Adapt CI for multiple OS

.github/workflows/main.yml

@@ -14,24 +14,49 @@ on:
 
 
 jobs:
-  build:
+  check_install:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: True
+      matrix:
+        python-version: [3.8, 3.9, "3.10", "3.11"]
+        os: [ubuntu-latest, macos-latest, windows-latest]
+
+    steps:
+    - uses: actions/checkout@v3
+    - name: Install poetry
+      run: pipx install poetry
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v4
+      with:
+        python-version: ${{ matrix.python-version }}
+        cache: 'poetry'
+    - name: Install dependencies
+      run: |
+        python -m pip install nox_poetry
+    - name: Test install all
+      run: pip install -e .[all]
+
+  tests:
 
-    runs-on: ubuntu-latest
+    runs-on: ${{ matrix.os }}
     strategy:
-      fail-fast: false
+      fail-fast: True
       matrix:
-        python-version: [3.8, "3.10"]
+        python-version: ["3.11"]
+        os: [ubuntu-latest, macos-latest, windows-latest]
 
     steps:
     - uses: actions/checkout@v3
+    - name: Install poetry
+      run: pipx install poetry
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python-version }}
+        cache: 'poetry'
     - name: Install dependencies
       run: |
-        python -m pip install --upgrade pip
-        python -m pip install poetry
         python -m pip install nox_poetry
     - name: Test with nox
       run: nox -s tests

.github/workflows/quality.yml

@@ -21,18 +21,17 @@ jobs:
       fail-fast: false
     steps:
     - uses: actions/checkout@v3
-    - name: Set up Python
+    - name: Install poetry
+      run: pipx install poetry
+    - name: Setup python
       uses: actions/setup-python@v4
       with:
-        python-version: 3.8
+        python-version: "3.8"
+        cache: 'poetry'
     - name: Install dependencies
       run: |
-        python -m pip install --upgrade pip
-        python -m pip install poetry
         python -m pip install nox_poetry
-    - name: Lint
-      run: nox -s lint
-    - name: Type checking
-      run: nox -s type_checking
+    - name: Run all style checks
+      run: nox -t style
     - name: Build docs
       run: nox -s build_docs

kiez/hubness_reduction/mutual_proximity.py

@@ -8,11 +8,8 @@
 
 import numpy as np
 from scipy import stats
-from sklearn.utils.validation import (
-    check_array,
-    check_consistent_length,
-    check_is_fitted,
-)
+from sklearn.utils.validation import (check_array, check_consistent_length,
+                                      check_is_fitted)
 from tqdm.auto import tqdm
 
 from .base import HubnessReduction

kiez/neighbors/__init__.py

@@ -1,10 +1,12 @@
 from class_resolver import ClassResolver
+
 from kiez.neighbors.approximate.faiss import Faiss
 from kiez.neighbors.approximate.nmslib import NMSLIB
 from kiez.neighbors.approximate.nng import NNG
 from kiez.neighbors.approximate.random_projection_trees import Annoy
 from kiez.neighbors.exact.sklearn_nearest_neighbors import SklearnNN
-from kiez.neighbors.neighbor_algorithm_base import NNAlgorithm, NNAlgorithmWithJoblib
+from kiez.neighbors.neighbor_algorithm_base import (NNAlgorithm,
+                                                    NNAlgorithmWithJoblib)
 
 __all__ = [
     "nn_algorithm_resolver",

kiez/neighbors/approximate/nmslib.py

@@ -7,6 +7,7 @@
 from __future__ import annotations
 
 import numpy as np
+
 from kiez.neighbors.neighbor_algorithm_base import NNAlgorithm
 
 try:

kiez/neighbors/approximate/nng.py

@@ -9,9 +9,10 @@
 import logging
 
 import numpy as np
+from tqdm.auto import tqdm
+
 from kiez.io.temp_file_handling import create_tempfile_preferably_in_dir
 from kiez.neighbors.neighbor_algorithm_base import NNAlgorithmWithJoblib
-from tqdm.auto import tqdm
 
 try:
     import ngtpy  # noqa: autoimport

kiez/neighbors/approximate/random_projection_trees.py

@@ -11,9 +11,10 @@
 from typing import Tuple
 
 import numpy as np
+from tqdm.auto import tqdm
+
 from kiez.io.temp_file_handling import create_tempfile_preferably_in_dir
 from kiez.neighbors.neighbor_algorithm_base import NNAlgorithmWithJoblib
-from tqdm.auto import tqdm
 
 try:
     import annoy  # noqa: autoimport

kiez/neighbors/exact/sklearn_nearest_neighbors.py

@@ -1,7 +1,8 @@
 # documentation copied in parts from scikit-learn
-from kiez.neighbors.neighbor_algorithm_base import NNAlgorithm
 from sklearn.neighbors import VALID_METRICS, NearestNeighbors
 
