Clean up var names in unit tests, avoid MP API access in GitHub workflow

examples/make_assets/structure_viz.py

@@ -1,4 +1,5 @@
 # %%
+import os
 from typing import cast
 
 import matplotlib.pyplot as plt
@@ -10,8 +11,6 @@
 from pymatviz.enums import ElemColorScheme, Key
 
 
-struct: Structure  # for type hinting
-
 df_steels = load_dataset("matbench_steels")
 df_phonons = load_dataset("matbench_phonons")
 
@@ -31,11 +30,18 @@
 
 
 # %% Plot some disordered structures in 2D
+if os.environ.get("MP_API_KEY") is None:
+    raise RuntimeError("no mp api key, debugging")
+
 disordered_structs = {
-    mp_id: MPRester().get_structure_by_material_id(mp_id, conventional_unit_cell=True)
+    mp_id: MPRester(api_key=os.environ.get("MP_API_KEY")).get_structure_by_material_id(
+        mp_id, conventional_unit_cell=True
+    )
     for mp_id in ["mp-19017", "mp-12712"]
 }
 
+struct: Structure  # for type hinting
+
 for mp_id, struct in disordered_structs.items():
     for site in struct:  # disorder structures in-place
         if "Fe" in site.species:

tests/conftest.py

@@ -17,9 +17,9 @@
     from collections.abc import Generator
 
 
-# if platform is windows, set matplotlib backend to "Agg" to fix
-# _tkinter.TclError: Can't find a usable init.tcl in the following directories
-# https://github.com/orgs/community/discussions/26434
+# If platform is Windows, set matplotlib backend to "Agg" to fix:
+# "_tkinter.TclError: Can't find a usable init.tcl in the following directories"
+# See: https://github.com/orgs/community/discussions/26434
 if platform.system() == "Windows":
     import matplotlib as mpl
 
@@ -52,10 +52,10 @@ def df_or_arrays(request: pytest.FixtureRequest) -> DfOrArrays:
 
 @pytest.fixture(autouse=True)
 def _run_around_tests() -> Generator[None, None, None]:
-    """Ensure matplotlib plots are closed after each test so as not to leak state
-    between tests."""
+    """Ensure matplotlib plots are closed after each test
+    so as not to leak state between tests.
+    """
     # runs before each test
-
     yield
 
     # runs after each test
@@ -121,7 +121,7 @@ def matplotlib_scatter() -> plt.Figure:
 
 @pytest.fixture
 def glass_formulas() -> list[str]:
-    """First 20 materials in the Matbench glass dataset.
+    """First 20 materials in the MatBench glass dataset.
 
     from matminer.datasets import load_dataset
 

tests/test_bar.py

@@ -9,7 +9,6 @@
 
 from pymatviz.bar import spacegroup_bar
 from pymatviz.utils import BACKENDS, MATPLOTLIB, PLOTLY
-from tests.conftest import y_pred, y_true
 
 
 if TYPE_CHECKING:
@@ -20,9 +19,6 @@
     from pymatviz.utils import Backend
 
 
-y_std_mock = y_true - y_pred
-
-
 @pytest.mark.parametrize("backend", BACKENDS)
 @pytest.mark.parametrize(
     ("xticks", "show_counts", "show_empty_bins", "log"),

tests/test_scatter.py

@@ -26,8 +26,8 @@
     from tests.conftest import DfOrArrays
 
 
-x_col, y_col, *_ = df_regr
-df_tips = px.data.tips()
+X_COL, Y_COL, *_ = df_regr
+DF_TIPS = px.data.tips()
 
