Adopt Ruff in Place of flake8 and black For Modern Linting Stack

.git-blame-ignore-revs

@@ -0,0 +1,3 @@
+# Migrate from Black to ruff
+bc2e00b5eaee49cca7829dd615dedbf9d202fa11
+df59900337de9c74cdbc7aba8511e3840afb0737

.pre-commit-config.yaml

@@ -1,14 +1,6 @@
 repos:
-  - repo: https://github.com/psf/black
-    rev: 26.1.0
-    hooks:
-        - id: black
-          name: black
-          stages: [pre-commit]
-          language_version: python3
-
   - repo: https://github.com/pycqa/isort
-    rev: 7.0.0
+    rev: 9.0.2
     hooks:
       - id: isort
         additional_dependencies: [toml]
@@ -22,11 +14,14 @@ repos:
         additional_dependencies: [toml]
         types: [pyi]
 
-  - repo: https://github.com/asottile/pyupgrade
-    rev: v3.21.2
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.16.10
     hooks:
-    - id: pyupgrade
-      args: [--py38-plus]
+      - id: ruff-check
+        types_or: [python, pyi, jupyter]
+        args: [--fix]
+      - id: ruff-format
+        types_or: [python, pyi, jupyter]
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v6.0.0
@@ -40,8 +35,3 @@ repos:
     -   id: mixed-line-ending
     -   id: pretty-format-json
         args: [--autofix]
-
-  -   repo: https://github.com/pycqa/flake8
-      rev: '7.3.0'
-      hooks:
-      -   id: flake8

CHANGELOG.md

@@ -1,6 +1,10 @@
 # Changelog
 All notable changes to this project will be documented in this file. If you make a notable change to the project, please add a line describing the change to the "unreleased" section. The maintainers will make an effort to keep the [Github Releases](https://github.com/NREL/OpenOA/releases) page up to date with this changelog. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 
+## Unreleased
+
+- Replace `black` and `flake8` with `ruff` for faster and more robust linting/automated formatting.
+
 ## v3.2 - 2026-01-29
 
 - Features and updates:

README.md

@@ -13,7 +13,7 @@
 [![PyPI downloads](https://img.shields.io/pypi/dm/openoa)](https://pypi.org/project/WOMBAT/)
 
 [![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
-[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+[![Code style: Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
 [![Imports: isort](https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336)](https://pycqa.github.io/isort/)
 <!-- ALL-CONTRIBUTORS-BADGE:START - Do not remove or modify this section -->
 [![All Contributors](https://img.shields.io/badge/all_contributors-15-orange.svg?style=flat-square)](#contributors-)

contributing.md

@@ -143,8 +143,8 @@ will need to accept the Contributor License Agreement(CLA).
 ## Coding Style
 
 This code uses a ``pre-commit`` workflow where code styling and linting is taken care of when a user
-commits their code. Specifically, this code utilizes ``black`` for automatic formatting (line length, quotation usage, hanging
-lines, etc.), ``isort`` for automatic import sorting, and ``flake8`` for linting.
+commits their code. Specifically, this code utilizes ``ruff`` for automatic formatting (line length,
+quotation usage, hanging lines, etc.) and linting and ``isort`` for automatic import sorting.
 
 To activate the ``pre-commit`` workflow, the user must install the develop version as outlined in the
 [Readme](https://github.com/NREL/OpenOA/tree/develop#Development), and run the following line:

