Move pipelines

Taskfile.yml

@@ -12,9 +12,10 @@ tasks:
     deps:
       - install
     cmds:
-      - uv run python download_land_registry.py
-      - uv run python download_arcgis_data.py
-      - uv run python -m pipeline.pois
+      - uv run -m pipeline.download.arcgis
+      - uv run -m pipeline.download.pois
+      - uv run -m pipeline.download.deprivation_data
+      - uv run -m pipeline.download.price_paid
 
   pipeline:
     desc: Run data processing pipeline

download_arcgis_data.py

@@ -1,129 +0,0 @@
-#!/usr/bin/env python3
-"""Download ArcGIS data and convert to Parquet."""
-
-# Run it with:
-#   uv run download_arcgis_data.py
-
-import time
-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"
-
-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 extract_zip(zip_path: Path, extract_path: Path) -> list[Path]:
-    """Extract ZIP file and return list of extracted files."""
-    print("Extracting ZIP file...")
-    extract_path.mkdir(exist_ok=True)
-
-    with zipfile.ZipFile(zip_path, "r") as zf:
-        zf.extractall(extract_path)
-        return [extract_path / name for name in zf.namelist()]
-
-
-def find_data_file(extract_path: Path) -> Path:
-    """Find the main data file (CSV, XLSX, or similar) in extracted files."""
-    # Look for common data file extensions
-    for ext in ["*.csv", "*.xlsx", "*.xls", "*.json", "*.geojson"]:
-        files = list(extract_path.rglob(ext))
-        if files:
-            # Return the largest file if multiple found
-            return max(files, key=lambda f: f.stat().st_size)
-
-    raise FileNotFoundError(f"No data file found in {extract_path}")
-
-
-def convert_to_parquet(data_path: Path, parquet_path: Path) -> None:
-    """Convert data file to Parquet using Polars."""
-    print(f"Converting {data_path.name} to Parquet...")
-
-    suffix = data_path.suffix.lower()
-
-    if suffix == ".csv":
-        df = pl.read_csv(data_path, try_parse_dates=True)
-    elif suffix in [".xlsx", ".xls"]:
-        df = pl.read_excel(data_path)
-    elif suffix in [".json", ".geojson"]:
-        df = pl.read_json(data_path)
-    else:
-        raise ValueError(f"Unsupported file format: {suffix}")
-
-    df.write_parquet(parquet_path, compression="zstd")
-    print(f"Saved to {parquet_path}")
-    print(f"Rows: {df.height:,}")
-    print(f"Columns: {df.columns}")
-    print(f"Original size: {data_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 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")
-
-    # Check if it's a ZIP file
-    if zipfile.is_zipfile(DOWNLOAD_PATH):
-        extracted_files = extract_zip(DOWNLOAD_PATH, EXTRACT_PATH)
-        print(f"Extracted {len(extracted_files)} files")
-        data_file = find_data_file(EXTRACT_PATH)
-    else:
-        # Not a ZIP, treat as direct data file
-        data_file = DOWNLOAD_PATH
-
-    convert_to_parquet(data_file, PARQUET_PATH)
-
-
-if __name__ == "__main__":
-    main()

download_land_registry.py

@@ -1,114 +0,0 @@
-#!/usr/bin/env python3
-"""Download Land Registry price paid data and convert to Parquet."""
-
-# Run it with:
-#   uv run 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...")
-
-    # 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:,}")
-    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 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()

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

@@ -1,6 +1,3 @@
-#!/usr/bin/env python3
-"""Download IoD2025 Deprivation Scores and convert to Parquet."""
-
 import httpx
 import polars as pl
 from pathlib import Path
@@ -14,8 +11,6 @@ PARQUET_PATH = BASE_DATA_PATH / "IoD2025_Scores.parquet"
 
 
 def download_file(url: str, output_path: Path) -> None:
-    """Download file from URL."""
-    print(f"Downloading from {url}...")
     with httpx.stream("GET", url, follow_redirects=True, timeout=60) as response:
         response.raise_for_status()
         total = int(response.headers.get("content-length", 0))
@@ -33,7 +28,6 @@ def download_file(url: str, output_path: Path) -> None:
 
 
 def convert_to_parquet(xlsx_path: Path, parquet_path: Path) -> None:
-    """Convert Excel sheet 2 to Parquet."""
     print("Reading Excel file (sheet 2)...")
 
     # Read the 2nd sheet (index 1) - IoD2025 Scores

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()