Bump min supported Python to 3.10

.github/workflows/test.yml

@@ -17,5 +17,43 @@ jobs:
     uses: janosh/workflows/.github/workflows/pytest-release.yml@main
     with:
       os: ${{ matrix.os }}
-      python-version: 3.9
+      python-version: "3.10"
     secrets: inherit
+
+  find-scripts:
+    runs-on: ubuntu-latest
+    outputs:
+      script_list: ${{ steps.set-matrix.outputs.script_list }}
+    steps:
+      - name: Check out repository
+        uses: actions/checkout@v4
+
+      - name: Find Python scripts
+        id: set-matrix
+        run: |
+          SCRIPTS=$(find examples/make_assets -name "*.py" | jq -R -s -c 'split("\n")[:-1]')
+          echo "script_list=$SCRIPTS" >> $GITHUB_OUTPUT
+
+  test-scripts:
+    needs: find-scripts
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        script: ${{fromJson(needs.find-scripts.outputs.script_list)}}
+    steps:
+      - name: Check out repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.10"
+
+      - name: Install package and dependencies
+        run: pip install -e .[make-assets]
+
+      - name: Run script
+        run: python ${{ matrix.script }}
+        env:
+          MP_API_KEY: ${{ secrets.MP_API_KEY }}

.pre-commit-config.yaml

@@ -8,7 +8,7 @@ default_install_hook_types: [pre-commit, commit-msg]
 
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.6.1
+    rev: v0.6.3
     hooks:
       - id: ruff
         args: [--fix]
@@ -17,7 +17,7 @@ repos:
         types_or: [python, jupyter]
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.11.1
+    rev: v1.11.2
     hooks:
       - id: mypy
         additional_dependencies: [types-requests]
@@ -73,7 +73,7 @@ repos:
         exclude: ^(site/src/figs/.+\.svelte|data/wbm/20.+\..+|site/src/(routes|figs).+\.(yaml|json)|changelog.md)$
 
   - repo: https://github.com/pre-commit/mirrors-eslint
-    rev: v9.9.0
+    rev: v9.9.1
     hooks:
       - id: eslint
         types: [file]
@@ -87,6 +87,6 @@ repos:
           - typescript-eslint
 
   - repo: https://github.com/RobertCraigie/pyright-python
-    rev: v1.1.376
+    rev: v1.1.378
     hooks:
       - id: pyright

examples/dataset_exploration/matpes/eda.py

@@ -225,13 +225,21 @@
 df_pbe[Key.forces] = df_pbe[Key.forces].map(np.abs)
 
 df_r2scan_elem_forces = pd.DataFrame(
-    {site.specie.symbol: np.linalg.norm(force) for site, force in zip(struct, forces)}
-    for struct, forces in zip(df_r2scan[Key.structure], df_r2scan[Key.forces])
+    {
+        site.specie.symbol: np.linalg.norm(force)
+        for site, force in zip(struct, forces, strict=True)
+    }
+    for struct, forces in zip(
+        df_r2scan[Key.structure], df_r2scan[Key.forces], strict=True
+    )
 ).mean()
 
 df_pbe_elem_forces = pd.DataFrame(
-    {site.specie.symbol: np.linalg.norm(force) for site, force in zip(struct, forces)}
-    for struct, forces in zip(df_pbe[Key.structure], df_pbe[Key.forces])
+    {
+        site.specie.symbol: np.linalg.norm(force)
+        for site, force in zip(struct, forces, strict=True)
+    }
+    for struct, forces in zip(df_pbe[Key.structure], df_pbe[Key.forces], strict=True)
 ).mean()
 
 

examples/make_assets/phonons.py

@@ -11,6 +11,12 @@
 from pymatviz.enums import Key
 
 
+try:
+    import ffonons  # noqa: F401
+except ImportError:
+    raise SystemExit(0) from None  # install ffonons to run this script
+
+
 # %% Plot phonon bands and DOS
 for mp_id, formula in (
     ("mp-2758", "Sr4Se4"),

examples/make_assets/scatter.py

@@ -28,7 +28,7 @@
 np_rng = np.random.default_rng(seed=0)
 y_true = np_rng.normal(5, 4, rand_regression_size)
 y_pred = 1.2 * y_true - 2 * np_rng.normal(0, 1, rand_regression_size)
-y_std = (y_true - y_pred) * 10 * np_rng.normal(0, 0.1, rand_regression_size)
+y_std = abs((y_true - y_pred) * 10 * np_rng.normal(0, 0.1, rand_regression_size))
 
