Update CI

.github/workflows/ci.yml

@@ -1,26 +1,43 @@
 name: Continuous Integration Workflow
 
 on:
-    pull_request:
-        branches:
-            - master
-            - dev
-    push:
-        branches:
-            - master
-            - dev
     workflow_dispatch:
+    push:
+      branches:
+          - master
+          - dev
+    pull_request:
+      branches:
+          - master
+          - dev
 
 jobs:
-    build:
-        runs-on: ubuntu-latest
-        steps:
-            - uses: actions/checkout@v3
-            - name: install
-              run: make install
-            - name: test
-              run: make test
-            - name: format
-              run: make format
-            - name: lint
-              run: make lint
+  main:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Repository
+        uses: actions/checkout@v4
+
+      - name: Install Poetry
+        run: |
+          pipx install poetry
+          poetry config virtualenvs.in-project true
+
+      - name: Set Up Python
+        uses: actions/setup-python@v5
+        with:
+          cache: poetry
+          cache-dependency-path: poetry.lock
+
+      - name: Install Dependencies
+        run: poetry install --no-root --no-interaction
+
+      - name: Lint
+        run: poetry run ruff check bias_scan
+
+      - name: Test
+        run: poetry run pytest
+          --color=yes
+          --full-trace
+          --showlocals
+          --verbose

pyproject.toml

@@ -0,0 +1,22 @@
+[tool.poetry]
+name = "bias-scan"
+version = "0.1.0"
+description = ""
+authors = []
+license = "MIT"
+readme = "README.md"
+
+[tool.poetry.dependencies]
+python = "^3.11"
+numpy = "^1.26.4"
+scikit-learn = "^1.4.1.post1"
+kmodes = "^0.12.2"
+
+[tool.poetry.dev-dependencies]
+ruff = "^0.2.2"
+pytest = "^8.0.2"
+
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"

tests/test_bahc.py

@@ -0,0 +1,13 @@
+import numpy as np
+
+from bias_scan.clustering import BiasAwareHierarchicalKMeans
+
+
+def test_clusters():
+    # Checks that label values are between 0 and n_clusters
+    rng = np.random.RandomState(12)
+    X = rng.rand(10, 5)
+    y = rng.rand(10)
+    algo = BiasAwareHierarchicalKMeans(max_iter=3, min_cluster_size=2)
+    algo.fit(X, y)
+    assert np.array_equal(np.unique(algo.labels_), np.arange(algo.n_clusters_))