Add ruff linting to Makefile format target

.github/update_api.py

@@ -1,6 +1,5 @@
-import argparse
-import tomllib
 import os
+import tomllib
 
 
 def main():

Makefile

@@ -11,6 +11,7 @@ install:
 	pip install huggingface_hub
 
 format:
+	ruff check . --fix
 	ruff format .
 
 test:

changelog.d/add-ruff-linting.added.md

@@ -0,0 +1 @@
+Added ruff linting (ruff check) to Makefile format target with E, F, and I rule sets.

docs/book/programs/contrib/ubi-center/carbon-tax.ipynb

@@ -980,8 +980,8 @@
     }
    ],
    "source": [
-    "import plotly.express as px\n",
     "import pandas as pd\n",
+    "import plotly.express as px\n",
     "\n",
     "df = pd.DataFrame(\n",
     "    {\n",

docs/book/programs/gov/dcms/bbc/tv-licence.ipynb

@@ -121,6 +121,7 @@
    ],
    "source": [
     "import pandas as pd\n",
+    "\n",
     "from policyengine_uk import CountryTaxBenefitSystem\n",
     "\n",
     "system = CountryTaxBenefitSystem()\n",

docs/book/programs/gov/hmrc/child-benefit.ipynb

@@ -152,9 +152,10 @@
     }
    ],
    "source": [
-    "from policyengine_uk import CountryTaxBenefitSystem\n",
     "import pandas as pd\n",
     "\n",
+    "from policyengine_uk import CountryTaxBenefitSystem\n",
+    "\n",
     "parameters = CountryTaxBenefitSystem().parameters\n",
     "data = {\n",
     "    \"Date\": [],\n",

docs/book/programs/gov/hmrc/fuel-duty.ipynb

@@ -116,9 +116,10 @@
     }
    ],
    "source": [
-    "from policyengine_uk import CountryTaxBenefitSystem\n",
-    "import plotly.express as px\n",
     "import pandas as pd\n",
+    "import plotly.express as px\n",
+    "\n",
+    "from policyengine_uk import CountryTaxBenefitSystem\n",
     "\n",
     "system = CountryTaxBenefitSystem()\n",
     "hmrc = system.parameters.gov.hmrc\n",
@@ -1053,8 +1054,6 @@
     }
    ],
    "source": [
-    "import plotly.express as px\n",
-    "\n",
     "px.line(\n",
     "    df,\n",
     "    x=\"Date of change\",\n",

docs/book/programs/gov/hmrc/income-tax.ipynb

@@ -204,6 +204,7 @@
    ],
    "source": [
     "import pandas as pd\n",
+    "\n",
     "from policyengine_uk import Simulation\n",
     "\n",
     "\n",
@@ -515,9 +516,10 @@
     }
    ],
    "source": [
-    "from policyengine_uk.system import system\n",
     "import pandas as pd\n",
     "\n",
+    "from policyengine_uk.system import system\n",
+    "\n",
     "default = system.parameters.gov.hmrc.income_tax.allowances.annual_allowance.default\n",
     "minimum = system.parameters.gov.hmrc.income_tax.allowances.annual_allowance.minimum\n",
     "reduction_rate = (\n",
@@ -5635,8 +5637,6 @@
     }
    ],
    "source": [
-    "from policyengine_uk import Simulation\n",
-    "\n",
     "simulation = Simulation(\n",
     "    situation=dict(\n",
     "        people=dict(\n",
@@ -5658,8 +5658,8 @@
     "    ),\n",
     ")\n",
     "\n",
-    "import plotly.express as px\n",
     "import pandas as pd\n",
+    "import plotly.express as px\n",
     "from policyengine_core.charts import format_fig\n",
     "\n",
     "df = pd.DataFrame(\n",

docs/book/programs/gov/hmrc/national-insurance.ipynb

@@ -133,8 +133,6 @@
    "source": [
     "# @title\n",
     "import pandas as pd\n",
-    "from tabulate import tabulate\n",
-    "\n",
     "\n",
     "data = {\n",
     "    \"Class\": [\"Class 1\", \"Class 2\", \"Class 4\"],\n",
@@ -1433,11 +1431,12 @@
     }
    ],
    "source": [
-    "from policyengine_uk.system import system\n",
     "import plotly.express as px\n",
     "from policyengine_core.charts import format_fig\n",
     "from policyengine_core.parameters import Parameter\n",
     "\n",
+    "from policyengine_uk.system import system\n",
+    "\n",
     "ni = system.parameters.gov.hmrc.national_insurance\n",
     "\n",
     "threshold_parameters = [\n",