+from kiez.neighbors.neighbor_algorithm_base import NNAlgorithm
+
 
 class SklearnNN(NNAlgorithm):
     """Wrapper for scikit learn's NearestNeighbors class

noxfile.py

@@ -1,7 +1,7 @@
 from nox_poetry import Session, session
 
 
-@session()
+@session(tags=["test"])
 def tests(session: Session) -> None:
     args = session.posargs or ["--cov=kiez/", "--cov-report=xml", "tests/"]
     session.install(".[all]")
@@ -13,8 +13,16 @@ def tests(session: Session) -> None:
 locations = ["kiez", "tests", "noxfile.py"]
 
 
-@session()
+@session(tags=["fix"])
 def lint(session: Session) -> None:
+    args = session.posargs or locations
+    session.install("black", "isort")
+    session.run("black", *args)
+    session.run("isort", *args)
+
+
+@session(tags=["style"])
+def style_checking(session: Session) -> None:
     args = session.posargs or locations
     session.install(
         "pyproject-flake8",
@@ -27,28 +35,28 @@ def lint(session: Session) -> None:
     session.run("pflake8", *args)
 
 
-@session()
+@session(tags=["style"])
 def pyroma(session: Session) -> None:
     session.install("poetry", "pyroma")
     session.run("pyroma", "--min", "10", ".")
 
 
-@session()
+@session(tags=["style", "docs"])
 def doctests(session: Session) -> None:
     session.install(".[all]")
     session.install("xdoctest")
     session.install("pygments")
     session.run("xdoctest", "-m", "kiez")
 
 
-@session()
+@session(tags=["style"])
 def type_checking(session: Session) -> None:
     args = session.posargs or locations
     session.install("mypy")
     session.run("mypy", "--ignore-missing-imports", *args)
 
 
-@session()
+@session(tags=["docs"])
 def build_docs(session: Session) -> None:
     session.install(".")
     session.install("sphinx")

pyproject.toml

@@ -61,7 +61,7 @@ mypy = "^0.960"
 
 [tool.poetry.extras]
 docs = ["sphinx", "insegel"]
-all = ["ngt","annoy","nmslib","faiss-cpu","faiss-gpu","autofaiss"]
+all = ["annoy","nmslib","faiss-cpu","faiss-gpu","autofaiss"]
 ngt = ["ngt"]
 nmslib = ["nmslib"]
 annoy = ["annoy"]

tests/analysis/test_estimation.py

@@ -6,9 +6,10 @@
 
 import numpy as np
 import pytest
+from numpy.testing import assert_array_equal
+
 from kiez.analysis import hubness_score
 from kiez.analysis.estimation import _calc_atkinson_index, _calc_gini_index
-from numpy.testing import assert_array_equal
 
 PRE_CALC_NEIGHBORS = np.load("tests/nn_ind.npy")
 
@@ -108,9 +109,9 @@ def test_hubness_return_values_are_self_consistent(k):
     np.testing.assert_array_equal(occ, occ_true)
     # Calculate skewness (different method than in module)
     x0 = occ - occ.mean()
-    s2 = (x0 ** 2).mean()
-    m3 = (x0 ** 3).mean()
-    skew_true = m3 / (s2 ** 1.5)
+    s2 = (x0**2).mean()
+    m3 = (x0**3).mean()
+    skew_true = m3 / (s2**1.5)
     np.testing.assert_equal(skew, skew_true)
 
