLearner: Standard two-model and single-model estimators for baseline causal analysis.