 
 # %% density scatter plotly
@@ -42,7 +42,7 @@
 xs, ys = make_blobs(n_samples=100_000, centers=3, n_features=2, random_state=42)
 
 x_col, y_col, target_col = "feature1", "feature2", "target"
-df_blobs = pd.DataFrame(dict(zip([x_col, y_col], xs.T)) | {target_col: ys})
+df_blobs = pd.DataFrame(dict(zip([x_col, y_col], xs.T, strict=True)) | {target_col: ys})
 
 fig = pmv.density_scatter_plotly(df=df_blobs, x=x_col, y=y_col)
 fig.show()

examples/make_assets/uncertainty.py

@@ -37,9 +37,9 @@
 
 
 # %% Cumulative Plots
-ax = pmv.cumulative_error(y_pred, y_true)
+ax = pmv.cumulative_error(y_pred - y_true)
 pmv.io.save_and_compress_svg(ax, "cumulative-error")
 
 
-ax = pmv.cumulative_residual(y_pred, y_true)
+ax = pmv.cumulative_residual(y_pred - y_true)
 pmv.io.save_and_compress_svg(ax, "cumulative-residual")

pymatviz/bar.py

@@ -100,7 +100,9 @@ def spacegroup_bar(
 
         # sort df by crystal system going from smallest to largest spacegroup numbers
         # e.g. triclinic (1-2) comes first, cubic (195-230) last
-        sys_order = dict(zip(crystal_sys_colors, range(len(crystal_sys_colors))))
+        sys_order = dict(
+            zip(crystal_sys_colors, range(len(crystal_sys_colors)), strict=True)
+        )
         df_data = df_data.loc[
             df_data[Key.crystal_system].map(sys_order).sort_values().index
         ]

pymatviz/io.py

@@ -8,7 +8,7 @@
 from pathlib import Path
 from shutil import which
 from time import sleep
-from typing import TYPE_CHECKING, Any, Callable, Final, Literal
+from typing import TYPE_CHECKING, Any, Final, Literal
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -24,7 +24,7 @@
 
 
 if TYPE_CHECKING:
-    from collections.abc import Sequence
+    from collections.abc import Callable, Sequence
     from pathlib import Path
 
     import pandas as pd
@@ -130,7 +130,7 @@ def save_fig(
     if any(var in os.environ for var in env_disable):
         return
     # handle matplotlib figures
-    if isinstance(fig, (plt.Figure, plt.Axes)):
+    if isinstance(fig, plt.Figure | plt.Axes):
         if hasattr(fig, "figure"):
             fig = fig.figure  # unwrap Axes
         fig.savefig(path, **kwargs, transparent=True)
@@ -566,7 +566,7 @@ def print_table(
         x0 = (1 - total_width) / 2
         y_i = 1
 
-        for idx, (yd, row) in enumerate(zip(row_locs, rows)):
+        for idx, (yd, row) in enumerate(zip(row_locs, rows, strict=True)):
             x_i = x0
             y_i -= yd
             # table zebra stripes
@@ -581,7 +581,7 @@ def print_table(
                 )
                 fig.add_artist(rect)
 
-            for xd, val in zip(col_widths, row):
+            for xd, val in zip(col_widths, row, strict=True):
                 text, weight, ha, bg_color, fg_color = val[:5]
 
                 if bg_color != row_colors[1]:

pymatviz/phonons.py

@@ -4,7 +4,7 @@
 
 import sys
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, Literal, Union, get_args, no_type_check
+from typing import TYPE_CHECKING, Any, Literal, get_args, no_type_check
 
 import plotly.express as px
 import plotly.graph_objects as go
@@ -23,7 +23,7 @@
     from pymatgen.core import Structure
     from typing_extensions import Self
 
-AnyBandStructure = Union[BandStructureSymmLine, PhononBands]
+AnyBandStructure = BandStructureSymmLine | PhononBands
 
 
 @dataclass
@@ -121,8 +121,8 @@ def get_band_xaxis_ticks(
     return ticks_x_pos, tick_labels
 
 
-YMin = Union[float, Literal["y_min"]]
-YMax = Union[float, Literal["y_max"]]
+YMin = float | Literal["y_min"]
+YMax = float | Literal["y_max"]
 
 
 @no_type_check
@@ -133,7 +133,7 @@ def _shaded_range(
         return fig
 
     shade_defaults = dict(layer="below", row="all", col="all")
-    y_lim = dict(zip(("y_min", "y_max"), fig.layout.yaxis.range))
+    y_lim = dict(zip(("y_min", "y_max"), fig.layout.yaxis.range, strict=True))
 
     shaded_ys = shaded_ys or {(0, "y_min"): dict(fillcolor="gray", opacity=0.07)}
     for (y0, y1), kwds in shaded_ys.items():

pymatviz/powerups/both.py

@@ -70,7 +70,7 @@ def annotate_metrics(
     """
     if isinstance(metrics, str):
         metrics = [metrics]
-    if not isinstance(metrics, (dict, list, tuple, set)):
+    if not isinstance(metrics, dict | list | tuple | set):
         raise TypeError(
             f"metrics must be dict|list|tuple|set, not {type(metrics).__name__}"
         )
@@ -166,7 +166,7 @@ def add_identity_line(
     """
     (x_min, x_max), (y_min, y_max) = get_fig_xy_range(fig=fig, trace_idx=trace_idx)
 