 
 @pytest.mark.parametrize("log_density", [True, False])
@@ -166,7 +166,7 @@ def test_density_scatter_plotly(
 
 
 def test_density_scatter_plotly_hover_template() -> None:
-    fig = density_scatter_plotly(df=df_regr, x=x_col, y=y_col, log_density=True)
+    fig = density_scatter_plotly(df=df_regr, x=X_COL, y=Y_COL, log_density=True)
     hover_template = fig.data[0].hovertemplate
     assert "Point Density" in hover_template
     assert "color" not in hover_template  # Ensure log-count values are not displayed
@@ -175,18 +175,18 @@ def test_density_scatter_plotly_hover_template() -> None:
 @pytest.mark.parametrize("stats", [1, (1,), "foo"])
 def test_density_scatter_plotly_raises_on_bad_stats_type(stats: Any) -> None:
     with pytest.raises(TypeError, match="stats must be bool or dict"):
-        density_scatter_plotly(df=df_regr, x=x_col, y=y_col, stats=stats)
+        density_scatter_plotly(df=df_regr, x=X_COL, y=Y_COL, stats=stats)
 
 
 def test_density_scatter_plotly_empty_dataframe() -> None:
-    empty_df = pd.DataFrame({x_col: [], y_col: []})
+    empty_df = pd.DataFrame({X_COL: [], Y_COL: []})
     with pytest.raises(ValueError, match="input should have multiple elements"):
-        density_scatter_plotly(df=empty_df, x=x_col, y=y_col)
+        density_scatter_plotly(df=empty_df, x=X_COL, y=Y_COL)
 
 
 def test_density_scatter_plotly_facet() -> None:
     fig = density_scatter_plotly(
-        df=df_tips, x="total_bill", y="tip", facet_col="smoker"
+        df=DF_TIPS, x="total_bill", y="tip", facet_col="smoker"
     )
 
     assert isinstance(fig, go.Figure)
@@ -196,7 +196,7 @@ def test_density_scatter_plotly_facet() -> None:
 
 def test_density_scatter_plotly_facet_log_density() -> None:
     fig = density_scatter_plotly(
-        df=df_tips, x="total_bill", y="tip", facet_col="smoker", log_density=True
+        df=DF_TIPS, x="total_bill", y="tip", facet_col="smoker", log_density=True
     )
 
     assert fig.layout.coloraxis.colorbar.ticktext is not None
@@ -205,7 +205,7 @@ def test_density_scatter_plotly_facet_log_density() -> None:
 
 def test_density_scatter_plotly_facet_stats() -> None:
     fig = density_scatter_plotly(
-        df=df_tips, x="total_bill", y="tip", facet_col="smoker", stats=True
+        df=DF_TIPS, x="total_bill", y="tip", facet_col="smoker", stats=True
     )
 
     # Check there are at least 2 annotations (could be more due to facet labels)
@@ -217,7 +217,7 @@ def test_density_scatter_plotly_facet_stats() -> None:
 
 def test_density_scatter_plotly_facet_best_fit_line() -> None:
     fig = density_scatter_plotly(
-        df=df_tips, x="total_bill", y="tip", facet_col="smoker", best_fit_line=True
+        df=DF_TIPS, x="total_bill", y="tip", facet_col="smoker", best_fit_line=True
     )
 
     # Check there are at least 4 shapes (2 identity lines, 2 best fit lines)
@@ -231,18 +231,18 @@ def test_density_scatter_plotly_facet_best_fit_line() -> None:
 
 def test_density_scatter_plotly_facet_custom_bins() -> None:
     fig = density_scatter_plotly(
-        df=df_tips, x="total_bill", y="tip", facet_col="smoker", n_bins=10
+        df=DF_TIPS, x="total_bill", y="tip", facet_col="smoker", n_bins=10
     )
 
     # Check that binning has been applied (number of points should be reduced)
-    smoker_count = df_tips["smoker"].value_counts()
+    smoker_count = DF_TIPS["smoker"].value_counts()
     assert len(fig.data[0].x) < smoker_count["No"]
     assert len(fig.data[1].x) < smoker_count["Yes"]
 
 
 def test_density_scatter_plotly_facet_custom_color() -> None:
     fig = density_scatter_plotly(
-        df=df_tips,
+        df=DF_TIPS,
         x="total_bill",
         y="tip",
         facet_col="smoker",
@@ -260,7 +260,7 @@ def test_density_scatter_plotly_facet_density_methods(
     density: Literal["kde", "empirical"],
 ) -> None:
     fig = density_scatter_plotly(
-        df=df_tips, x="total_bill", y="tip", facet_col="smoker", density=density
+        df=DF_TIPS, x="total_bill", y="tip", facet_col="smoker", density=density
     )
 
