Update pre-commit hooks: formatting with ruff, format pyproject.toml

.pre-commit-config.yaml

@@ -1,31 +1,31 @@
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.3.0
+    rev: v4.5.0
     hooks:
       # - id: check-added-large-files
       - id: check-toml
       - id: check-yaml
       - id: end-of-file-fixer
       - id: trailing-whitespace
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.0
+    rev: v0.1.3
     hooks:
       - id: ruff
+        types_or: [python, pyi, jupyter]
         args:
         - --fix
-  - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.0
-    hooks:
-      - id: ruff
-        alias: isort
-        name: ruff (isort)
-        args: [--select=I001, --fix]
-  - repo: https://github.com/psf/black
-    rev: 22.10.0
+      - id: ruff-format
+        types_or: [python, pyi, jupyter]
+  - repo: https://github.com/tox-dev/pyproject-fmt
+    rev: "1.3.0"
     hooks:
-      - id: black
-        language_version: python3
+      - id: pyproject-fmt
   - repo: https://github.com/abravalheri/validate-pyproject
-    rev: v0.10.1
+    rev: v0.15
     hooks:
       - id: validate-pyproject
+  - repo: https://github.com/commitizen-tools/commitizen
+    rev: 3.12.0
+    hooks:
+      - id: commitizen-branch
+        stages: [push]

docs/code/quickstart.py

@@ -59,7 +59,9 @@
 
 print("✅ Predictions (multivariate):\n", y_pred.sort(entity_col))
 print("💯 Scores (multivariate):\n", scores_with_exog.sort("smape"))
-print("💯 Scores summary (multivariate):\n", scores_with_exog.select("smape").describe())
+print(
+    "💯 Scores summary (multivariate):\n", scores_with_exog.select("smape").describe()
+)
 