-    if isinstance(fig, (plt.Figure, plt.Axes)):  # handle matplotlib
+    if isinstance(fig, plt.Figure | plt.Axes):  # handle matplotlib
         ax = fig if isinstance(fig, plt.Axes) else fig.gca()
 
         line_defaults = dict(alpha=0.5, zorder=0, linestyle="dashed", color="black")

pymatviz/powerups/matplotlib.py

@@ -102,7 +102,7 @@ def annotate_bars(
 
     y_max: float = 0
     texts: list[Annotation] = []
-    for rect, label in zip(ax.patches, labels):
+    for rect, label in zip(ax.patches, labels, strict=True):
         y_pos = rect.get_height()
         x_pos = rect.get_x() + rect.get_width() / 2 + h_offset
 
@@ -113,7 +113,7 @@ def annotate_bars(
 
         y_max = max(y_max, y_pos)
 
-        txt = f"{label:,}" if isinstance(label, (int, float)) else label
+        txt = f"{label:,}" if isinstance(label, int | float) else label
         # place label at end of the bar and center horizontally
         anno = ax.annotate(
             txt, (x_pos, y_pos), ha="center", fontsize=fontsize, **kwargs

pymatviz/powerups/plotly.py

@@ -49,7 +49,7 @@ def add_ecdf_line(
 
     target_trace: BaseTraceType = fig.data[trace_idx]
     if values is None or len(values) == 0:
-        if isinstance(target_trace, (go.Histogram, go.Scatter, go.Scattergl)):
+        if isinstance(target_trace, go.Histogram | go.Scatter | go.Scattergl):
             values = target_trace.x
         elif isinstance(target_trace, go.Bar):
             xs, ys = target_trace.x, target_trace.y

pymatviz/ptable/_process_data.py

@@ -4,7 +4,7 @@
 
 import warnings
 from collections.abc import Iterable, Sequence
-from typing import TYPE_CHECKING, Literal, Union, get_args
+from typing import TYPE_CHECKING, Literal, TypeAlias, get_args
 
 import numpy as np
 import pandas as pd
@@ -14,19 +14,21 @@
 
 
 if TYPE_CHECKING:
-    from typing import Any, Callable
+    from collections.abc import Callable
+    from typing import Any
 
     from numpy.typing import NDArray
 
 
 # Data types that can be passed to PTableProjector and normalized by data_preprocessor
 # to SupportedValueType
-SupportedDataType = Union[
-    dict[str, Union[float, Sequence[float], np.ndarray]], pd.DataFrame, pd.Series
-]
+SupportedDataType: TypeAlias = (
+    dict[str, float | Sequence[float] | np.ndarray] | pd.DataFrame | pd.Series
+)
+
 
 # Data types used internally by ptable plotters (returned by preprocess_ptable_data)
-SupportedValueType = Union[Sequence[float], np.ndarray]
+SupportedValueType: TypeAlias = Sequence[float] | np.ndarray
 
 
 class PTableData:
@@ -173,7 +175,7 @@ def _write_meta_data(self) -> None:
             mean: The mean value.
             vmax: The max value.
         """
-        numeric_values = pd.to_numeric(
+        numeric_values: pd.Series = pd.to_numeric(
             self._data[self.val_col].explode().explode().explode(), errors="coerce"
         )
         self._data.attrs["vmin"] = numeric_values.min()

pymatviz/ptable/_projector.py

@@ -26,7 +26,8 @@
 
 
 if TYPE_CHECKING:
-    from typing import Any, Callable
+    from collections.abc import Callable
+    from typing import Any
 
     import pandas as pd
     from matplotlib.typing import ColorType
@@ -533,7 +534,7 @@ def rectangle(
             tick_kwargs: For compatibility with other plotters.
         """
         # Map values to colors
-        if isinstance(data, (Sequence, np.ndarray)):
+        if isinstance(data, Sequence | np.ndarray):
             colors = [cmap(norm(value)) for value in data]
         else:
             raise TypeError("Unsupported data type.")
@@ -657,7 +658,7 @@ def histogram(
             cols = (n - n.min()) / (n.max() - n.min())
 
         # Apply colors
-        for col, patch in zip(cols, patches):
+        for col, patch in zip(cols, patches, strict=True):
             plt.setp(patch, "facecolor", cmap(col))
 
         # Set tick labels
@@ -683,7 +684,7 @@ def filter_near_zero(self, tol: float = 1e-6) -> None:
 
         def to_scalar(x: float | list[float] | NDArray) -> float:
             """Convert single value array/list to scalar."""
-            if isinstance(x, (list, np.ndarray)):
+            if isinstance(x, list | np.ndarray):
                 return x[0] if len(x) > 0 else np.nan
             return x