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-rw-r--r--fnme/__init__.py0
-rw-r--r--fnme/cli.py60
-rw-r--r--fnme/constants.py12
-rw-r--r--fnme/data.py13
-rw-r--r--fnme/geo.py10
-rw-r--r--fnme/station.py60
6 files changed, 155 insertions, 0 deletions
diff --git a/fnme/__init__.py b/fnme/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/fnme/__init__.py
diff --git a/fnme/cli.py b/fnme/cli.py
new file mode 100644
index 0000000..d9ef508
--- /dev/null
+++ b/fnme/cli.py
@@ -0,0 +1,60 @@
+import argparse
+import sys
+from typing import Any, Dict, List
+
+from tabulate import tabulate
+
+from fnme.constants import SORT_KV
+from fnme.data import get_latest_data
+from fnme.geo import get_location
+from fnme.station import filter_df, sort_stations
+
+
+def parse_args() -> argparse.Namespace:
+ parser = argparse.ArgumentParser()
+ parser.add_argument("-a", "--address", type=str, required=True)
+ parser.add_argument("-r", "--radius", type=int, default=5)
+ parser.add_argument("-s", "--sort", type=str, default="e10", choices=SORT_KV.keys())
+ return parser.parse_args()
+
+
+def output_stations(stations: List[Dict[str, Any]]) -> None:
+ if not stations:
+ print("[*] No stations found.")
+ return
+ print(
+ tabulate(
+ stations,
+ headers={
+ "station_name": "Station Name",
+ "distance": "Distance (miles)",
+ "e5_price": "E5 (£/L)",
+ "e10_price": "E10 (£/L)",
+ "diesel_price": "B7S (£/L)",
+ },
+ floatfmt=".2f",
+ )
+ )
+
+
+def main():
+ args = parse_args()
+
+ try:
+ location = get_location(args.address)
+ except ValueError as e:
+ print(f"[*] {e}")
+ sys.exit(1)
+ df, last_modified = get_latest_data()
+
+ print(f"Last updated: {last_modified}")
+
+ df_filtered = filter_df(df, args, location)
+
+ sorted_stations_list = sort_stations(df_filtered, args.sort)
+
+ output_stations(sorted_stations_list)
+
+
+if __name__ == "__main__":
+ main()
diff --git a/fnme/constants.py b/fnme/constants.py
new file mode 100644
index 0000000..bb57cb8
--- /dev/null
+++ b/fnme/constants.py
@@ -0,0 +1,12 @@
+ENDPOINT = "https://www.fuel-finder.service.gov.uk/internal/v1.0.2/csv/get-latest-fuel-prices-csv"
+
+SORT_KV = {
+ "e10": "e10_price",
+ "e5": "e5_price",
+ "b7s": "diesel_price",
+ "distance": "distance",
+}
+
+HEADERS = {
+ "User-Agent": "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_4; en-US) AppleWebKit/533.45 (KHTML, like Gecko) Chrome/48.0.2094.221 Safari/602"
+}
diff --git a/fnme/data.py b/fnme/data.py
new file mode 100644
index 0000000..bdec6df
--- /dev/null
+++ b/fnme/data.py
@@ -0,0 +1,13 @@
+from io import StringIO
+from typing import Optional
+
+import pandas as pd
+import requests
+
+from fnme.constants import ENDPOINT, HEADERS
+
+
+def get_latest_data() -> tuple[pd.DataFrame, Optional[str]]:
+ response = requests.get(ENDPOINT, headers=HEADERS, timeout=10)
+ response.raise_for_status()
+ return pd.read_csv(StringIO(response.text)), response.headers.get("Last-Modified")
diff --git a/fnme/geo.py b/fnme/geo.py
new file mode 100644
index 0000000..dba68fe
--- /dev/null
+++ b/fnme/geo.py
@@ -0,0 +1,10 @@
+from geopy.geocoders import Nominatim
+from geopy.location import Location
+
+
+def get_location(address: str) -> tuple[float, float]:
+ geolocator = Nominatim(user_agent="FuelNearMe")
+ result = geolocator.geocode(address)
+ if not isinstance(result, Location):
+ raise ValueError(f"Failed to get location from address: '{address}'")
+ return (result.latitude, result.longitude)
diff --git a/fnme/station.py b/fnme/station.py
new file mode 100644
index 0000000..c971173
--- /dev/null
+++ b/fnme/station.py
@@ -0,0 +1,60 @@
+import argparse
+import math
+from typing import Any, Dict, List, Tuple
+
+import numpy as np
+import pandas as pd
+
+from fnme.constants import SORT_KV
+
+
+def filter_df(
+ dframe: pd.DataFrame, arguments: argparse.Namespace, loc: Tuple[float, float]
+) -> List[Dict[str, Any]]:
+
+ def bounding_box() -> pd.DataFrame:
+ lat, lon = loc
+ deg_lat = arguments.radius / 69.0
+ deg_lon = arguments.radius / (69.0 * math.cos(math.radians(lat)))
+ return dframe[
+ dframe["forecourts.location.latitude"].between(lat - deg_lat, lat + deg_lat)
+ & dframe["forecourts.location.longitude"].between(
+ lon - deg_lon, lon + deg_lon
+ )
+ ]
+
+ def haversine_miles(lat2: np.ndarray, lon2: np.ndarray) -> np.ndarray:
+ R = 3958.8
+ lat1, lon1 = np.radians(loc[0]), np.radians(loc[1])
+ lat2, lon2 = np.radians(lat2), np.radians(lon2)
+ dlat = lat2 - lat1
+ dlon = lon2 - lon1
+ a = np.sin(dlat / 2) ** 2 + np.cos(lat1) * np.cos(lat2) * np.sin(dlon / 2) ** 2
+ return R * 2 * np.arcsin(np.sqrt(a))
+
+ def pence_to_pounds(col: pd.Series) -> pd.Series:
+ return (col / 100).round(2).where(col.notna(), other="N/A")
+
+ df = bounding_box().copy()
+
+ df["distance"] = haversine_miles(
+ df["forecourts.location.latitude"].to_numpy(),
+ df["forecourts.location.longitude"].to_numpy(),
+ ).round(1)
+
+ df = df[df["distance"] < arguments.radius]
+
+ df = df.assign(
+ e5_price=pence_to_pounds(df["forecourts.fuel_price.E5"]),
+ e10_price=pence_to_pounds(df["forecourts.fuel_price.E10"]),
+ diesel_price=pence_to_pounds(df["forecourts.fuel_price.B7S"]),
+ )
+
+ return df.rename(columns={"forecourts.trading_name": "station_name"})[
+ ["station_name", "distance", "e5_price", "e10_price", "diesel_price"]
+ ].to_dict(orient="records")
+
+
+def sort_stations(stations: list[dict], sort: str) -> list[dict]:
+ sort_key = SORT_KV[sort]
+ return sorted(stations, key=lambda d: d[sort_key] if d[sort_key] != "N/A" else 999)
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