 # Check uplift from Fourier features
 uplift = (

docs/notebooks/evaluation.ipynb

@@ -143,7 +143,7 @@
     "y.select(\n",
     "    pl.all().exclude(\"price\").n_unique(),\n",
     "    pl.col(\"time\").min().dt.date().alias(\"start\"),\n",
-    "    pl.col(\"time\").max().dt.date().alias(\"end\")\n",
+    "    pl.col(\"time\").max().dt.date().alias(\"end\"),\n",
     ")"
    ]
   },
@@ -243,10 +243,7 @@
     }
    ],
    "source": [
-    "ranks = rank_point_forecasts(\n",
-    "    y_true=y_test,\n",
-    "    y_pred=y_pred_bench\n",
-    ")\n",
+    "ranks = rank_point_forecasts(y_true=y_test, y_pred=y_pred_bench)\n",
     "ranks.head()"
    ]
   },
@@ -273,7 +270,7 @@
     "    y_pred=y_pred_bench.filter(pl.col(entity_col).is_in(selected_entities)),\n",
     "    n_cols=2,\n",
     "    height=1000,\n",
-    "    width=1200\n",
+    "    width=1200,\n",
     ")\n",
     "figure.show(renderer=\"svg\")"
    ]
@@ -324,11 +321,7 @@
     }
    ],
    "source": [
-    "ranks = rank_point_forecasts(\n",
-    "    y_true=y_test,\n",
-    "    y_pred=y_pred_bench,\n",
-    "    descending=True\n",
-    ")\n",
+    "ranks = rank_point_forecasts(y_true=y_test, y_pred=y_pred_bench, descending=True)\n",
     "ranks.head()"
    ]
   },
@@ -355,7 +348,7 @@
     "    y_pred=y_pred_bench.filter(pl.col(entity_col).is_in(selected_entities)),\n",
     "    n_cols=2,\n",
     "    height=1000,\n",
-    "    width=1200\n",
+    "    width=1200,\n",
     ")\n",
     "figure.show(renderer=\"svg\")"
    ]
@@ -377,12 +370,7 @@
    "source": [
     "# Instantiate forecaster and backtest\n",
     "forecaster = lightgbm(freq=\"1mo\", lags=48, target_transform=detrend())\n",
-    "y_preds, y_resids = forecaster.backtest(\n",
-    "    y=y,\n",
-    "    test_size=12,\n",
-    "    step_size=12,\n",
-    "    n_splits=5\n",
-    ")\n",
+    "y_preds, y_resids = forecaster.backtest(y=y, test_size=12, step_size=12, n_splits=5)\n",
     "y_pred = forecaster(fh=fh, y=y_train)"
    ]
   },
@@ -462,7 +450,7 @@
     "    y_pred=y_preds.filter(pl.col(entity_col).is_in(selected_entities)),\n",
     "    n_cols=2,\n",
     "    height=1000,\n",
-    "    width=1200\n",
+    "    width=1200,\n",
     ")\n",
     "figure.show(renderer=\"svg\")"
    ]
@@ -513,11 +501,7 @@
     }
    ],
    "source": [
-    "ranks = rank_point_forecasts(\n",
-    "    y_true=y,\n",
-    "    y_pred=y_preds,\n",
-    "    descending=True\n",
-    ")\n",
+    "ranks = rank_point_forecasts(y_true=y, y_pred=y_preds, descending=True)\n",
     "ranks.head()"
    ]
   },
@@ -544,7 +528,7 @@
     "    y_pred=y_preds.filter(pl.col(entity_col).is_in(selected_entities)),\n",
     "    n_cols=2,\n",
     "    height=1000,\n",
-    "    width=1200\n",
+    "    width=1200,\n",
     ")\n",
     "figure.show(renderer=\"svg\")"
    ]
@@ -595,11 +579,7 @@
     }
    ],
    "source": [
-    "ranks = rank_residuals(\n",
-    "    y_resids=y_resids,\n",
-    "    sort_by=\"abs_bias\",\n",
-    "    descending=True\n",
-    ")\n",
+    "ranks = rank_residuals(y_resids=y_resids, sort_by=\"abs_bias\", descending=True)\n",
     "ranks.head()"
    ]
   },
@@ -625,7 +605,7 @@
     "    y_resids=y_resids.filter(pl.col(entity_col).is_in(selected_entities)),\n",
     "    n_bins=200,\n",
     "    height=800,\n",
-    "    width=1000\n",
+    "    width=1000,\n",
     ")\n",
     "figure.show(renderer=\"svg\")"
    ]
@@ -676,11 +656,7 @@
     }
    ],
    "source": [
-    "ranks = rank_residuals(\n",
-    "    y_resids=y_resids,\n",
-    "    sort_by=\"normality\",\n",
-    "    descending=True\n",
-    ")\n",
+    "ranks = rank_residuals(y_resids=y_resids, sort_by=\"normality\", descending=True)\n",
     "ranks.head()"
    ]
   },
@@ -706,7 +682,7 @@
     "    y_resids=y_resids.filter(pl.col(entity_col).is_in(selected_entities)),\n",
     "    n_bins=200,\n",
     "    height=800,\n",
-    "    width=1000\n",
+    "    width=1000,\n",
     ")\n",
     "figure.show(renderer=\"svg\")"
    ]
@@ -738,11 +714,7 @@
    ],
    "source": [
     "figure = plot_fva(\n",
-    "    y_true=y_test,\n",
-    "    y_pred=y_pred,\n",
-    "    y_pred_bench=y_pred_bench,\n",
-    "    height=900,\n",
-    "    width=900\n",
+    "    y_true=y_test, y_pred=y_pred, y_pred_bench=y_pred_bench, height=900, width=900\n",
     ")\n",
     "figure.show(renderer=\"svg\")"
    ]
@@ -774,11 +746,7 @@
    ],
    "source": [
     "figure = plot_comet(\n",
-    "    y_train=y_train,\n",
-    "    y_test=y_test,\n",
-    "    y_pred=y_pred,\n",
-    "    height=900,\n",
-    "    width=900\n",
+    "    y_train=y_train, y_test=y_test, y_pred=y_pred, height=900, width=900\n",
     ")\n",
     "figure.show(renderer=\"svg\")"
    ]

docs/notebooks/llm.ipynb

@@ -33,7 +33,9 @@
    "outputs": [],
    "source": [
     "import os\n",
-    "from IPython.display import display, Markdown\n",
+    "\n",
+    "from IPython.display import Markdown, display\n",
+    "\n",
     "os.environ[\"OPENAI_API_KEY\"] = \"...\"  # Your API key here"
    ]
   },
@@ -180,7 +182,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "dataset_context = \"This dataset comprises of forecasted commodity prices between 2020 to 2023.\""
+    "dataset_context = (\n",
+    "    \"This dataset comprises of forecasted commodity prices between 2020 to 2023.\"\n",
+    ")"
    ]
   },
   {
@@ -230,7 +234,7 @@
    "source": [
     "analysis = y_pred.llm.analyze(\n",
     "    context=\"This dataset comprises of forecasted commodity prices between 2020 to 2023.\",\n",
-    "    basket=[\"Aluminum\", \"Banana, Europe\"]\n",
+    "    basket=[\"Aluminum\", \"Banana, Europe\"],\n",
     ")\n",
     "display(Markdown(analysis))"
    ]
@@ -306,10 +310,7 @@
     }
    ],
    "source": [
-    "comparison = y_pred.llm.compare(\n",
-    "    basket=basket_a,\n",
-    "    other_basket=basket_b\n",
-    ")\n",
+    "comparison = y_pred.llm.compare(basket=basket_a, other_basket=basket_b)\n",
     "display(Markdown(comparison))"
    ]
   }