Merge pull request #41 from HumanBrainProject/python312_and_modernize

Add tests for Python 3.12 and modernize code quality checks

.github/workflows/tox.yaml

@@ -43,9 +43,11 @@ jobs:
       run: |
         tox
 
+    # 2024-07-02: disable CodeCov (temporarily?), uploads do not work even with a token
     # Code coverage is run on Python 3.10, see tox.ini
-    - if: ${{ matrix.python-version == '3.10' }}
-      uses: codecov/codecov-action@v3
-      with:
-        fail_ci_if_error: true # optional (default = false)
-        verbose: true # optional (default = false)
+    #- if: ${{ matrix.python-version == '3.10' }}
+    #  uses: codecov/codecov-action@v4
+    #  with:
+    #    token: ${{ secrets.CODECOV_TOKEN }}
+    #    fail_ci_if_error: true # optional (default = false)
+    #    verbose: true # optional (default = false)

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
 -   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.6.0
     hooks:
     -   id: check-added-large-files
     -   id: check-case-conflict
@@ -15,11 +15,12 @@ repos:
     -   id: name-tests-test
     -   id: trailing-whitespace
 
--   repo: https://github.com/pycqa/flake8
-    rev: 6.0.0
-    hooks:
-    -   id: flake8
-        additional_dependencies: [pep8-naming]
+- repo: https://github.com/astral-sh/ruff-pre-commit
+  # Ruff version.
+  rev: v0.5.0
+  hooks:
+    # Run the linter.
+    - id: ruff
 
 -   repo: https://github.com/mgedmin/check-manifest
     rev: "0.49"

docs/conf.py

@@ -1,5 +1,4 @@
 #!/usr/bin/env python3
-# -*- coding: utf-8 -*-
 #
 # neuroglancer-scripts documentation build configuration file, created by
 # sphinx-quickstart on Fri Feb  2 15:05:24 2018.
@@ -19,11 +18,11 @@
 #
 import os
 import sys
+
 sys.path.insert(0, os.path.abspath('../src/'))
 
 import neuroglancer_scripts  # noqa: E402
 
-
 # -- General configuration ------------------------------------------------
 
 # If your documentation needs a minimal Sphinx version, state it here.

experimental/mesh_to_vtk.py

@@ -7,16 +7,15 @@
 
 import sys
 
+import neuroglancer_scripts.mesh
 import nibabel
 import numpy as np
 
-import neuroglancer_scripts.mesh
-
 
 def mesh_file_to_vtk(input_filename, output_filename, data_format="ascii",
                      coord_transform=None):
     """Convert a mesh file read by nibabel to VTK format"""
-    print("Reading {}".format(input_filename))
+    print(f"Reading {input_filename}")
     mesh = nibabel.load(input_filename)
     print()
     print("Summary")
@@ -45,7 +44,7 @@ def mesh_file_to_vtk(input_filename, output_filename, data_format="ascii",
     # Gifti uses millimetres, Neuroglancer expects nanometres
     points *= 1e6
 
-    with open(output_filename, "wt") as output_file:
+    with open(output_filename, "w") as output_file:
         neuroglancer_scripts.mesh.save_mesh_as_neuroglancer_vtk(
             output_file, points, triangles
         )
@@ -79,15 +78,15 @@ def parse_command_line(argv):
         try:
             matrix = np.fromstring(args.coord_transform, sep=",")
         except ValueError as exc:
-            parser.error("cannot parse --coord-transform: {}"
-                         .format(exc.args[0]))
+            parser.error(f"cannot parse --coord-transform: {exc.args[0]}"
+                         )
         if len(matrix) == 12:
             matrix = matrix.reshape(3, 4)
         elif len(matrix) == 16:
             matrix = matrix.reshape(4, 4)
         else:
             parser.error("--coord-transform must have 12 or 16 elements"
-                         " ({} passed)".format(len(matrix)))
+                         f" ({len(matrix)} passed)")
 
         args.coord_transform = matrix
 

experimental/off_to_vtk.py

@@ -19,7 +19,7 @@
 def off_mesh_file_to_vtk(input_filename, output_filename, data_format="binary",
                          coord_transform=None):
     """Convert a mesh file from OFF format to VTK format"""
-    print("Reading {}".format(input_filename))
+    print(f"Reading {input_filename}")
     with gzip.open(input_filename, "rt") as f:
         header_keyword = f.readline().strip()
         match = re.match(r"(ST)?(C)?(N)?(4)?(n)?OFF", header_keyword)
@@ -32,7 +32,7 @@ def off_mesh_file_to_vtk(input_filename, output_filename, data_format="binary",
         assert match
         num_vertices = int(match.group(1))
         num_triangles = int(match.group(2))
-        vertices = np.empty((num_vertices, 3), dtype=np.float)
+        vertices = np.empty((num_vertices, 3), dtype=float)
         for i in range(num_vertices):
             components = f.readline().split()
             assert len(components) >= 3
@@ -48,8 +48,8 @@ def off_mesh_file_to_vtk(input_filename, output_filename, data_format="binary",
             triangles[i, 1] = float(components[2])
             triangles[i, 2] = float(components[3])
     print()
-    print("{0} vertices and {1} triangles read"
-          .format(num_vertices, num_triangles))
+    print(f"{num_vertices} vertices and {num_triangles} triangles read"
+          )
 