docs/book/programs/gov/hmrc/stamp-duty.ipynb

@@ -7298,9 +7298,10 @@
     }
    ],
    "source": [
-    "from policyengine_uk.system import system\n",
     "from policyengine_core.charts import format_fig\n",
     "\n",
+    "from policyengine_uk.system import system\n",
+    "\n",
     "sdlt = system.parameters.gov.hmrc.stamp_duty.statistics\n",
     "stats = {\"Year\": [], \"Revenue (£m)\": [], \"Type\": []}\n",
     "# residential corporate\n",

docs/book/programs/gov/ofgem/energy-price-guarantee.ipynb

@@ -1002,9 +1002,10 @@
     }
    ],
    "source": [
-    "from policyengine_uk import CountryTaxBenefitSystem\n",
-    "import plotly.express as px\n",
     "import pandas as pd\n",
+    "import plotly.express as px\n",
+    "\n",
+    "from policyengine_uk import CountryTaxBenefitSystem\n",
     "\n",
     "system = CountryTaxBenefitSystem()\n",
     "ofgem = system.parameters.gov.ofgem\n",

docs/book/programs/gov/revenue_scotland/land-and-buildings-transaction-tax.ipynb

@@ -1171,6 +1171,7 @@
     "import pandas as pd\n",
     "import plotly.express as px\n",
     "from policyengine_core.charts import format_fig\n",
+    "\n",
     "from policyengine_uk import CountryTaxBenefitSystem\n",
     "\n",
     "system = CountryTaxBenefitSystem()\n",

docs/book/programs/gov/wra/land-transaction-tax.ipynb

@@ -1114,6 +1114,7 @@
     "import pandas as pd\n",
     "import plotly.express as px\n",
     "from policyengine_core.charts import format_fig\n",
+    "\n",
     "from policyengine_uk import CountryTaxBenefitSystem\n",
     "\n",
     "system = CountryTaxBenefitSystem()\n",

docs/book/validation/student-loan-repayments.ipynb

@@ -32,9 +32,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from policyengine_uk import Microsimulation\n",
     "import numpy as np\n",
-    "import pandas as pd\n",
+    "\n",
+    "from policyengine_uk import Microsimulation\n",
     "\n",
     "sim = Microsimulation()\n",
     "year = 2025"

docs/book/validation/validation.ipynb

@@ -1891,10 +1891,10 @@
     "    ]\n",
     "\n",
     "\n",
+    "from policyengine_core.parameters import get_parameter\n",
     "from policyengine_uk.data.datasets.frs.calibration.loss import (\n",
     "    calibration_parameters,\n",
     ")\n",
-    "from policyengine_core.parameters import get_parameter\n",
     "\n",
     "\n",
     "def official_estimate(parameter: str):\n",
@@ -2008,7 +2008,7 @@
     "                )\n",
     "\n",
     "import plotly.express as px\n",
-    "from policyengine_core.charts import format_fig, BLUE_COLOUR_SCALE, GRAY\n",
+    "from policyengine_core.charts import BLUE_COLOUR_SCALE, GRAY, format_fig\n",
     "\n",
     "fig = (\n",
     "    px.bar(\n",

policyengine_uk/__init__.py

@@ -7,13 +7,14 @@
 
 from policyengine_uk import entities
 from policyengine_uk.system import (
+    COUNTRY_DIR,
     CountryTaxBenefitSystem,
     Microsimulation,
     Simulation,
-    COUNTRY_DIR,
     parameters,
     variables,
 )
+
 from .model_api import *
 
 REPO = Path(__file__).parent

policyengine_uk/data/__init__.py

@@ -2,4 +2,5 @@
     UKMultiYearDataset,
     UKSingleYearDataset,
 )
+
 from .filter_dataset import filter_dataset

policyengine_uk/data/dataset_schema.py

@@ -1,11 +1,13 @@
-import pandas as pd
-import numpy as np
 from typing import TYPE_CHECKING
 
+import numpy as np
+import pandas as pd
+
 if TYPE_CHECKING:
     from policyengine_uk import Microsimulation
 
 from pathlib import Path
+
 import h5py
 
 

policyengine_uk/data/economic_assumptions.py

@@ -1,10 +1,11 @@
-from policyengine_uk.data import UKMultiYearDataset, UKSingleYearDataset
+import logging
+from pathlib import Path
 
