GEOPY-2741: Continue update to Python 3.12

.github/workflows/python_analysis.yml

@@ -26,26 +26,26 @@
 jobs:
   call-workflow-static-analysis:
     name: Static analysis
     uses: MiraGeoscience/CI-tools/.github/workflows/reusable-python-static_analysis.yml@v2
     permissions:
       contents: read
       pull-requests: read
     with:
       package-manager: 'poetry'
       app-name: 'omf'
-      python-version: '3.10'
+      python-version: '3.12'
   call-workflow-pytest:
     name: Pytest
     uses: MiraGeoscience/CI-tools/.github/workflows/reusable-python-pytest.yml@v2
     permissions:
       contents: read
       pull-requests: read
     with:
       package-manager: 'poetry'
-      python-versions: '["3.10", "3.11", "3.12"]'
+      python-versions: '["3.12", "3.13", "3.14"]'
       os: '["ubuntu-latest", "windows-latest"]'
       cache-number: 1
-      codecov-reference-python-version: '3.10'
+      codecov-reference-python-version: '3.12'
       codecov-reference-os: '["windows-latest"]'
     secrets:
       CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}

.github/workflows/python_deploy_dev.yml

@@ -14,12 +14,12 @@
 jobs:
   call-workflow-conda-publish:
     name: Publish development conda package on JFrog Artifactory
     uses: MiraGeoscience/CI-tools/.github/workflows/reusable-python-publish_rattler_package.yml@v2
     permissions:
       contents: write
     with:
       package-name: 'mira-omf'
-      python-version: '3.10'
+      python-version: '3.12'
       source-repo-names: '["public-noremote-conda-dev"]'
       conda-channels: '["conda-forge"]'
       publish-repo-names: '["public-noremote-conda-dev"]'
@@ -28,14 +28,14 @@
       JFROG_ARTIFACTORY_TOKEN: ${{ secrets.JFROG_ARTIFACTORY_TOKEN }}
   call-workflow-pypi-publish:
     name: Publish development pypi package (JFrog Artifactory, TestPyPI)
     uses: MiraGeoscience/CI-tools/.github/workflows/reusable-python-publish_pypi_package.yml@v2
     permissions:
       contents: write
     with:
       package-manager: 'poetry'
       package-name: 'mira-omf'
       version-tag: ${{ github.ref_name }}
-      python-version: '3.10'
+      python-version: '3.12'
       virtual-repo-names: '["public-pypi-dev", "test-pypi"]'
     secrets:
       JFROG_ARTIFACTORY_URL: ${{ secrets.JFROG_ARTIFACTORY_URL }}

.pre-commit-config.yaml

@@ -35,7 +35,7 @@ repos:
     hooks:
     -   id: mypy
         additional_dependencies: [
-#            numpy==1.26.*,  # TODO: fix mypy errors related to numpy
+            numpy==2.4.*,  # TODO: fix mypy errors related to numpy
             tomli, # to read config from pyproject.toml
             types-six,
             types-toml,

pyproject.toml

@@ -13,7 +13,7 @@ build-backend = "poetry_dynamic_versioning.backend"
 
 [project]
 name = "mira-omf"
-requires-python = ">=3.10,<4.0"
+requires-python = ">=3.12,<3.15"
 description = "API Library for Open Mining Format"
 license = "MIT"
 license-files = [
@@ -64,11 +64,12 @@ include = [
 version = "0.0.0.dev0"
 
 [tool.poetry.dependencies]
-numpy = "~1.26.0"  # also in geoh5py
+numpy = "~2.4.0"  # also in geoh5py
 properties = "0.6.*"
 pypng = "^0.20220715"
 six = "^1.16"
 vectormath = "0.2.*"
+standard-imghdr = "3.13.*"
 
 ## dependencies from Git repositories
 #------------------------------------
@@ -81,7 +82,7 @@ Pygments = "*"
 pylint = "*"
 pytest = "*"
 pytest-cov = "*"
-sphinx = "^5.3"
+sphinx = "*"
 pyyaml = '*'
 packaging = '*'
 
@@ -114,7 +115,7 @@ initial-content = """
 persistent-substitution = true
 
 [tool.ruff]
-target-version = "py310"
+target-version = "py312"
 
 exclude = [
     "docs/*",
@@ -174,9 +175,7 @@ show_error_context = true
 show_column_numbers = true
 check_untyped_defs = true
 
-plugins = [
-#    "numpy.typing.mypy_plugin"
-]
+plugins = []
 
