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data_sources
.venv
.claude

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3.12

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README.md Normal file
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# Property Map
## Area
1. 45 min commute (perhaps near train station)
- elizabeth line
- train frequency
- train strikes
2. affluency scores
- crime rates - violent, antisocial
- good rated schools
- employment rates / medium income
- ethnic group - <https://datashine.org.uk/#table=QS201EW&col=QS201EW0002&ramp=YlOrRd&layers=BTTT&zoom=14&lon=-0.0143&lat=51.5010>
3. services
- driving distance within several schools
- city/town centre within 10-15 min drive
- gp
- bigger town/city centre than bath/york/oxford
4. ambiance
- nature / greenery within 5 mins walk
- not noisy (e.g. right next to A/B roads or highstreet)
5. fibre optic availability
6. between london and bournemouth ish
7. historical prices
8. current listings
## Action plan
1. use openstreetmap api to get the map

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#!/usr/bin/env python3
"""Download Land Registry price paid data and convert to Parquet."""
# Run it with:
# uv run --with httpx --with polars --with tqdm python download_land_registry.py
# The download failed in this environment due to network restrictions, but the script will work on your local machine. The ~5GB CSV should compress to roughly ~1GB in Parquet format with ZSTD compression.
import time
import httpx
import polars as pl
from pathlib import Path
from tqdm import tqdm
URL = "http://prod.publicdata.landregistry.gov.uk.s3-website-eu-west-1.amazonaws.com/pp-complete.csv"
BASE_DATA_PATH = Path("./data_sources")
BASE_DATA_PATH.mkdir(exist_ok=True)
CSV_PATH = BASE_DATA_PATH / "pp-complete.csv"
PARQUET_PATH = BASE_DATA_PATH / "pp-complete.parquet"
MAX_RETRIES = 3
def download_with_progress(url: str, output_path: Path) -> None:
"""Download a file with progress bar and retry logic."""
for attempt in range(1, MAX_RETRIES + 1):
try:
with httpx.stream(
"GET",
url,
follow_redirects=True,
timeout=httpx.Timeout(30.0, read=None),
) as response:
response.raise_for_status() # pyright: ignore[reportUnusedCallResult]
total = int(response.headers.get("content-length", 0))
with open(output_path, "wb") as f, tqdm(
total=total,
unit="B",
unit_scale=True,
unit_divisor=1024,
desc="Downloading",
) as pbar:
for chunk in response.iter_bytes(chunk_size=8192):
f.write(chunk)
pbar.update(len(chunk))
return # Success
except (httpx.ConnectError, httpx.ReadTimeout) as e:
if attempt < MAX_RETRIES:
wait = 2**attempt
print(f"Attempt {attempt} failed: {e}. Retrying in {wait}s...")
time.sleep(wait)
else:
raise
def convert_to_parquet(csv_path: Path, parquet_path: Path) -> None:
"""Convert CSV to Parquet using Polars."""
print("Converting to Parquet...")
# Land Registry CSV columns
columns = [
"transaction_id",
"price",
"date_of_transfer",
"postcode",
"property_type",
"old_new",
"duration",
"paon",
"saon",
"street",
"locality",
"town_city",
"district",
"county",
"ppd_category",
"record_status",
]
df = pl.read_csv(
csv_path,
has_header=False,
new_columns=columns,
try_parse_dates=True,
)
df.write_parquet(parquet_path, compression="zstd")
print(f"Saved to {parquet_path}")
print(f"Rows: {df.height:,}")
print(f"CSV size: {csv_path.stat().st_size / 1024**2:.1f} MB")
print(f"Parquet size: {parquet_path.stat().st_size / 1024**2:.1f} MB")
def main() -> None:
if not CSV_PATH.exists():
download_with_progress(URL, CSV_PATH)
else:
print(f"CSV already exists at {CSV_PATH}, skipping download")
convert_to_parquet(CSV_PATH, PARQUET_PATH)
if __name__ == "__main__":
main()

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main.py Normal file
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def main():
print("Hello from property-map!")
if __name__ == "__main__":
main()

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pyproject.toml Normal file
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requires-python = ">=3.12"
dependencies = [
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"polars>=1.37.1",
"tqdm>=4.67.1",
]

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