 

tests/evaluate/test_eval_metrics.py

@@ -1,4 +1,5 @@
 import pytest
+
 from kiez.evaluate import hits
 
 

tests/hubness_reduction/test_mutual_proximity.py

@@ -1,8 +1,9 @@
 import numpy as np
 import pytest
+from numpy.testing import assert_array_equal
+
 from kiez import Kiez
 from kiez.hubness_reduction import MutualProximity
-from numpy.testing import assert_array_equal
 
 rng = np.random.RandomState(2)
 

tests/io/test_data_loading.py

@@ -1,8 +1,9 @@
 import numpy as np
 import pytest
-from kiez.io.data_loading import _seperate_common_embedding
 from numpy.testing import assert_array_equal
 
+from kiez.io.data_loading import _seperate_common_embedding
+
 
 @pytest.mark.parametrize(
     "input,expected",

tests/io/test_temp_file_handling.py

@@ -1,6 +1,7 @@
 import os
 
 import pytest
+
 from kiez.io.temp_file_handling import create_tempfile_preferably_in_dir
 
 

tests/neighbors/test_alignment.py

@@ -1,10 +1,12 @@
 import numpy as np
 import pytest
+from numpy.testing import assert_array_almost_equal, assert_array_equal
+
 from kiez import Kiez
-from kiez.hubness_reduction import CSLS, DisSimLocal, LocalScaling, MutualProximity
+from kiez.hubness_reduction import (CSLS, DisSimLocal, LocalScaling,
+                                    MutualProximity)
 from kiez.neighbors import NMSLIB, NNG, Annoy, Faiss, SklearnNN
 from kiez.utils.platform import available_ann_algorithms_on_current_platform
-from numpy.testing import assert_array_almost_equal, assert_array_equal
 
 P = (1, 3, 4, np.inf, 2)  # Euclidean last, for tests against approx NN
 rng = np.random.RandomState(2)

tests/neighbors/test_annoy.py

@@ -1,8 +1,9 @@
 import numpy as np
 import pytest
-from kiez.neighbors import Annoy
 from numpy.testing import assert_array_equal
 
+from kiez.neighbors import Annoy
+
 rng = np.random.RandomState(2)
 
 

tests/neighbors/test_base.py

@@ -1,5 +1,6 @@
 import numpy as np
 import pytest
+
 from kiez.neighbors import NMSLIB, NNG, Annoy, Faiss, SklearnNN
 
 rng = np.random.RandomState(2)

tests/neighbors/test_faiss.py

@@ -1,8 +1,9 @@
 import numpy as np
 import pytest
-from kiez.neighbors import Faiss
 from numpy.testing import assert_array_equal
 
+from kiez.neighbors import Faiss
+
 
 @pytest.mark.parametrize("single_source", [True, False])
 def test_different_instantiations(single_source):

tests/neighbors/test_hnsw.py

@@ -1,8 +1,9 @@
 import numpy as np
 import pytest
-from kiez.neighbors import NMSLIB
 from numpy.testing import assert_array_equal
 
+from kiez.neighbors import NMSLIB
+
 rng = np.random.RandomState(2)
 
 

tests/neighbors/test_nng.py

@@ -1,8 +1,9 @@
 import numpy as np
 import pytest
-from kiez.neighbors import NNG
 from numpy.testing import assert_array_equal
 
+from kiez.neighbors import NNG
+
 rng = np.random.RandomState(2)
 
 

tests/neighbors/test_sklearn.py

@@ -1,7 +1,8 @@
 import numpy as np
-from kiez.neighbors import SklearnNN
 from numpy.testing import assert_array_equal
 
+from kiez.neighbors import SklearnNN
+
 rng = np.random.RandomState(2)
 
 

tests/test_kiez.py

@@ -3,17 +3,14 @@
 
 import numpy as np
 import pytest
-from kiez import Kiez
-from kiez.hubness_reduction import (
-    DisSimLocal,
-    HubnessReduction,
-    LocalScaling,
-    NoHubnessReduction,
-)
-from kiez.neighbors import NMSLIB, NNAlgorithm, SklearnNN
 from numpy.testing import assert_array_equal
 from sklearn.neighbors import NearestNeighbors
 
+from kiez import Kiez
+from kiez.hubness_reduction import (DisSimLocal, HubnessReduction,
+                                    LocalScaling, NoHubnessReduction)
+from kiez.neighbors import NMSLIB, NNAlgorithm, SklearnNN
+
 HERE = pathlib.Path(__file__).parent.resolve()
 rng = np.random.RandomState(2)