Get manifest (#33)

pyproject.toml

@@ -24,10 +24,9 @@ classifiers = [
 	"Intended Audience :: Science/Research",
 	"Topic :: Scientific/Engineering",
 ]
-requires-python = ">=3.7"
+requires-python = ">=3.10"
 dependencies = [
 	"backoff>=2,<3",
-	"dask[dataframe]",
 	"geopandas<1",
 	"h5py",
 	"httpx",

src/blackmarble/__init__.py

@@ -1,7 +1,5 @@
-from pathlib import Path
 import logging
-
-# from .base import BlackMarbleDownloader  # noqa: F401
+from pathlib import Path
 
 __version__ = (Path(__file__).parent / "VERSION").read_text().strip()
 
@@ -12,4 +10,4 @@
 
 logger: logging.Logger = logging.getLogger(__name__)
 
-logger.setLevel(logging.DEBUG)
+logger.setLevel(logging.WARN)

src/blackmarble/download.py

@@ -1,22 +1,44 @@
+import asyncio
 import datetime
+import json
 from dataclasses import dataclass
 from importlib.resources import files
 from pathlib import Path
 from typing import ClassVar, List
 
 import backoff
-import dask.dataframe as dd
 import geopandas
 import httpx
+import nest_asyncio
 import pandas as pd
 from httpx import HTTPError
 from pqdm.threads import pqdm
 from pydantic import BaseModel
 from tqdm.auto import tqdm
-
 from .types import Product
 
 
+def chunks(ls, n):
+    """Yield successive n-sized chunks from list."""
+    for i in range(0, len(ls), n):
+        yield ls[i : i + n]
+
+
+@backoff.on_exception(
+    backoff.expo,
+    HTTPError,
+)
+async def get_url(client, url, params):
+    """
+
+    Returns
+    -------
+    httpx.Response
+        HTTP response
+    """
+    return await client.get(url, params=params)
+
+
 @dataclass
 class BlackMarbleDownloader(BaseModel):
     """A downloader to retrieve `NASA Black Marble <https://blackmarble.gsfc.nasa.gov>`_ data.
@@ -36,13 +58,15 @@ class BlackMarbleDownloader(BaseModel):
     TILES: ClassVar[geopandas.GeoDataFrame] = geopandas.read_file(
         files("blackmarble.data").joinpath("blackmarbletiles.geojson")
     )
-    URL: ClassVar[str] = "https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/5000"
+    URL: ClassVar[str] = "https://ladsweb.modaps.eosdis.nasa.gov"
 
     def __init__(self, bearer: str, directory: Path):
+        nest_asyncio.apply()
         super().__init__(bearer=bearer, directory=directory)
 
-    def _retrieve_manifest(
+    async def get_manifest(
         self,
+        gdf: geopandas.GeoDataFrame,
         product_id: Product,
         date_range: datetime.date | List[datetime.date],
     ) -> pd.DataFrame:
@@ -66,20 +90,42 @@ def _retrieve_manifest(
         if isinstance(product_id, str):
             product_id = Product(product_id)
 
-        urlpaths = set()
-        for date in date_range:
-            match product_id:
-                case Product.VNP46A3:  # if VNP46A3 then first day of the month
-                    tm_yday = date.replace(day=1).timetuple().tm_yday
-                case Product.VNP46A4:  # if VNP46A4 then first day of the year
-                    tm_yday = date.replace(month=1, day=1).timetuple().tm_yday
-                case _:
-                    tm_yday = date.timetuple().tm_yday
-
-            urlpath = f"{self.URL}/{product_id.value}/{date.year}/{tm_yday}.csv"
-            urlpaths.add(urlpath)
+        # Create bounding box
+        gdf = pd.concat([gdf, gdf.bounds], axis="columns").round(2)
+        gdf["bbox"] = gdf.round(2).apply(
+            lambda row: f"x{row.minx}y{row.miny},x{row.maxx}y{row.maxy}", axis=1
+        )
 
-        return dd.read_csv(list(urlpaths)).compute()
+        async with httpx.AsyncClient(verify=False) as client:
+            tasks = []
+            for chunk in chunks(date_range, 250):
+                for _, row in gdf.iterrows():
+                    url = f"{self.URL}/api/v1/files"
+                    params = {
+                        "product": product_id.value,
+                        "collection": "5000",
+                        "dateRanges": f"{min(chunk)}..{max(chunk)}",
+                        "areaOfInterest": row["bbox"],
+                    }
+                    tasks.append(asyncio.ensure_future(get_url(client, url, params)))
+
+            responses = [
+                await f
+                for f in tqdm(
+                    asyncio.as_completed(tasks),
+                    total=len(tasks),
+                    desc="GETTING MANIFEST...",
+                )
+            ]
+
+            rs = []
+            for r in responses:
+                try:
+                    rs.append(pd.DataFrame(r.json()).T)
+                except json.decoder.JSONDecodeError:
+                    continue
+
+            return pd.concat(rs)
 
     @backoff.on_exception(
         backoff.expo,
@@ -101,19 +147,14 @@ def _download_file(
         filename: pathlib.Path
             Filename of downloaded data file
         """
-        year = name[9:13]
-        day = name[13:16]
-        product_id = name[0:7]
-
-        url = f"{self.URL}/{product_id}/{year}/{day}/{name}"
-        headers = {"Authorization": f"Bearer {self.bearer}"}
-        filename = Path(self.directory, name)
+        url = f"{self.URL}{name}"
+        name = name.split("/")[-1]
 