examples/00_intro_to_plant_data.ipynb

@@ -809,7 +809,7 @@
         "    df=scada_df_tz,\n",
         "    time_col=\"Date_time\",\n",
         "    local_tz=\"Europe/Paris\",\n",
-        "    tz_aware=True # Indicate that we can use encoded data to convert between timezones\n",
+        "    tz_aware=True,  # Indicate that we can use encoded data to convert between timezones\n",
         ")\n",
         "scada_df_tz.head()"
       ]
@@ -1043,7 +1043,7 @@
         "    df=scada_df_no_tz,\n",
         "    time_col=\"Date_time\",\n",
         "    local_tz=\"Europe/Paris\",\n",
-        "    tz_aware=False  # Indicates that we're going to need to make inferences about encoding the timezones\n",
+        "    tz_aware=False,  # Indicates that we're going to need to make inferences about encoding the timezones\n",
         ")\n",
         "scada_df_no_tz.head()"
       ]
@@ -1249,8 +1249,19 @@
       ],
       "source": [
         "no_tz = qa.describe(scada_df_no_tz)\n",
-        "no_tz = no_tz.loc[~no_tz.index.isin([\"Date_time\"])] # Ignore the Date_time column that is not shared between the dataframes\n",
-        "col_order = [\"count\", \"mean\", \"std\", \"min\", \"25%\", \"50%\", \"75%\", \"max\"] # Ensure description columns are in the same order\n",
+        "no_tz = no_tz.loc[\n",
+        "    ~no_tz.index.isin([\"Date_time\"])\n",
+        "]  # Ignore the Date_time column that is not shared between the dataframes\n",
+        "col_order = [\n",
+        "    \"count\",\n",
+        "    \"mean\",\n",
+        "    \"std\",\n",
+        "    \"min\",\n",
+        "    \"25%\",\n",
+        "    \"50%\",\n",
+        "    \"75%\",\n",
+        "    \"max\",\n",
+        "]  # Ensure description columns are in the same order\n",
         "qa.describe(scada_df_tz)[col_order] == no_tz[col_order]"
       ]
     },
@@ -1621,9 +1632,7 @@
       ],
       "source": [
         "dup_orig_no_tz, dup_local_no_tz, dup_utc_no_tz = qa.duplicate_time_identification(\n",
-        "    df=scada_df_no_tz,\n",
-        "    time_col=\"Date_time\",\n",
-        "    id_col=\"Wind_turbine_name\"\n",
+        "    df=scada_df_no_tz, time_col=\"Date_time\", id_col=\"Wind_turbine_name\"\n",
         ")\n",
         "dup_orig_no_tz.size, dup_local_no_tz.size, dup_utc_no_tz.size"
       ]
@@ -1729,9 +1738,7 @@
       ],
       "source": [
         "gap_orig_no_tz, gap_local_no_tz, gap_utc_no_tz = qa.gap_time_identification(\n",
-        "    df=scada_df_no_tz,\n",
-        "    time_col=\"Date_time\",\n",
-        "    freq=\"10min\"\n",
+        "    df=scada_df_no_tz, time_col=\"Date_time\", freq=\"10min\"\n",
         ")\n",
         "gap_orig_no_tz.size, gap_local_no_tz.size, gap_utc_no_tz.size"
       ]
@@ -1840,7 +1847,7 @@
         "    time_col=\"Date_time\",\n",
         "    power_col=\"P_avg\",\n",
         "    freq=\"10min\",\n",
-        "    hour_window=3  # default value\n",
+        "    hour_window=3,  # default value\n",
         ")"
       ]
     },
@@ -1864,9 +1871,7 @@
       "outputs": [],
       "source": [
         "dup_orig_tz, dup_local_tz, dup_utc_tz = qa.duplicate_time_identification(\n",
-        "    df=scada_df_tz,\n",
-        "    time_col=\"Date_time\",\n",
-        "    id_col=\"Wind_turbine_name\"\n",
+        "    df=scada_df_tz, time_col=\"Date_time\", id_col=\"Wind_turbine_name\"\n",
         ")"
       ]
     },
@@ -1980,9 +1985,7 @@
       ],
       "source": [
         "gap_orig_tz, gap_local_tz, gap_utc_tz = qa.gap_time_identification(\n",
-        "    df=scada_df_tz,\n",
-        "    time_col=\"Date_time\",\n",
-        "    freq=\"10min\"\n",
+        "    df=scada_df_tz, time_col=\"Date_time\", freq=\"10min\"\n",
         ")\n",
         "gap_orig_tz.size, gap_local_tz.size, gap_utc_tz.size"
       ]
@@ -2054,7 +2057,7 @@
         "    time_col=\"Date_time\",\n",
         "    power_col=\"P_avg\",\n",
         "    freq=\"10min\",\n",
-        "    hour_window=3  # default value\n",
+        "    hour_window=3,  # default value\n",
         ")"
       ]
     },
@@ -2265,6 +2268,7 @@
       ],
       "source": [
         "from openoa.plant import PlantMetaData\n",
+        "\n",
         "print(PlantMetaData.__doc__)"
       ]
     },
@@ -2349,7 +2353,7 @@
         "print(f\"The new analysis types now has all and MonteCarloAEP: {engie.analysis_type}\")\n",
         "try:\n",
         "    engie.validate()\n",
-        "except ValueError as e: # Catch the error message so that the whole notebook can run\n",
+        "except ValueError as e:  # Catch the error message so that the whole notebook can run\n",
         "    print(e)"
       ]
     },
@@ -2398,7 +2402,7 @@
         "    asset=f\"{data_path}/asset.csv\",\n",
         "    reanalysis={\n",
         "        \"era5\": f\"{data_path}/reanalysis_era5.csv\",\n",
-        "        \"merra2\": f\"{data_path}/reanalysis_merra2.csv\"\n",
+        "        \"merra2\": f\"{data_path}/reanalysis_merra2.csv\",\n",
         "    },\n",
         ")"
       ]