     points = vertices
 
@@ -108,15 +108,15 @@ def parse_command_line(argv):
         try:
             matrix = np.fromstring(args.coord_transform, sep=",")
         except ValueError as exc:
-            parser.error("cannot parse --coord-transform: {}"
-                         .format(exc.args[0]))
+            parser.error(f"cannot parse --coord-transform: {exc.args[0]}"
+                         )
         if len(matrix) == 12:
             matrix = matrix.reshape(3, 4)
         elif len(matrix) == 16:
             matrix = matrix.reshape(4, 4)
         else:
             parser.error("--coord-transform must have 12 or 16 elements"
-                         " ({} passed)".format(len(matrix)))
+                         f" ({len(matrix)} passed)")
 
         args.coord_transform = matrix
 

experimental/stl_to_precomputed.py

@@ -5,13 +5,13 @@
 #
 # This software is made available under the MIT licence, see LICENCE.txt.
 
-# flake8: noqa
+# noqa
 
 """
 Convert a mesh from STL ASCII to Neuroglancer pre-computed mesh format
 
-Currently STL triangles are just written to the output as is, i.e. normals are not considered
-and equal vertices are not reused.
+Currently STL triangles are just written to the output as is, i.e. normals are
+not considered and equal vertices are not reused.
 """
 
 import gzip
@@ -78,10 +78,13 @@ def parse_command_line(argv):
     """Parse the script's command line."""
     import argparse
     parser = argparse.ArgumentParser(
-        description="""Convert a mesh from STL ASCII to Neuroglancer pre-computed mesh format""")
+        description="Convert a mesh from STL ASCII to Neuroglancer "
+                    "pre-computed mesh format")
     parser.add_argument("input_filename")
     parser.add_argument("output_filename")
-    parser.add_argument("--voxel-size", help="Voxel size in mm. Only isotropic voxels are supported for now. Default is 1.0",
+    parser.add_argument("--voxel-size", help="Voxel size in mm. Only "
+                        "isotropic voxels are supported for now. Default is "
+                        "1.0",
                         type=float, default=1.0)
     parser.add_argument("--no-compression", help="Don't gzip the output.",
                         action="store_false", dest="compress")
@@ -93,7 +96,8 @@ def main(argv):
     """The script's entry point."""
     args = parse_command_line(argv)
     return stl_file_to_precomputed(
-        args.input_filename, args.output_filename, args.voxel_size, args.compress) or 0
+        args.input_filename, args.output_filename, args.voxel_size,
+        args.compress) or 0
 
 
 if __name__ == "__main__":

pyproject.toml

@@ -4,3 +4,22 @@ requires = [
     "wheel",
 ]
 build-backend = "setuptools.build_meta"
+
+[tool.ruff]
+target-version = "py37"  # py36 does not exist
+line-length = 79
+indent-width = 4
+
+[tool.ruff.lint]
+extend-select = [
+    "F",
+    "E",
+    "W",
+    "I",
+    "N",
+    "NPY",
+    "UP",
+]
+ignore = [
+    "N802",  # Gives false positives when a name contains an uppercase acronym
+]

script_tests/test_scripts.py

@@ -13,12 +13,10 @@
 
 import nibabel
 import numpy as np
-import pytest
 import PIL.Image
-
+import pytest
 from neuroglancer_scripts.mesh import read_precomputed_mesh
 
-
 # Environment passed to sub-processes so that they raise an error on warnings
 env = os.environ.copy()
 env['PYTHONWARNINGS'] = 'error'
@@ -36,8 +34,8 @@ def test_jubrain_example_MPM(examples_dir, tmpdir):
     try:
         gzip.open(str(input_nifti)).read(348)
     except OSError as exc:
-        pytest.skip("Cannot find a valid example file {0} for testing: {1}"
-                    .format(input_nifti, exc))
+        pytest.skip(f"Cannot find a valid example file {input_nifti} for "
+                    f"testing: {exc}")
 
     output_dir = tmpdir / "MPM"
     assert subprocess.call([
@@ -82,8 +80,8 @@ def test_all_in_one_conversion(examples_dir, tmpdir):
     try:
         gzip.open(str(input_nifti)).read(348)
     except OSError as exc:
-        pytest.skip("Cannot find a valid example file {0} for testing: {1}"
-                    .format(input_nifti, exc))
+        pytest.skip(f"Cannot find a valid example file {input_nifti} for "
+                    f"testing: {exc}")
 
     output_dir = tmpdir / "colin27T1_seg"
     assert subprocess.call([
@@ -106,8 +104,8 @@ def test_sharded_conversion(examples_dir, tmpdir):
     try:
         gzip.open(str(input_nifti)).read(348)
     except OSError as exc:
-        pytest.skip("Cannot find a valid example file {0} for testing: {1}"
-                    .format(input_nifti, exc))
+        pytest.skip(f"Cannot find a valid example file {input_nifti} for "
+                    f"testing: {exc}")
 
     output_dir = tmpdir / "colin27T1_seg_sharded"
     assert subprocess.call([
@@ -118,7 +116,7 @@ def test_sharded_conversion(examples_dir, tmpdir):
         str(output_dir)
     ], env=env) == 4  # datatype not supported by neuroglancer
 
