Move pipelines

pipeline/download/arcgis.py

@@ -0,0 +1,71 @@
+import zipfile
+import httpx
+import polars as pl
+from pathlib import Path
+from tqdm import tqdm
+
+URL = "https://www.arcgis.com/sharing/rest/content/items/077631e063eb4e1ab43575d01381ec33/data"
+
+BASE_DATA_PATH = Path("./data_sources")
+BASE_DATA_PATH.mkdir(exist_ok=True)
+DOWNLOAD_PATH = BASE_DATA_PATH / "arcgis_data.zip"
+EXTRACT_PATH = BASE_DATA_PATH / "arcgis_extracted"
+PARQUET_PATH = BASE_DATA_PATH / "arcgis_data.parquet"
+
+
+def download_with_progress(url: str, output_path: Path) -> None:
+    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 
+   
+
+
+def extract_zip(zip_path: Path, extract_path: Path) -> None:
+    extract_path.mkdir(exist_ok=True)
+
+    with zipfile.ZipFile(zip_path, "r") as zf:
+        zf.extractall(extract_path)
+
+
+def convert_to_parquet(data_path: Path, parquet_path: Path) -> None:
+    df = pl.scan_csv(data_path / 'Data/NSPL_MAY_2025_UK.csv', try_parse_dates=True)
+    print(f"Columns: {df.columns}")
+    df.sink_parquet(parquet_path, compression="zstd")
+    print(f"Saved to {parquet_path}")
+
+
+def main() -> None:
+    if PARQUET_PATH.exists():
+        print(f"Parquet already exists at {PARQUET_PATH}, skipping")
+        return
+
+    if not DOWNLOAD_PATH.exists():
+        download_with_progress(URL, DOWNLOAD_PATH)
+    else:
+        print(f"File already exists at {DOWNLOAD_PATH}, skipping download")
+
+    extract_zip(DOWNLOAD_PATH, EXTRACT_PATH)
+    convert_to_parquet(EXTRACT_PATH, PARQUET_PATH)
+
+if __name__ == "__main__":
+    main()

pipeline/download/deprivation_data.py

@@ -0,0 +1,58 @@
+import httpx
+import polars as pl
+from pathlib import Path
+
+URL = "https://assets.publishing.service.gov.uk/media/691ded34513046b952c500bd/File_5_IoD2025_Scores_for_the_Indices_of_Deprivation.xlsx"
+
+BASE_DATA_PATH = Path("./data_sources")
+BASE_DATA_PATH.mkdir(exist_ok=True)
+XLSX_PATH = BASE_DATA_PATH / "IoD2025_Scores.xlsx"
+PARQUET_PATH = BASE_DATA_PATH / "IoD2025_Scores.parquet"
+
+
+def download_file(url: str, output_path: Path) -> None:
+    with httpx.stream("GET", url, follow_redirects=True, timeout=60) as response:
+        response.raise_for_status()
+        total = int(response.headers.get("content-length", 0))
+        downloaded = 0
+        with open(output_path, "wb") as f:
+            for chunk in response.iter_bytes(chunk_size=8192):
+                f.write(chunk)
+                downloaded += len(chunk)
+                if total:
+                    print(
+                        f"\rDownloaded {downloaded / 1024 / 1024:.1f} MB / {total / 1024 / 1024:.1f} MB",
+                        end="",
+                    )
+    print(f"\nSaved to {output_path}")
+
+
+def convert_to_parquet(xlsx_path: Path, parquet_path: Path) -> None:
+    print("Reading Excel file (sheet 2)...")
+
+    # Read the 2nd sheet (index 1) - IoD2025 Scores
+    df = pl.read_excel(
+        xlsx_path,
+        sheet_id=2,  # 1-indexed, so 2 = second sheet
+    )
+
+    print(f"Shape: {df.shape}")
+    print(f"Columns: {df.columns}")
+
+    df.write_parquet(parquet_path, compression="zstd")
+    print(f"Saved to {parquet_path}")
+    print(f"Excel size: {xlsx_path.stat().st_size / 1024 / 1024:.1f} MB")
+    print(f"Parquet size: {parquet_path.stat().st_size / 1024 / 1024:.1f} MB")
+
+
+def main() -> None:
+    if not XLSX_PATH.exists():
+        download_file(URL, XLSX_PATH)
+    else:
+        print(f"Excel file already exists at {XLSX_PATH}, skipping download")
+
+    convert_to_parquet(XLSX_PATH, PARQUET_PATH)
+
+
+if __name__ == "__main__":
+    main()

pipeline/download/price_paid.py

@@ -0,0 +1,91 @@
+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 / "price-paid-complete.csv"
+PARQUET_PATH = BASE_DATA_PATH / "price-paid-complete.parquet"
+
+
+def download_with_progress(url: str, output_path: Path) -> None:
+    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
+
+      
+def convert_to_parquet(csv_path: Path, parquet_path: Path) -> None:
+    """Convert CSV to Parquet using Polars."""
+    print("Converting to Parquet...")
+
+    # https://www.gov.uk/guidance/about-the-price-paid-data
+    # 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:,}")
+
+
+def main() -> None:
+    if PARQUET_PATH.exists():
+        print(f"Parquet already exists at {PARQUET_PATH}, skipping")
+        return
+
+    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()