+import numpy as np
 import yaml
 from policyengine_core.parameters import ParameterNode
-from pathlib import Path
-import numpy as np
-import logging
+
+from policyengine_uk.data import UKMultiYearDataset, UKSingleYearDataset
 
 # Base year for the FRS dataset - used to calculate age offsets
 _FRS_BASE_YEAR = 2023  # FRS 2023-24 represents calendar year 2024
@@ -55,7 +56,6 @@ def apply_uprating(
     dataset: UKMultiYearDataset,
     tax_benefit_system_parameters: ParameterNode = None,
 ):
-    from policyengine_uk.system import system
 
     # Apply uprating to the dataset.
     dataset = dataset.copy()

policyengine_uk/data/filter_dataset.py

@@ -8,7 +8,6 @@
 def filter_dataset(
     sim: "Microsimulation", household_id: int, year: int = 2026
 ) -> "UKSingleYearDataset":
-    from policyengine_uk import Microsimulation
     from policyengine_uk.data import UKSingleYearDataset
 
     """

policyengine_uk/dynamics/labour_supply.py

@@ -8,22 +8,21 @@
 Reference: https://obr.uk/docs/dlm_uploads/NICS-Cut-Impact-on-Labour-Supply-Note.pdf
 """
 
+from typing import Optional
+
 import numpy as np
 import pandas as pd
-from policyengine_uk import Simulation
 from microdf import MicroDataFrame
 from pydantic import BaseModel
-from typing import Optional
+
+from policyengine_uk import Simulation
 
 from .progression import (
     calculate_derivative_change,
-    calculate_relative_income_change,
-    calculate_labour_substitution_elasticities,
-    calculate_labour_net_income_elasticities,
     calculate_employment_income_change,
-)
-from .participation import (
-    apply_participation_responses,
+    calculate_labour_net_income_elasticities,
+    calculate_labour_substitution_elasticities,
+    calculate_relative_income_change,
 )
 
 

policyengine_uk/dynamics/participation.py

@@ -9,8 +9,8 @@
 
 import numpy as np
 import pandas as pd
+
 from policyengine_uk import Simulation
-import warnings
 
 
 def calculate_participation_elasticities(

policyengine_uk/dynamics/progression.py

@@ -9,6 +9,7 @@
 
 import numpy as np
 import pandas as pd
+
 from policyengine_uk import Simulation
 
 

policyengine_uk/model_api.py

@@ -1,7 +1,5 @@
 from policyengine_core.model_api import *
+
 from policyengine_uk.entities import *
-from policyengine_core import periods
-from microdf import MicroSeries, MicroDataFrame
-from policyengine_uk.utils.scenario import Scenario
 
 GBP = "currency-GBP"

policyengine_uk/parameters/gov/contrib/create_private_pension_uprating.py

@@ -1,6 +1,6 @@
 from policyengine_core.parameters import (
-    ParameterNode,
     Parameter,
+    ParameterNode,
 )
 
 YEARS = list(range(2020, 2035))

policyengine_uk/parameters/gov/dwp/LHA/__init__.py

@@ -1,4 +1,5 @@
-import pandas as pd
 from pathlib import Path
 
+import pandas as pd
+
 lha_list_of_rents = pd.read_csv(Path(__file__).parent / "lha_list_of_rents.csv.gz")

policyengine_uk/parameters/gov/dwp/state_pension/triple_lock/create_triple_lock.py

@@ -1,7 +1,6 @@
 from policyengine_core.parameters import (
-    ParameterNode,
     Parameter,
-    get_parameter,
+    ParameterNode,
 )
 
 YEARS = list(range(2022, 2035))

policyengine_uk/parameters/gov/economic_assumptions/create_economic_assumption_indices.py

@@ -1,7 +1,6 @@
 from policyengine_core.parameters import (
-    ParameterNode,
     Parameter,
-    get_parameter,
+    ParameterNode,
 )
 
 

policyengine_uk/parameters/gov/hmrc/fuel_duty/calculate_fuel_duty_rates.py

@@ -12,8 +12,8 @@
 
 import argparse
 import re
-from datetime import date
 from calendar import isleap
+from datetime import date
 from pathlib import Path
 
 import yaml

policyengine_uk/reforms/cps/marriage_tax_reforms.py

@@ -1,5 +1,6 @@
+from typing import Optional
+
 from policyengine_uk.model_api import *
-from typing import Union, Optional
 
 
 def create_expanded_ma_reform(