Drop Python 3.8, 3.9 and add Python 3.12

.github/workflows/build_upload_pypi_wheels.yml

@@ -10,7 +10,7 @@ jobs:
     strategy:
       matrix:
         os: [windows-latest, macos-13, ubuntu-latest]
-        python-version: ['3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.10', '3.11']
         include:
           - os: windows-latest
             wheelname: win
@@ -19,16 +19,10 @@ jobs:
           - os: ubuntu-latest
             wheelname: manylinux
           # Build wheels against the lowest compatible Numpy version
-          - python-version: 3.8
-            manylinux-version-tag: cp38
-            numpy-version: 1.19.5
-          - python-version: 3.9
-            manylinux-version-tag: cp39
-            numpy-version: 1.19.5
-          - python-version: 3.10
+          - python-version: '3.10'
             manylinux-version-tag: cp310
             numpy-version: 1.21.3
-          - python-version: 3.11
+          - python-version: '3.11'
             manylinux-version-tag: cp311
             numpy-version: 1.23.2
       fail-fast: false

.github/workflows/create-landing-page.yml

@@ -17,7 +17,7 @@ jobs:
           ref: gh-pages
       - uses: actions/setup-python@v4
         with:
-          python-version: 3.8
+          python-version: '3.10'
       - name: Update pip and install dependencies
         run: |
           python -m pip install --upgrade pip

.github/workflows/run_tests.yml

@@ -24,7 +24,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: conda-incubator/setup-miniconda@v3
         with:
-          python-version: 3.8
+          python-version: '3.10'
           channels: conda-forge,defaults
           channel-priority: true
       - name: Install llvm on Macos
@@ -36,10 +36,10 @@ jobs:
         run: |
           python -m pip install --upgrade pip
           python -m pip install -r tests_and_analysis/ci_requirements.txt
-      - name: Run tests, skip Python 3.9, 3.10 unless workflow dispatch
+      - name: Run tests, skip Python 3.11 unless workflow dispatch
         if: github.event_name != 'workflow_dispatch'
         env:
-          TOX_SKIP_ENV: '.*?(py39|py310).*?'
+          TOX_SKIP_ENV: '.*?(py311).*?'
         shell: bash -l {0}
         run: python -m tox
       - name: Run tests, workflow dispatch so test all Python versions
@@ -70,7 +70,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: conda-incubator/setup-miniconda@v3
         with:
-          python-version: 3.8
+          python-version: '3.10'
           channels: conda-forge,defaults
           channel-priority: true
       - name: Update pip and install dependencies

.github/workflows/test_release.yml

@@ -10,14 +10,14 @@ jobs:
   test:
     strategy:
       matrix:
-        os: [ubuntu-latest, windows-latest, macos-latest]
+        os: [ubuntu-latest, windows-latest, macos-latest, macos-13]
       fail-fast: false
     runs-on: ${{ matrix.os }}
     steps:
       - uses: actions/checkout@v3
       - uses: conda-incubator/setup-miniconda@v2
         with:
-          python-version: 3.8
+          python-version: '3.10'
           channels: conda-forge,defaults
           channel-priority: true
       - name: Install llvm on Macos

.readthedocs.yml

@@ -13,7 +13,7 @@ sphinx:
 build:
   os: ubuntu-22.04
   tools:
-    python: "3.8"
+    python: "3.10"
 
 # Optionally set the version of Python and requirements required to build your docs
 python:

doc/requirements.txt

@@ -1,4 +1,4 @@
-numpy>=1.14.5
+numpy>=1.21.3
 sphinx==5.3.0
 sphinx-argparse==0.3.2
 sphinx-autodoc-typehints==1.19.5

doc/source/cite.rst

@@ -12,7 +12,7 @@ or it can be read programatically as follows:
 
   import yaml
   import euphonic
-  from importlib_resources import files
+  from importlib.resources import files
 
   with open(files(euphonic) / 'CITATION.cff') as fp:
       citation_data = yaml.safe_load(fp)

doc/source/installation.rst

@@ -5,7 +5,7 @@ Installation
 
 .. contents:: :local:
 
-Euphonic has been tested on Python 3.8 - 3.10.
+Euphonic has been tested on Python 3.10 - 3.12.
 