-    with open(output_dir / "info_fullres.json", "r") as fp:
+    with open(output_dir / "info_fullres.json") as fp:
         fullres_info = json.load(fp=fp)
     with open(output_dir / "info_fullres.json", "w") as fp:
         fullres_info["data_type"] = "uint8"

setup.cfg

@@ -19,6 +19,7 @@ classifiers =
     Programming Language :: Python :: 3.9
     Programming Language :: Python :: 3.10
     Programming Language :: Python :: 3.11
+    Programming Language :: Python :: 3.12
     Topic :: Scientific/Engineering :: Medical Science Apps.
     Topic :: Scientific/Engineering :: Visualization
 keywords = neuroimaging
@@ -30,7 +31,7 @@ packages = find:
 python_requires = ~=3.6
 install_requires =
     nibabel >= 2
-    numpy >= 1.11.0
+    numpy >= 1.17
     pillow >= 1.1.6
     requests >= 2
     scikit-image  # TODO use pillow instead
@@ -47,11 +48,11 @@ dev =
     pytest
     requests-mock
     check-manifest
-    flake8
     pep8-naming
     pre-commit
     pytest-cov
     readme_renderer
+    ruff
     sphinx
     tox
 docs =

src/neuroglancer_scripts/_compressed_segmentation.py

@@ -9,8 +9,8 @@
 
 import numpy as np
 
-from neuroglancer_scripts.utils import ceil_div
 from neuroglancer_scripts.chunk_encoding import InvalidFormatError
+from neuroglancer_scripts.utils import ceil_div
 
 
 def pad_block(block, block_size):
@@ -104,7 +104,7 @@ def _encode_channel(chunk_channel, block_size):
 
 def _pack_encoded_values(encoded_values, bits):
     if bits == 0:
-        return bytes()
+        return b""
     else:
         assert 32 % bits == 0
         assert np.array_equal(encoded_values,
@@ -162,8 +162,8 @@ def _decode_channel_into(chunk, channel, buf, block_size):
         bits = res[0] >> 24
         if bits not in (0, 1, 2, 4, 8, 16, 32):
             raise InvalidFormatError("Invalid number of encoding bits for "
-                                     "compressed_segmentation block ({0})"
-                                     .format(bits))
+                                     f"compressed_segmentation block ({bits})"
+                                     )
         encoded_values_offset = 4 * res[1]
         lookup_table_past_end = lookup_table_offset + chunk.itemsize * min(
             (2 ** bits),

src/neuroglancer_scripts/_jpeg.py

@@ -10,7 +10,6 @@
 import numpy as np
 import PIL.Image
 
-
 from neuroglancer_scripts.chunk_encoding import InvalidFormatError
 
 
@@ -47,17 +46,17 @@ def decode_chunk(buf, chunk_size, num_channels):
         img = PIL.Image.open(io_buf)
     except Exception as exc:
         raise InvalidFormatError(
-            "The JPEG-encoded chunk could not be decoded: {0}"
-            .format(exc)) from exc
+            f"The JPEG-encoded chunk could not be decoded: {exc}"
+            ) from exc
 
     if num_channels == 1 and img.mode != "L":
         raise InvalidFormatError(
-            "The JPEG chunk is encoded with mode={0} instead of L"
-            .format(img.mode))
+            f"The JPEG chunk is encoded with mode={img.mode} instead of L"
+            )
     if num_channels == 3 and img.mode != "RGB":
         raise InvalidFormatError(
-            "The JPEG chunk is encoded with mode={0} instead of RGB"
-            .format(img.mode))
+            f"The JPEG chunk is encoded with mode={img.mode} instead of RGB"
+            )
 
     flat_chunk = np.asarray(img)
     if num_channels == 3:
@@ -68,7 +67,6 @@ def decode_chunk(buf, chunk_size, num_channels):
                                    chunk_size[2], chunk_size[1], chunk_size[0])
     except Exception:
         raise InvalidFormatError("The JPEG-encoded chunk has an incompatible "
-                                 "shape ({0} elements, expecting {1})"
-                                 .format(flat_chunk.size // num_channels,
-                                         np.prod(chunk_size)))
+                                 f"shape ({flat_chunk.size // num_channels} "
+                                 f"elements, expecting {np.prod(chunk_size)})")
     return chunk