Restructure to steps

cds.py

@@ -1,66 +0,0 @@
-"""Download ERA5 data from the Copernicus Data Store.
-
-Web platform: https://cds.climate.copernicus.eu
-"""
-
-import os
-import re
-from pathlib import Path
-
-import cdsapi
-import cyclopts
-from rich import pretty, print, traceback
-
-traceback.install()
-pretty.install()
-
-DATA_DIR = Path(os.environ.get("DATA_DIR", "data")) / "entropyc-rts"
-
-
-def hourly(years: str):
-    """Download ERA5 data from the Copernicus Data Store.
-
-    Args:
-        years (str): Years to download, seperated by a '-'.
-
-    """
-    assert re.compile(r"^\d{4}-\d{4}$").match(years), "Years must be in the format 'YYYY-YYYY'"
-    start_year, end_year = map(int, years.split("-"))
-    assert 1950 <= start_year <= end_year <= 2024, "Years must be between 1950 and 2024"
-
-    dataset = "reanalysis-era5-single-levels"
-    client = cdsapi.Client(wait_until_complete=False)
-
-    outdir = (DATA_DIR / "era5/cds").resolve()
-    outdir.mkdir(parents=True, exist_ok=True)
-
-    print(f"Downloading ERA5 data from {start_year} to {end_year}...")
-    for y in range(start_year, end_year + 1):
-        for month in [f"{i:02d}" for i in range(1, 13)]:
-            request = {
-                "product_type": ["reanalysis"],
-                "variable": [
-                    "2m_temperature",
-                    "total_precipitation",
-                    "snow_depth",
-                    "snow_density",
-                    "snowfall",
-                    "lake_ice_temperature",
-                    "surface_sensible_heat_flux",
-                ],
-                "year": [str(y)],
-                "month": [month],
-                "day": [f"{i:02d}" for i in range(1, 32)],
-                "time": [f"{i:02d}:00" for i in range(0, 24)],
-                "data_format": "netcdf",
-                "download_format": "unarchived",
-                "area": [85, -180, 50, 180],
-            }
-
-            outpath = outdir / f"era5_{y}_{month}.zip"
-            client.retrieve(dataset, request).download(str(outpath))
-            print(f"Downloaded {dataset} for {y}-{month}")
-
-
-if __name__ == "__main__":
-    cyclopts.run(hourly)