-        with open(filename, "wb+") as f:
+        with open(filename := Path(self.directory, name), "wb+") as f:
             with httpx.stream(
                 "GET",
                 url,
-                headers=headers,
+                headers={"Authorization": f"Bearer {self.bearer}"},
             ) as response:
                 total = int(response.headers["Content-Length"])
                 with tqdm(
@@ -129,29 +170,11 @@ def _download_file(
 
                 return filename
 
-    def _download(self, names: List[str], n_jobs: int = 16):
-        """Download (in parallel) from NASA Black Marble archive
-
-        Parameters
-        ----------
-        names: List[str]
-            List of names for which to download from the NASA Black Marble archive
-        """
-        args = [(name,) for name in names]
-
-        return pqdm(
-            args,
-            self._download_file,
-            n_jobs=n_jobs,
-            argument_type="args",
-            desc="Downloading...",
-        )
-
     def download(
         self,
         gdf: geopandas.GeoDataFrame,
         product_id: Product,
-        date_range: datetime.date | List[datetime.date],
+        date_range: List[datetime.date],
         skip_if_exists: bool = True,
     ):
         """Download (in parallel) from NASA Black Marble archive
@@ -164,16 +187,27 @@ def download(
         product: Product
             Nasa Black Marble Product Id (e.g, VNP46A1)
 
+        date_range: List[datetime.date]
+            Date range for which to download NASA Black Marble data.
+
         skip_if_exists: bool, default=True
-            Whether to skip downloading or extracting data if the data file for that date already exists
+            Whether to skip downloading data if file already exists
         """
         gdf = geopandas.overlay(
             gdf.to_crs("EPSG:4326").dissolve(), self.TILES, how="intersection"
         )
-        bm_files_df = self._retrieve_manifest(product_id, date_range)
+
+        bm_files_df = asyncio.run(self.get_manifest(gdf, product_id, date_range))
         bm_files_df = bm_files_df[
             bm_files_df["name"].str.contains("|".join(gdf["TileID"]))
         ]
-        names = bm_files_df["name"].tolist()
+        names = bm_files_df["fileURL"].tolist()
 
-        return self._download(names)
+        args = [(name,) for name in names]
+        return pqdm(
+            args,
+            self._download_file,
+            n_jobs=16,
+            argument_type="args",
+            desc="Downloading...",
+        )

src/blackmarble/raster.py

@@ -20,7 +20,6 @@
 from .download import BlackMarbleDownloader
 from .types import Product
 
-
 VARIABLE_DEFAULT = {
     Product.VNP46A1: "DNB_At_Sensor_Radiance_500m",
     Product.VNP46A2: "Gap_Filled_DNB_BRDF-Corrected_NTL",
@@ -56,9 +55,9 @@ def h5_to_geotiff(
     Returns
     ------
     output_path: Path
-        Path to which GeoTIFF
+        Path to which export GeoTIFF file
     """
-    output_path = Path(output_directory, f"{output_prefix}{f.stem}").with_suffix(".tif")
+    output_path = Path(output_directory, f.name).with_suffix(".tif")
     product_id = Product(f.stem.split(".")[0])
 
     if variable is None:
@@ -277,24 +276,29 @@ def bm_raster(
         for date in tqdm(date_range, desc="COLLATING RESULTS | Processing..."):
             filenames = _pivot_paths_by_date(pathnames).get(date)
 
-            # Open each GeoTIFF file as a DataArray and store in a list
-            da = [
-                rioxarray.open_rasterio(
-                    h5_to_geotiff(
-                        f,
-                        variable=variable,
-                        quality_flag_rm=quality_flag_rm,
-                        output_prefix=file_prefix,
-                        output_directory=d,
+            try:
+                # Open each GeoTIFF file as a DataArray and store in a list
+                da = [
+                    rioxarray.open_rasterio(
+                        h5_to_geotiff(
+                            f,
+                            variable=variable,
+                            quality_flag_rm=quality_flag_rm,
+                            output_prefix=file_prefix,
+                            output_directory=d,
+                        ),
                     )
-                )
-                for f in filenames
-            ]
-            ds = merge_arrays(da)
-            ds = ds.rio.clip(gdf.geometry.apply(mapping), gdf.crs, drop=True)
-            ds["time"] = pd.to_datetime(date)
+                    for f in filenames
+                ]
+                ds = merge_arrays(da)
+                ds = ds.rio.clip(gdf.geometry.apply(mapping), gdf.crs, drop=True)
+                ds["time"] = pd.to_datetime(date)
+
+                dx.append(ds.squeeze())
+            except TypeError:
+                continue
 
-            dx.append(ds.squeeze())
+        dx = filter(lambda item: item is not None, dx)
 
         # Stack the individual dates along "time" dimension
         ds = (

src/blackmarble/types.py

@@ -1,7 +1,6 @@
-from datetime import date
-from enum import Enum
+"""Types for blackmarblepy"""
 
-from pydantic import BaseModel, validator
+from enum import Enum
 
 
 class Product(Enum):
@@ -11,20 +10,3 @@ class Product(Enum):
     VNP46A2 = "VNP46A2"
     VNP46A3 = "VNP46A3"
     VNP46A4 = "VNP46A4"
-
-
-class DateRange(BaseModel):
-    start_date: date
-    end_date: date
-
-    @validator("start_date", "end_date", pre=True)
-    def parse_dates(cls, v):
-        if isinstance(v, str):
-            return date.fromisoformat(v)
-        return v
-
-    @validator("end_date")
-    def check_date_range(cls, v, values, **kwargs):
-        if "start_date" in values and v < values["start_date"]:
-            raise ValueError("End date cannot be before start date")
-        return v