Run linter -- add hooks

Author: johmedr

.github/workflows/publish-to-pypi.yml

@@ -3,26 +3,26 @@ name: Publish Package to PyPI and TestPyPI
 on:
   workflow_dispatch:
   push:
-    paths: 
+    paths:
       - pyproject.toml
 
-jobs: 
+jobs:
   create-tag:
     name: Create tag from new version
     runs-on: "ubuntu-latest"
     permissions:
-      contents: write  
-      id-token: write 
-    outputs: 
-      MPYTHON_VERSION: ${{ steps.getversion.outputs.MPYTHON_VERSION }} 
-    steps: 
+      contents: write
+      id-token: write
+    outputs:
+      MPYTHON_VERSION: ${{ steps.getversion.outputs.MPYTHON_VERSION }}
+    steps:
       - name: Check out package
         uses: actions/checkout@v4
       - name: Get package version
         id: getversion
         run: |
            VERSION=$(sed -n 's/^version = "\(.*\)"/\1/p' pyproject.toml)
-           echo "pyproject.toml version: $VERSION" 
+           echo "pyproject.toml version: $VERSION"
            git config user.name github-actions
            git config user.email [email protected]
            MSG=$(git log $(git describe --tags --abbrev=0)..HEAD --oneline)
@@ -31,12 +31,12 @@ jobs:
            git tag -a "$VERSION" -m "$MSG"
            echo "MPYTHON_VERSION=$VERSION" >> "$GITHUB_OUTPUT"
       - name: Publish tags
-        run: git push --tags 
+        run: git push --tags
 
   build:
     name: Build Package
     runs-on: ubuntu-latest
-    needs: 
+    needs:
     - create-tag
     steps:
     - uses: actions/checkout@v4
@@ -59,7 +59,7 @@ jobs:
       with:
         name: python-package-distributions
         path: dist/
-       
+
   publish-to-pypi:
     name: >-
       Publish Package to PyPI
@@ -109,7 +109,7 @@ jobs:
     - name: Create GitHub Release
       env:
         GITHUB_TOKEN: ${{ github.token }}
-      run: | 
+      run: |
         gh release create ${{ needs.create-tag.outputs.MPYTHON_VERSION }} --repo "$GITHUB_REPOSITORY" --notes ""
     - name: Upload artifact signatures to GitHub Release
       env:

README.md

@@ -102,4 +102,3 @@ This project is licensed under the [GNU General Public License v2 (GPLv2)](LICEN
 ## Links
 
 - [Repository](https://github.com/MPython-Package-Factory/mpython-core)
-

mpython/__init__.py

@@ -1,19 +1,19 @@
-from .runtime import Runtime
+from .array import Array
+from .cell import Cell
 from .matlab_class import MatlabClass
 from .matlab_function import MatlabFunction
-from .cell import Cell
-from .struct import Struct
-from .array import Array
+from .runtime import Runtime
 from .sparse_array import SparseArray
+from .struct import Struct
 
 __all__ = [
-    'Runtime',
-    'MatlabClass',
-    'MatlabFunction',
-    'Cell',
-    'Struct',
-    'Array',
-    'SparseArray'
+    "Runtime",
+    "MatlabClass",
+    "MatlabFunction",
+    "Cell",
+    "Struct",
+    "Array",
+    "SparseArray",
 ]
 
 # ----------------------------------------------------------------------
@@ -69,4 +69,4 @@
 
 # * We should probably implement a helper to convert matlab batches into
 #   python batches.
-# """
+# """

mpython/array.py

@@ -1,11 +1,8 @@
-from .core import (
-    WrappedArray, 
-    _ListishMixin
-)
-from .utils import _copy_if_needed
-
 import numpy as np
 
+from .core import WrappedArray, _ListishMixin
+from .utils import _copy_if_needed
+
 
 class Array(_ListishMixin, WrappedArray):
     """
@@ -31,6 +28,7 @@ class Array(_ListishMixin, WrappedArray):
         `Array` constructor. To ensure that they are interpreted as
         arrays to copy, use `Array.from_any`.
     """
+
     @classmethod
     def _DEFAULT(cls, n: list = ()) -> int:
         return 0
@@ -178,16 +176,19 @@ def from_cell(cls, other, **kwargs) -> "Array":
         array : Array
             Converted array.
         """
-        from .cell import Cell # FIXME: avoid circular import
+        from .cell import Cell  # FIXME: avoid circular import
 
         if not isinstance(other, Cell):
             raise TypeError(f"Expected a {Cell} but got a {type(other)}")
         order = kwargs.get("order", None)
         if order in (None, "K", "A"):
             order = (
-                "F" if other.flags.f_contiguous else
-                "C" if other.flags.c_contiguous else
-                order)
+                "F"
+                if other.flags.f_contiguous
+                else "C"
+                if other.flags.c_contiguous
+                else order
+            )
             kwargs["order"] = order
         return cls.from_any(other.tolist(), **kwargs)
 
@@ -200,4 +201,4 @@ def __repr__(self):
             # Scalar -> display as python scalar
             return np.array2string(self, separator=", ")
         else:
-            return super().__repr__()
+            return super().__repr__()

mpython/cell.py

@@ -1,20 +1,10 @@
-from .core import (
-    MatlabType,
-    WrappedArray,
-    DelayedCell,
-    AnyDelayedArray,
-    _ListMixin,
-)
-from .utils import (
-    _empty_array, 
-    _copy_if_needed, 
-    _import_matlab, 
-    _matlab_array_types
-)
-global matlab
-
 import numpy as np
 
