[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -91,23 +91,23 @@ repos:
             |params.yaml
           )$
   - repo: "https://github.com/pre-commit/pre-commit-hooks"
-    rev: "v4.6.0"
+    rev: "v6.0.0"
     hooks:
       - id: "end-of-file-fixer"
       - id: "trailing-whitespace"
   - repo: "https://github.com/iterative/dvc"
-    rev: "3.51.2"
+    rev: "3.65.0"
     hooks:
       - id: "dvc-post-checkout"
         additional_dependencies: ["dvc[gs]"]
       - id: "dvc-pre-push"
         additional_dependencies: ["dvc[gs]"]
   - repo: "https://github.com/DavidAnson/markdownlint-cli2"
-    rev: "v0.13.0"
+    rev: "v0.20.0"
     hooks:
       - id: "markdownlint-cli2"
   - repo: "https://github.com/srstevenson/nb-clean"
-    rev: "3.3.0"
+    rev: "4.0.1"
     hooks:
       - id: "nb-clean"
         args:
@@ -123,7 +123,7 @@ repos:
             |tests/.*
           )$
   - repo: "https://github.com/charliermarsh/ruff-pre-commit"
-    rev: "v0.5.2"
+    rev: "v0.14.10"
     hooks:
       - id: "ruff"
         args: ["--extend-fixable", "PIE790"]

src/boilerdata/models/params.py

@@ -12,7 +12,7 @@
 from pydantic.v1 import Extra, Field
 
 from boilerdata import get_params_file
-from boilerdata.axes_enum import AxesEnum as A  # noqa: N814
+from boilerdata.axes_enum import AxesEnum as A
 from boilerdata.models.axes import Axes
 from boilerdata.models.paths import Paths
 

src/boilerdata/stages/__init__.py

@@ -12,7 +12,7 @@
 from boilercore.models.trials import Trial
 from matplotlib import pyplot as plt
 
-from boilerdata.axes_enum import AxesEnum as A  # noqa: N814
+from boilerdata.axes_enum import AxesEnum as A
 from boilerdata.models.params import PARAMS, Params
 
 idxs = pd.IndexSlice
@@ -49,7 +49,8 @@ def get_run(params: Params, run: Path) -> pd.DataFrame:
     # Need "df" defined so we can call "df.index.dropna()". Repeat `dropna` because a
     # run can have an NA index at the end and a CSV can have an all NA record at the end
     return (
-        df.reindex(index=df.index.dropna())
+        df
+        .reindex(index=df.index.dropna())
         .dropna(how="all")
         .pipe(rename_columns, params)
     )
@@ -90,7 +91,8 @@ def per_index(
 ) -> pd.DataFrame:
     """Group dataframe by index and apply a function to the groups, setting dtypes."""
     df = (
-        df.groupby(level=level, sort=False, group_keys=False)  # type: ignore
+        df
+        .groupby(level=level, sort=False, group_keys=False)  # type: ignore
         .apply(per_index_func, params, *args, **kwargs)
         .pipe(set_proj_dtypes, params)
     )

src/boilerdata/stages/metrics.ipynb

@@ -33,7 +33,7 @@
     "from IPython.display import display\n",
     "from matplotlib import pyplot as plt\n",
     "\n",
-    "from boilerdata.axes_enum import AxesEnum as A  # noqa: N814\n",
+    "from boilerdata.axes_enum import AxesEnum as A\n",
     "from boilerdata.models.params import PARAMS\n",
     "from boilerdata.stages import (\n",
     "    MODEL_WITH_UNCERTAINTY,\n",

src/boilerdata/stages/originlab.py

@@ -8,13 +8,14 @@
 import originpro as op  # type: ignore  # Not installed in CI
 import pandas as pd
 