examples/01_utils_examples.ipynb

@@ -367,6 +367,7 @@
         "\n",
         "from bokeh.plotting import show\n",
         "from bokeh.io import output_notebook\n",
+        "\n",
         "output_notebook()\n",
         "\n",
         "from openoa.utils import filters, power_curve, plot\n",
@@ -697,7 +698,7 @@
         "    xlim=(-1, 20),  # optional input for refining plots\n",
         "    ylim=(-100, 2100),  # optional input for refining plots\n",
         "    legend=True,  # optional flag for adding a legend\n",
-        "    scatter_kwargs=dict(alpha=0.8, s=10)  # optional input for refining plots\n",
+        "    scatter_kwargs=dict(alpha=0.8, s=10),  # optional input for refining plots\n",
         ")"
       ]
     },
@@ -757,7 +758,7 @@
         }
       ],
       "source": [
-        "out_of_window = filters.window_range_flag(windspeed, 5., 40, power_kw, 20., 2100.)\n",
+        "out_of_window = filters.window_range_flag(windspeed, 5.0, 40, power_kw, 20.0, 2100.0)\n",
         "plot.plot_power_curve(\n",
         "    windspeed,\n",
         "    power_kw,\n",
@@ -766,7 +767,7 @@
         "    xlim=(-1, 20),  # optional input for refining plots\n",
         "    ylim=(-100, 2100),  # optional input for refining plots\n",
         "    legend=True,  # optional flag for adding a legend\n",
-        "    scatter_kwargs=dict(alpha=0.4, s=10)  # optional input for refining plots\n",
+        "    scatter_kwargs=dict(alpha=0.4, s=10),  # optional input for refining plots\n",
         ")"
       ]
     },
@@ -816,7 +817,9 @@
       ],
       "source": [
         "max_bin = 0.90 * power_kw_filt1.max()\n",
-        "bin_outliers = filters.bin_filter(power_kw_filt1, windspeed_filt1, 100, 1.5, \"median\", 20., max_bin, \"scalar\", \"all\")\n",
+        "bin_outliers = filters.bin_filter(\n",
+        "    power_kw_filt1, windspeed_filt1, 100, 1.5, \"median\", 20.0, max_bin, \"scalar\", \"all\"\n",
+        ")\n",
         "plot.plot_power_curve(\n",
         "    windspeed_filt1,\n",
         "    power_kw_filt1,\n",
@@ -825,7 +828,7 @@
         "    xlim=(-1, 20),  # optional input for refining plots\n",
         "    ylim=(-100, 2100),  # optional input for refining plots\n",
         "    legend=True,  # optional flag for adding a legend\n",
-        "    scatter_kwargs=dict(alpha=0.5, s=10)  # optional input for refining plots\n",
+        "    scatter_kwargs=dict(alpha=0.5, s=10),  # optional input for refining plots\n",
         ")"
       ]
     },
@@ -881,7 +884,7 @@
         "    xlim=(-1, 20),  # optional input for refining plots\n",
         "    ylim=(-100, 2100),  # optional input for refining plots\n",
         "    legend=True,  # optional flag for adding a legend\n",
-        "    scatter_kwargs=dict(alpha=0.4, s=10)  # optional input for refining plots\n",
+        "    scatter_kwargs=dict(alpha=0.4, s=10),  # optional input for refining plots\n",
         ")"
       ]
     },
@@ -972,9 +975,9 @@
         ")\n",
         "\n",
         "x = np.linspace(0, 20, 100)\n",
-        "ax.plot(x, iec_curve(x), color=\"red\", label = \"IEC\", linewidth = 3)\n",
-        "ax.plot(x, spline_curve(x), color=\"C1\", label = \"Spline\", linewidth = 3)\n",
-        "ax.plot(x, l5p_curve(x), color=\"C2\", label = \"L5P\", linewidth = 3)\n",
+        "ax.plot(x, iec_curve(x), color=\"red\", label=\"IEC\", linewidth=3)\n",
+        "ax.plot(x, spline_curve(x), color=\"C1\", label=\"Spline\", linewidth=3)\n",
+        "ax.plot(x, l5p_curve(x), color=\"C2\", label=\"L5P\", linewidth=3)\n",
         "\n",
         "ax.legend()\n",
         "\n",