 Pip
 ===
@@ -47,7 +47,7 @@ To create a "complete" installation in a new environment:
 
 .. code-block:: bash
 
-  conda create -n euphonic-forge -c conda-forge python=3.8 euphonic matplotlib-base pyyaml tqdm h5py
+  conda create -n euphonic-forge -c conda-forge python=3.10 euphonic matplotlib-base pyyaml tqdm h5py
 
 This creates an environment named "euphonic-forge", which can be
 entered with ``activate euphonic-forge`` and exited with

euphonic/__init__.py

@@ -1,9 +1,10 @@
+from importlib.resources import files
+
 from . import _version
 __version__ = _version.get_versions()['version']
 
 import pint
 from pint import UnitRegistry
-from importlib_resources import files
 
 # Create ureg here so it is only created once
 ureg = UnitRegistry()

euphonic/readers/castep.py

@@ -111,7 +111,7 @@ def read_phonon_dos_data(
     _, idx = np.unique(atom_type, return_index=True)
     unique_types = atom_type[np.sort(idx)]
     for i, species in enumerate(unique_types):
-        dos_dict[species] = dos_data[:, i + 2]/dos_conv
+        dos_dict[str(species)] = dos_data[:, i + 2]/dos_conv
 
     return data_dict
 

euphonic/styles/__init__.py

@@ -1,5 +1,5 @@
 """Matplotlib stylesheets for plot styling"""
-from importlib_resources import files
+from importlib.resources import files
 
 base_style = files(__package__) / "base.mplstyle"
 intensity_widget_style = files(__package__) / "intensity_widget.mplstyle"

euphonic/util.py

@@ -1,17 +1,16 @@
-from collections import OrderedDict
 from functools import reduce
+from importlib.resources import files
 import itertools
 import json
 import math
 import os.path
 import sys
-from typing import Dict, Sequence, Union, Tuple, Optional, List
+from typing import Sequence, Optional
 import warnings
 
 import numpy as np
 import seekpath
 from seekpath.hpkot import SymmetryDetectionError
-from importlib_resources import files
 from pint import UndefinedUnitError
 
 from euphonic import ureg, Quantity
@@ -52,7 +51,7 @@ def direction_changed(qpts: np.ndarray, tolerance: float = 5e-6
     return np.abs(np.abs(dot) - modq[1:]*modq[:-1]) > tolerance
 
 
-def is_gamma(qpt: np.ndarray) -> Union[bool, np.ndarray]:
+def is_gamma(qpt: np.ndarray) -> bool | np.ndarray:
     """
     Determines whether the given point(s) are gamma points
 
@@ -73,7 +72,7 @@ def is_gamma(qpt: np.ndarray) -> Union[bool, np.ndarray]:
     return isgamma
 
 
-def mp_grid(grid: Tuple[int, int, int]) -> np.ndarray:
+def mp_grid(grid: tuple[int, int, int]) -> np.ndarray:
     """
     Returns the q-points on a MxNxL Monkhorst-Pack grid specified by
     grid
@@ -101,8 +100,8 @@ def mp_grid(grid: Tuple[int, int, int]) -> np.ndarray:
     return np.column_stack((qh, qk, ql))
 
 
-def get_all_origins(max_xyz: Tuple[int, int, int],
-                    min_xyz: Tuple[int, int, int] = (0, 0, 0),
+def get_all_origins(max_xyz: tuple[int, int, int],
+                    min_xyz: tuple[int, int, int] = (0, 0, 0),
                     step: int = 1) -> np.ndarray:
     """
     Given the max/min number of cells in each direction, get a list of
@@ -133,10 +132,10 @@ def get_all_origins(max_xyz: Tuple[int, int, int],
 
 
 def get_qpoint_labels(qpts: np.ndarray,
-                      cell: Optional[Tuple[List[List[float]],
-                                           List[List[float]],
-                                           List[int]]] = None
-                      ) -> List[Tuple[int, str]]:
+                      cell: Optional[tuple[list[list[float]],
+                                           list[list[float]],
+                                           list[int]]] = None
+                      ) -> list[tuple[int, str]]:
     """
     Gets q-point labels (e.g. GAMMA, X, L) for the q-points at which the
     path through reciprocal space changes direction, or where a point
@@ -170,7 +169,7 @@ def get_qpoint_labels(qpts: np.ndarray,
 
 def get_reference_data(collection: str = 'Sears1992',
                        physical_property: str = 'coherent_scattering_length'
-                       ) -> Dict[str, Quantity]:
+                       ) -> dict[str, Quantity]:
     """
     Get physical data as a dict of (possibly-complex) floats from reference
     data.
@@ -204,7 +203,7 @@ def get_reference_data(collection: str = 'Sears1992',
 