-from boilerdata.axes_enum import AxesEnum as A  # noqa: N814
+from boilerdata.axes_enum import AxesEnum as A
 from boilerdata.models.params import PARAMS, Params
 
 
 def main():  # noqa: D103
     (
-        pd.read_csv(
+        pd
+        .read_csv(
             PARAMS.paths.file_results,
             index_col=(index := [A.trial, A.run]),
             parse_dates=index,  # pyright: ignore[reportArgumentType]
@@ -52,7 +53,8 @@ def transform_for_originlab(df: pd.DataFrame, params: Params) -> pd.DataFrame:
     })
     units = cols.get_level_values("units")
     indices = [
-        index.to_series()
+        index
+        .to_series()
         .reset_index(drop=True)
         .replace(superscript, superscript_repl)  # type: ignore  # pandas
         .replace(subscript, subscript_repl)

src/boilerdata/stages/parse_benchmarks.py

@@ -4,7 +4,7 @@
 
 import pandas as pd
 
-from boilerdata.axes_enum import AxesEnum as A  # noqa: N814
+from boilerdata.axes_enum import AxesEnum as A
 from boilerdata.models.params import PARAMS, Params
 from boilerdata.stages import get_run
 

src/boilerdata/stages/pipeline.py

@@ -10,7 +10,7 @@
 from scipy.constants import convert_temperature
 from scipy.stats import t
 
-from boilerdata.axes_enum import AxesEnum as A  # noqa: N814
+from boilerdata.axes_enum import AxesEnum as A
 from boilerdata.models.params import PARAMS, Mat, Params, Prop, get_prop
 from boilerdata.stages import MODEL, get_tcs, get_trial, per_run, per_trial
 from boilerdata.validation import (
@@ -24,7 +24,8 @@ def main():  # noqa: D103
     confidence_interval_95 = t.interval(0.95, PARAMS.records_to_average)[1]
 
     (
-        pd.read_csv(
+        pd
+        .read_csv(
             PARAMS.paths.file_runs,
             index_col=(index_col := [A.trial, A.run, A.time]),
             parse_dates=index_col,  # pyright: ignore[reportArgumentType]
@@ -120,7 +121,8 @@ def agg_over_runs(
     trial = get_trial(grp, params)
     _, tc_errors = get_tcs(trial)
     grp = (
-        grp.groupby(level=[A.trial, A.run], dropna=False)  # type: ignore  # pandas
+        grp
+        .groupby(level=[A.trial, A.run], dropna=False)  # type: ignore  # pandas
         .agg(
             **(  # type: ignore  # pandas-stubs 2.0.2
                 # Take the default agg for all cols
@@ -133,9 +135,11 @@ def agg_over_runs(
             )
         )
         .assign(**{
-            tc_error: lambda df: df[tc_error]  # noqa: B023  # False positive
-            * confidence_interval_95
-            / np.sqrt(params.records_to_average)
+            tc_error: lambda df: (
+                df[tc_error]  # noqa: B023  # False positive
+                * confidence_interval_95
+                / np.sqrt(params.records_to_average)
+            )
             for tc_error in tc_errors
         })
     )
@@ -147,7 +151,7 @@ def get_superheat(df: pd.DataFrame, params: Params) -> pd.DataFrame:
     # Explicitly index the trial to catch improper application of the mean
     trial = get_trial(df, params)
     return df.assign(**{
-        A.DT: lambda df: (df[A.T_s] - df.loc[trial.date.isoformat(), A.T_w].mean()),
+        A.DT: lambda df: df[A.T_s] - df.loc[trial.date.isoformat(), A.T_w].mean(),
         A.DT_err: lambda df: df[A.T_s_err],
     })
 

src/boilerdata/stages/runs.py

@@ -31,7 +31,8 @@ def get_runs(params: Params) -> pd.DataFrame:
             )
 
     return (
-        pd.concat(runs)
+        pd
+        .concat(runs)
         .set_index(
             pd.MultiIndex.from_tuples(
                 multiindex, names=[idx.name for idx in params.axes.index]

src/boilerdata/validation.py

@@ -4,7 +4,7 @@
 from pandera import Check, Column, DataFrameSchema, Index, MultiIndex
 from pandera.errors import SchemaError
 
-from boilerdata.axes_enum import AxesEnum as A  # noqa: N814
+from boilerdata.axes_enum import AxesEnum as A
 from boilerdata.models.params import PARAMS
 
 c = {ax.name: ax for ax in PARAMS.axes.all}