+from .core import AnyDelayedArray, DelayedCell, MatlabType, WrappedArray, _ListMixin
+from .utils import _copy_if_needed, _empty_array, _import_matlab, _matlab_array_types
+
+global matlab
+
 
 class Cell(_ListMixin, WrappedArray):
     """
@@ -77,8 +67,7 @@ class Cell(_ListMixin, WrappedArray):
     def _DEFAULT(cls, shape: list = ()) -> np.ndarray:
         data = np.empty(shape, dtype=object)
         opt = dict(
-            flags=['refs_ok', 'zerosize_ok'],
-            op_flags=['writeonly', 'no_broadcast']
+            flags=["refs_ok", "zerosize_ok"], op_flags=["writeonly", "no_broadcast"]
         )
         with np.nditer(data, **opt) as iter:
             for elem in iter:
@@ -87,8 +76,9 @@ def _DEFAULT(cls, shape: list = ()) -> np.ndarray:
 
     def _fill_default(self):
         arr = np.ndarray.view(self, np.ndarray)
-        opt = dict(flags=['refs_ok', 'zerosize_ok'],
-                   op_flags=['writeonly', 'no_broadcast'])
+        opt = dict(
+            flags=["refs_ok", "zerosize_ok"], op_flags=["writeonly", "no_broadcast"]
+        )
         with np.nditer(arr, **opt) as iter:
             for elem in iter:
                 elem[()] = _empty_array()
@@ -113,37 +103,36 @@ def _as_runtime(self) -> dict:
             data = np.ndarray.view(self, np.ndarray)
             data = np.reshape(data, [-1], order="F").tolist()
             data = MatlabType._to_runtime(data)
-            return dict(type__='cell', size__=size, data__=data)
+            return dict(type__="cell", size__=size, data__=data)
 
     @classmethod
     def _from_runtime(cls, objdict: dict) -> "Cell":
         if isinstance(objdict, (list, tuple, set)):
             shape = [len(objdict)]
-            objdict = dict(type__='cell', size__=shape, data__=objdict)
+            objdict = dict(type__="cell", size__=shape, data__=objdict)
 
-        if objdict['type__'] != 'cell':
-            raise TypeError('objdict is not a cell')
+        if objdict["type__"] != "cell":
+            raise TypeError("objdict is not a cell")
 
-        size = np.array(objdict['size__'], dtype=np.uint64).ravel()
+        size = np.array(objdict["size__"], dtype=np.uint64).ravel()
         if len(size) == 2 and size[0] == 1:
             # NOTE: should not be needed for Cell, as this should
             # have been taken care of by MPython, but I am keeping it
             # here for symmetry with Array and Struct.
             size = size[1:]
-        data = np.fromiter(objdict['data__'], dtype=object)
+        data = np.fromiter(objdict["data__"], dtype=object)
         data = data.reshape(size[::-1]).transpose()
         try:
             obj = data.view(cls)
         except Exception:
             raise RuntimeError(
-                f'Failed to construct Cell data:\n'
-                f'  data={data}\n'
-                f'  objdict={objdict}'
+                f"Failed to construct Cell data:\n  data={data}\n  objdict={objdict}"
             )
 
         # recurse
-        opt = dict(flags=['refs_ok', 'zerosize_ok'],
-                   op_flags=['readwrite', 'no_broadcast'])
+        opt = dict(
+            flags=["refs_ok", "zerosize_ok"], op_flags=["readwrite", "no_broadcast"]
+        )
         with np.nditer(data, **opt) as iter:
             for elem in iter:
                 elem[()] = MatlabType._from_runtime(elem.item())
@@ -276,8 +265,9 @@ def asrecursive(other):
             other[...] = tmp
 
         # recurse
-        opt = dict(flags=['refs_ok', 'zerosize_ok'],
-                   op_flags=['readwrite', 'no_broadcast'])
+        opt = dict(
+            flags=["refs_ok", "zerosize_ok"], op_flags=["readwrite", "no_broadcast"]
+        )
         with np.nditer(other, **opt) as iter:
             for elem in iter:
                 elem[()] = MatlabType.from_any(elem.item())
@@ -295,8 +285,9 @@ def _unroll_build(cls, arr):
         # them to lists, and recurse.
         rebuild = False
         arr = np.asarray(arr)
-        opt = dict(flags=['refs_ok', 'zerosize_ok'],
-                   op_flags=['readwrite', 'no_broadcast'])
+        opt = dict(
+            flags=["refs_ok", "zerosize_ok"], op_flags=["readwrite", "no_broadcast"]
+        )
         with np.nditer(arr, **opt) as iter:
             for elem in iter:
                 item = elem.item()

mpython/core/__init__.py

@@ -1,21 +1,26 @@
-from .base_types import (
-    MatlabType,
-    AnyMatlabArray
-)
-from .wrapped_types import (
-    AnyWrappedArray,
-    WrappedArray
-)
-from .mixin_types import (
-    _ListishMixin,
-    _ListMixin, 
-    _DictMixin, 
-    _SparseMixin, 
-)
+from .base_types import AnyMatlabArray, MatlabType
 from .delayed_types import (
-    AnyDelayedArray, 
+    AnyDelayedArray,
     DelayedArray,
-    DelayedCell, 
+    DelayedCell,
     DelayedStruct,
-    WrappedDelayedArray
-) 
+    WrappedDelayedArray,
+)
+from .mixin_types import _DictMixin, _ListishMixin, _ListMixin, _SparseMixin
+from .wrapped_types import AnyWrappedArray, WrappedArray
+
+__all__ = [
+    "AnyMatlabArray",
+    "AnyDelayedArray",
+    "AnyWrappedArray",
+    "MatlabType",
+    "WrappedArray",
+    "DelayedArray",
+    "DelayedCell",
+    "DelayedStruct",
+    "_ListishMixin",
+    "_ListMixin",
+    "_DictMixin",
+    "_SparseMixin",
+    "WrappedDelayedArray",
+]