     Returns
     -------
-    Dict[str, Quantity]
+    dict[str, Quantity]
         Requested data as a dict with string keys and (possibly-complex)
         float Quantity values. String or None items of the original data file
         will be omitted.
@@ -304,7 +303,7 @@ def convert_fc_phases(force_constants: np.ndarray, atom_r: np.ndarray,
                       sc_atom_r: np.ndarray, uc_to_sc_atom_idx: np.ndarray,
                       sc_to_uc_atom_idx: np.ndarray, sc_matrix: np.ndarray,
                       cell_origins_tol: float = 1e-5
-                      ) -> Tuple[np.ndarray, np.ndarray]:
+                      ) -> tuple[np.ndarray, np.ndarray]:
     """
     Convert from a force constants matrix which uses the atom
     coordinates as r in the e^-iq.r phase (Phonopy-like), to a
@@ -390,7 +389,7 @@ def convert_fc_phases(force_constants: np.ndarray, atom_r: np.ndarray,
     # atom 0, so the same cell origins can be used for all atoms
     cell_origins_map = np.zeros((n_atoms_sc), dtype=np.int32)
     # Get origins of adjacent supercells in prim cell frac coords
-    sc_origins =  get_all_origins((2,2,2), min_xyz=(-1,-1,-1))
+    sc_origins = get_all_origins((2, 2, 2), min_xyz=(-1, -1, -1))
     sc_origins_pcell = np.einsum('ij,jk->ik', sc_origins, sc_matrix)
     for i in range(n_atoms_sc):
         co_idx = np.where(
@@ -429,7 +428,7 @@ def convert_fc_phases(force_constants: np.ndarray, atom_r: np.ndarray,
         sc_relative_idx = _get_supercell_relative_idx(cell_origins, sc_matrix)
         fc_converted[i, sc_relative_idx[cell_idx]] = fc_tmp
 
-    fc_converted =  np.reshape(np.transpose(
+    fc_converted = np.reshape(np.transpose(
         fc_converted,
         axes=[1, 0, 3, 2, 4]), (n_cells, 3*n_atoms_uc, 3*n_atoms_uc))
     return fc_converted, cell_origins
@@ -444,24 +443,23 @@ def _cell_vectors_to_volume(cell_vectors: Quantity) -> Quantity:
 
 
 def _get_unique_elems_and_idx(
-        all_elems: Sequence[Tuple[Union[int, str], ...]]
-        ) -> 'OrderedDict[Tuple[Union[int, str], ...], np.ndarray]':
+        all_elems: Sequence[tuple[int | str, ...]]
+        ) -> dict[tuple[int | str, ...], np.ndarray]:
     """
     Returns an ordered dictionary mapping the unique sequences of
     elements to their indices
     """
-    # Abuse OrderedDict to get ordered set
-    unique_elems = OrderedDict(
-        zip(all_elems, itertools.cycle([None]))).keys()
-    return OrderedDict((
+    # Abuse dict keys to get an "ordered set" of elems for iteration
+    unique_elems = dict(zip(all_elems, itertools.cycle([None]))).keys()
+    return dict((
         elem,
         np.asarray([i for i, other_elem in enumerate(all_elems)
                     if elem == other_elem])
         ) for elem in unique_elems)
 
 
 def _calc_abscissa(reciprocal_cell: Quantity, qpts: np.ndarray
-                       ) -> Quantity:
+                   ) -> Quantity:
     """
     Calculates the distance between q-points (e.g. to use as a plot
     x-coordinate)
@@ -519,10 +517,10 @@ def _calc_abscissa(reciprocal_cell: Quantity, qpts: np.ndarray
 
 
 def _recip_space_labels(qpts: np.ndarray,
-                        cell: Optional[Tuple[List[List[float]],
-                                             List[List[float]],
-                                             List[int]]]
-                        ) -> Tuple[np.ndarray, np.ndarray]:
+                        cell: Optional[tuple[list[list[float]],
+                                             list[list[float]],
+                                             list[int]]]
+                        ) -> tuple[np.ndarray, np.ndarray]:
     """
     Gets q-points point labels (e.g. GAMMA, X, L) for the q-points at
     which the path through reciprocal space changes direction or where a
@@ -592,7 +590,7 @@ def _recip_space_labels(qpts: np.ndarray,
     return labels, qpts_with_labels
 