 [tool.pytest.ini_options]
 

recipe.yaml

@@ -3,7 +3,7 @@ schema_version: 1
 context:
   name: "mira-omf"
   version: "0.0.0.dev0"  # This will be replaced by the actual version in the build process
-  python_min: "3.10"
+  python_min: "3.12"
   module_name: omf
 
 package:
@@ -25,20 +25,21 @@ build:
 requirements:
   host:
     - pip
-    - python 3.10.*
+    - python ${{ python_min }}.*
     - poetry-core >=1.8.0
     - poetry-dynamic-versioning >=1.9, 1.*
     - setuptools
   run:
     - python >=${{ python_min }}
     # Mira packages
-    - geoh5py >=0.12.0b5, 0.12.*
+    - geoh5py >=0.13.0a2, 0.13.*
     # direct dependencies
-    - numpy 1.26.*
+    - numpy 2.4.*
     - properties 0.6.*
     - pypng 0.20220715.*
     - six >=1.16.0, 1.*
     - vectormath 0.2.*
+    - standard-imghdr 3.13.0
 
 tests:
   - python:

tests/conftest.py

@@ -116,7 +116,7 @@ def random_project() -> omf.Project:
             ),
             omf.ScalarData(
                 name="rand face data",
-                array=np.random.rand(10, 15).flatten(order="f"),
+                array=np.random.rand(10, 15).flatten(order="F"),
                 location="faces",
             ),
         ],

tests/convert_grid2d_test.py

@@ -21,10 +21,10 @@
 
 def test_grid2d_to_geoh5(tmp_path: Path, caplog):
     """Test pointset geometry validation"""
+    dip = np.random.uniform(low=0.0, high=np.pi / 2, size=1)[0]
+    rotation = np.random.uniform(low=-np.pi, high=np.pi, size=1)[0]
 
-    dip = np.random.uniform(low=0.0, high=90, size=1)
-    rotation = np.random.uniform(low=-180, high=180, size=1)
-    rot_op = omf.fileio.geoh5.rotation_opt(np.deg2rad(rotation), np.deg2rad(dip))
+    rot_op = omf.fileio.geoh5.rotation_opt(rotation, dip)
     grid = omf.SurfaceElement(
         name="gridsurf",
         geometry=omf.SurfaceGridGeometry(
@@ -43,7 +43,7 @@ def test_grid2d_to_geoh5(tmp_path: Path, caplog):
             ),
             omf.ScalarData(
                 name="rand face data",
-                array=np.random.rand(10, 15).flatten(order="f"),
+                array=np.random.rand(10, 15).flatten(order="F"),
                 location="faces",
             ),
         ],
@@ -57,8 +57,8 @@ def test_grid2d_to_geoh5(tmp_path: Path, caplog):
     with Workspace(file) as workspace:
         grid2d = workspace.get_entity("gridsurf")[0]
 
-        np.testing.assert_array_almost_equal(grid2d.dip, dip)
-        np.testing.assert_array_almost_equal(grid2d.rotation, rotation)
+        np.testing.assert_array_almost_equal(np.deg2rad(grid2d.dip), dip)
+        np.testing.assert_array_almost_equal(np.deg2rad(grid2d.rotation), rotation)
 
         data = grid2d.get_entity("rand vert data")[0]
         np.testing.assert_array_almost_equal(np.r_[grid.data[0].array], data.values)

tests/convert_volume_test.py

@@ -27,6 +27,7 @@
 def test_volume_to_geoh5(tmp_path: Path):
     """Test pointset geometry validation"""
     dims = [10, 15, 20]
+    size = int(np.prod(dims))
     vol = omf.VolumeElement(
         name="vol",
         geometry=omf.VolumeGridGeometry(
@@ -39,19 +40,17 @@ def test_volume_to_geoh5(tmp_path: Path):
             omf.ScalarData(
                 name="Random Int Data",
                 location="cells",
-                array=np.arange(np.prod(dims)).flatten().astype(np.int32),
+                array=np.arange(size).flatten().astype(np.int32),
             ),
             omf.ScalarData(
                 name="Random Float Data",
                 location="cells",
-                array=np.random.randn(np.prod(dims)),
+                array=np.random.randn(size),
             ),
             omf.MappedData(
                 name="Reference Data",
                 location="cells",
-                array=np.random.randint(-1, 3, np.prod(dims))
-                .flatten()
-                .astype(np.int32),
+                array=np.random.randint(-1, 3, size).flatten().astype(np.int32),
                 legends=[
                     omf.Legend(values=omf.StringArray(array=["abc", "123", "@#$%"])),
                     omf.Legend(
@@ -68,9 +67,7 @@ def test_volume_to_geoh5(tmp_path: Path):
             omf.MappedData(
                 name="Reference Data 2",
                 location="cells",
-                array=np.random.randint(-1, 3, np.prod(dims))
-                .flatten()
-                .astype(np.int32),
+                array=np.random.randint(-1, 3, size).flatten().astype(np.int32),
                 legends=[
                     omf.Legend(
                         values=omf.ColorArray(