     assert isinstance(fig, go.Figure)
@@ -269,30 +269,30 @@ def test_density_scatter_plotly_facet_density_methods(
 
 def test_density_scatter_plotly_facet_size() -> None:
     fig = density_scatter_plotly(
-        df=df_tips, x="total_bill", y="tip", size="size", facet_col="smoker"
+        df=DF_TIPS, x="total_bill", y="tip", size="size", facet_col="smoker"
     )
 
     assert "marker.size" in fig.data[0]
     assert "marker.size" in fig.data[1]
 
 
 def test_density_scatter_plotly_facet_multiple_categories() -> None:
-    fig = density_scatter_plotly(df=df_tips, x="total_bill", y="tip", facet_col="day")
+    fig = density_scatter_plotly(df=DF_TIPS, x="total_bill", y="tip", facet_col="day")
 
-    assert len(fig.data) == df_tips["day"].nunique()
+    assert len(fig.data) == DF_TIPS["day"].nunique()
 
 
 def test_density_scatter_plotly_facet_identity_line() -> None:
     fig = density_scatter_plotly(
-        df=df_tips, x="total_bill", y="tip", facet_col="smoker", identity_line=True
+        df=DF_TIPS, x="total_bill", y="tip", facet_col="smoker", identity_line=True
     )
 
     assert len(fig.layout.shapes) == 2  # Two identity lines, one for each facet
 
 
 def test_density_scatter_plotly_facet_hover_template() -> None:
     fig = density_scatter_plotly(
-        df=df_tips, x="total_bill", y="tip", facet_col="smoker"
+        df=DF_TIPS, x="total_bill", y="tip", facet_col="smoker"
     )
 
     for trace in fig.data:

tests/test_structure_viz.py

@@ -17,9 +17,9 @@
 if TYPE_CHECKING:
     from collections.abc import Sequence
 
-coords = [[0, 0, 0], [0.5, 0.5, 0.5]]
-disordered_struct = Structure(
-    lattice := np.eye(3) * 5, species=[{"Fe": 0.75, "C": 0.25}, "O"], coords=coords
+COORDS = [[0, 0, 0], [0.5, 0.5, 0.5]]
+DISORDERED_STRUCT = Structure(
+    lattice := np.eye(3) * 5, species=[{"Fe": 0.75, "C": 0.25}, "O"], coords=COORDS
 )
 
 
@@ -39,7 +39,7 @@ def test_structure_2d(
     standardize_struct: bool | None,
 ) -> None:
     ax = pmv.structure_2d(
-        disordered_struct,
+        DISORDERED_STRUCT,
         atomic_radii=radii,
         rotation=rotation,
         site_labels=labels,
@@ -57,15 +57,15 @@ def test_structure_2d(
     patch_counts = pd.Series(
         [type(patch).__name__ for patch in ax.patches]
     ).value_counts()
-    assert patch_counts["Wedge"] == len(disordered_struct.composition)
+    assert patch_counts["Wedge"] == len(DISORDERED_STRUCT.composition)
 
     min_expected_n_patches = 182
     assert patch_counts["PathPatch"] > min_expected_n_patches
 
 
 @pytest.mark.parametrize("axis", [True, False, "on", "off", "square", "equal"])
 def test_structure_2d_axis(axis: str | bool) -> None:
-    ax = pmv.structure_2d(disordered_struct, axis=axis)
+    ax = pmv.structure_2d(DISORDERED_STRUCT, axis=axis)
     assert isinstance(ax, plt.Axes)
     assert ax.axes.axison == (axis not in (False, "off"))
 
@@ -77,7 +77,7 @@ def test_structure_2d_axis(axis: str | bool) -> None:
 def test_structure_2d_site_labels(
     site_labels: bool | str | dict[str, str | float] | Sequence[str],
 ) -> None:
-    ax = pmv.structure_2d(disordered_struct, site_labels=site_labels)
+    ax = pmv.structure_2d(DISORDERED_STRUCT, site_labels=site_labels)
     assert isinstance(ax, plt.Axes)
     if site_labels is False:
         assert not ax.axes.texts
@@ -88,8 +88,8 @@ def test_structure_2d_site_labels(
 
