merge master into dev

.github/dependabot.yml

@@ -0,0 +1,11 @@
+# To get started with Dependabot version updates, you'll need to specify which
+# package ecosystems to update and where the package manifests are located.
+# Please see the documentation for all configuration options:
+# https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
+
+version: 2
+updates:
+  - package-ecosystem: "pip"
+    directory: "/"
+    schedule:
+      interval: "weekly"

.github/workflows/tests.yml

@@ -17,9 +17,14 @@ jobs:
   build:
     strategy:
       matrix:
-        os: [ubuntu-latest, windows-latest, macos-latest]
+        os: [ubuntu-latest, windows-latest]
         python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
         numpy-pandas-version: [">=1.0, <2.0", ">=2.0, <3.0"]
+
+        exclude:
+          - python-version: "3.8"
+            numpy-pandas-version: ">=2.0, <3.0"
+
       fail-fast: false
 
     runs-on: ${{ matrix.os }}
@@ -35,9 +40,11 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
+          python -m pip install build
+
+          make install
           make install-build-requirements
           make install-test-requirements
-          make install
 
           python -m pip install "numpy ${{ matrix.numpy-pandas-version }}"
           python -m pip install "pandas ${{ matrix.numpy-pandas-version }}"

Makefile

@@ -1,11 +1,8 @@
-install-requirements:
-	python -m pip install -r ./requirements/requirements.in
-
 install-test-requirements:
-	python -m pip install -r ./requirements/requirements-test.in
+	python -m pip install .[test]
 
 install-build-requirements:
-	python -m pip install -r ./requirements/requirements-build.in
+	python -m pip install .[build]
 
 build:
 	python -m build

pyproject.toml

@@ -7,9 +7,8 @@ where = ["src"]
 
 [project]
 name = "gradient-free-optimizers"
-version = "1.6.0"
+version = "1.6.1"
 description = "Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces."
-dynamic = ["dependencies"]
 readme = "README.md"
 requires-python = ">=3.8"
 license = {file = "LICENSE"}
@@ -37,14 +36,29 @@ classifiers=[
     "Intended Audience :: Science/Research",
 ]
 
-[tool.setuptools.dynamic]
-dependencies = {file = ["requirements/requirements.in"]}
+dependencies = [
+  "scipy <2.0.0",
+  "numpy >=1.18.1, <3.0.0",
+  "pandas <3.0.0",
+  "scikit-learn >=0.21, !=0.23.*",
+  "tqdm >=4.48.0, <5.0.0",
+]
 
 [project.optional-dependencies]
-dev = ["check-manifest"]
-test = ["coverage"]
+build = [
+  "setuptools",
+  "build",
+  "wheel",
+]
+test = [
+  "pytest == 8.3.2",
+  "flake8",
+  "pytest-cov",
+  "surfaces",
+]
 
 [project.urls]
 "Homepage" = "https://github.com/SimonBlanke/Gradient-Free-Optimizers"
 "Bug Reports" = "https://github.com/SimonBlanke/Gradient-Free-Optimizers/issues"
 "Source" = "https://github.com/SimonBlanke/Gradient-Free-Optimizers/"
+

tests/test_converter.py

@@ -551,7 +551,9 @@ def test_memory_dict2positions_scores_0(test_input, expected):
     [[-10, 10, 0.1], [10, 10, 0.2], [0, 0, 0.3]], columns=["x1", "x2", "score"]
 )
 
-dataframe1 = pd.DataFrame([[-10, 0.1], [10, 0.2], [0, 0.3]], columns=["x1", "score"])
+dataframe1 = pd.DataFrame(
+    [[-10, 0.1], [10, 0.2], [0, 0.3]], columns=["x1", "score"]
+)
 
 memory_dict_0 = {
     (0, 10): 0.1,
@@ -565,7 +567,9 @@ def test_memory_dict2positions_scores_0(test_input, expected):
 ]
 
 
-@pytest.mark.parametrize("test_input,expected", dataframe2memory_dict_test_para_0)
+@pytest.mark.parametrize(
+    "test_input,expected", dataframe2memory_dict_test_para_0
+)
 def test_dataframe2memory_dict_0(test_input, expected):
     search_space = {
         "x1": np.arange(-10, 11, 1),
@@ -599,7 +603,9 @@ def test_dataframe2memory_dict_0(test_input, expected):
 ]
 
 
-@pytest.mark.parametrize("test_input,expected", memory_dict2dataframe_test_para_0)
+@pytest.mark.parametrize(
+    "test_input,expected", memory_dict2dataframe_test_para_0
+)
 def test_memory_dict2dataframe_0(test_input, expected):
     search_space = {
         "x1": np.arange(-10, 11, 1),
@@ -619,4 +625,10 @@ def test_memory_dict2dataframe_0(test_input, expected):
 
     dataframe = dataframe[expected.columns]
 
+    dataframe[dataframe.select_dtypes(include=["number"]).columns] = (
+        dataframe.select_dtypes(include=["number"]).astype("int")
+    )
+    expected[expected.select_dtypes(include=["number"]).columns] = (
+        expected.select_dtypes(include=["number"]).astype("int")
+    )
     assert dataframe.equals(expected)