 
-def _generic_qpt_labels() -> Dict[str, Tuple[float, float, float]]:
+def _generic_qpt_labels() -> dict[str, tuple[float, float, float]]:
     """
     Returns a dictionary relating fractional q-point label strings to
     their coordinates e.g. '1/4 1/2 1/4' = [0.25, 0.5, 0.25]. Used for
@@ -612,7 +610,7 @@ def _generic_qpt_labels() -> Dict[str, Tuple[float, float, float]]:
 
 
 def _get_qpt_label(qpt: np.ndarray,
-                   point_labels: Dict[str, Tuple[float, float, float]]
+                   point_labels: dict[str, tuple[float, float, float]]
                    ) -> str:
     """
     Gets a label for a particular q-point, based on the high symmetry

release_tox.ini

@@ -2,7 +2,7 @@
 # Use conda to set up the python environments to run in
 requires = tox-conda
 # The python environments to run the tests in
-envlist = pypi-py38-min,conda-py38-old-np,{pypi,conda}-{py38,py39,py310,py311},pypisource-{py38,py311}
+envlist = pypi-py310-min,conda-py310-old-np,{pypi,conda}-{py310,py311,py312},pypisource-{py310,py312}
 # Skip the execution of setup.py as we do it with the correct version in commands_pre below
 skipsdist = True
 
@@ -11,7 +11,7 @@ changedir = tests_and_analysis/test
 test_command = python run_tests.py --report
 
 # Test PyPI source distribution
-[testenv:pypisource-{py38,py311}]
+[testenv:pypisource-{py310,py312}]
 install_command = python -m pip install {opts} {packages}
 deps =
     numpy
@@ -24,7 +24,7 @@ commands_pre =
 commands = {[testenv]test_command}
 
 
-[testenv:pypi-{py38,py39,py310,py311}]
+[testenv:pypi-{py310,py311,py312}]
 install_command = python -m pip install {opts} {packages}
 deps =
     numpy
@@ -36,10 +36,10 @@ commands_pre =
     --only-binary 'euphonic'
 commands = {[testenv]test_command}
 
-[testenv:pypi-py38-min]
+[testenv:pypi-py310-min]
 install_command = python -m pip install --force-reinstall {opts} {packages}
 deps =
-    numpy==1.19.5
+    numpy==1.21.3
 commands_pre =
     python -m pip install --force-reinstall \
         -r{toxinidir}/tests_and_analysis/minimum_euphonic_requirements.txt
@@ -50,7 +50,7 @@ commands_pre =
     --only-binary 'euphonic'
 commands = {[testenv]test_command}
 
-[testenv:conda-{py38,py39,py310,py311}]
+[testenv:conda-{py310,py311,py312}]
 whitelist_externals = conda
 install_command = conda install {packages}
 conda_channels =
@@ -65,7 +65,7 @@ commands = {[testenv]test_command} -m "not brille"
 
 # Test against a version of Numpy less than the latest for Conda
 # See https://github.com/conda-forge/euphonic-feedstock/pull/20
-[testenv:conda-py38-old-np]
+[testenv:conda-py310-old-np]
 whitelist_externals = conda
 install_command = conda install {packages}
 conda_channels =
@@ -74,7 +74,7 @@ conda_channels =
 conda_deps =
     --file={toxinidir}/tests_and_analysis/tox_requirements.txt
 commands_pre =
-    conda install numpy=1.20
+    conda install numpy=1.22
     conda install -c conda-forge euphonic={env:EUPHONIC_VERSION} matplotlib-base pyyaml h5py
 # Brille not available on conda
 commands = {[testenv]test_command} -m "not brille"