 def test_structure_2d_warns() -> None:
     # for sites with negative fractional coordinates
-    orig_coords = disordered_struct[0].frac_coords.copy()
-    disordered_struct[0].frac_coords = [-0.1, 0.1, 0.1]
+    orig_coords = DISORDERED_STRUCT[0].frac_coords.copy()
+    DISORDERED_STRUCT[0].frac_coords = [-0.1, 0.1, 0.1]
     standardize_struct = False
     try:
         with pytest.warns(
@@ -99,24 +99,24 @@ def test_structure_2d_warns() -> None:
                 f"{standardize_struct=}, you may want to set standardize_struct=True"
             ),
         ):
-            pmv.structure_2d(disordered_struct, standardize_struct=standardize_struct)
+            pmv.structure_2d(DISORDERED_STRUCT, standardize_struct=standardize_struct)
     finally:
-        disordered_struct[0].frac_coords = orig_coords
+        DISORDERED_STRUCT[0].frac_coords = orig_coords
 
     # warns when passing subplot_kwargs for a single structure
     with pytest.warns(
         UserWarning, match="subplot_kwargs are ignored when plotting a single structure"
     ):
-        pmv.structure_2d(disordered_struct, subplot_kwargs={"facecolor": "red"})
+        pmv.structure_2d(DISORDERED_STRUCT, subplot_kwargs={"facecolor": "red"})
 
 
-struct1 = Structure(lattice, ["Fe", "O"], coords=coords)
+struct1 = Structure(lattice, ["Fe", "O"], coords=COORDS)
 struct1.properties = {"id": "struct1"}
-struct2 = Structure(lattice, ["Co", "O"], coords=coords)
+struct2 = Structure(lattice, ["Co", "O"], coords=COORDS)
 struct2.properties = {Key.mat_id: "struct2"}
-struct3 = Structure(lattice, ["Ni", "O"], coords=coords)
+struct3 = Structure(lattice, ["Ni", "O"], coords=COORDS)
 struct3.properties = {"ID": "struct3", "name": "nickel oxide"}  # extra properties
-struct4 = Structure(lattice, ["Cu", "O"], coords=coords)
+struct4 = Structure(lattice, ["Cu", "O"], coords=COORDS)
 
 
 def test_structure_2d_multiple() -> None:
@@ -167,7 +167,7 @@ def subplot_title(struct: Structure, key: str | int) -> str:
 def test_structure_2d_color_warning() -> None:
     # Copernicium is not in the default color scheme
     elem_symbol = "Cn"
-    struct = Structure(np.eye(3) * 5, [elem_symbol] * 2, coords=coords)
+    struct = Structure(np.eye(3) * 5, [elem_symbol] * 2, coords=COORDS)
     fallback_color = "gray"
 
     for elem_colors in ElemColorScheme:
@@ -188,7 +188,7 @@ def test_structure_2d_color_warning() -> None:
 
     # create custom color scheme missing an element
     custom_colors = {"Fe": "red"}
-    struct = Structure(np.eye(3) * 5, ["Fe", "O"], coords=coords)
+    struct = Structure(np.eye(3) * 5, ["Fe", "O"], coords=COORDS)
 
     with pytest.warns(
         UserWarning,

tests/test_uncertainty.py

@@ -16,14 +16,14 @@
     from numpy.typing import ArrayLike
 
 
-y_std_mock = y_true - y_pred
+Y_STD_MOCK = y_true - y_pred
 
 
 @pytest.mark.parametrize(
     "y_std",
     [
-        y_std_mock,
-        {"y_std_mock": y_std_mock},
+        Y_STD_MOCK,
+        {"y_std_mock": Y_STD_MOCK},
         df_regr.columns[0],  # single std col
         df_regr.columns[:2],  # multiple std cols
     ],
@@ -39,7 +39,7 @@ def test_error_decay_with_uncert(
     df, x, y = df_or_arrays
     # override y_std if col name but no df provided, would be nonsensical input
     if df is None and isinstance(y_std, str | pd.Index):
-        y_std = y_std_mock
+        y_std = Y_STD_MOCK
     ax = error_decay_with_uncert(
         x, y, y_std, df=df, n_rand=n_rand, percentiles=percentiles
     )