add: Subclass for archiving query results as zipfiles

toargridding/toar_rest_client.py

@@ -4,6 +4,7 @@ from zipfile import ZipFile
 from dataclasses import dataclass, asdict
 from contextlib import contextmanager
 import json
+from pathlib import Path
 
 import requests
 import pandas as pd
@@ -180,3 +181,32 @@ class AnalysisService:
         with zip_file.open(f"{data_file}.csv") as f:
             s_stream = io.StringIO(f.read().decode("utf-8"))
             return pd.read_csv(s_stream, comment="#", index_col=0)
+
+
+class AnalysisServiceDownload(AnalysisService):
+    def __init__(
+        self, status_endpoint, cache_dir, sample_dir: Path, use_downloaded=True
+    ):
+        super().__init__(status_endpoint, cache_dir)
+        self.sample_dir = sample_dir
+        self.use_downloaded = use_downloaded
+
+    def get_timeseries_and_metadata(self, metadata: Metadata):
+        filename = self.sample_dir / self.get_sample_file_name(metadata)
+        query_options = QueryOptions.from_metadata(metadata)
+        needs_fresh_download = (not self.use_downloaded) or (not filename.is_file())
+
+        if needs_fresh_download:
+            content = self.connection.get(query_options)
+            with open(filename, "w+b") as downloaded_file:
+                downloaded_file.write()
+
+        with open(filename, "r+b") as data_file:
+            content = data_file.read()
+
+        timeseries, timeseries_metadata = self.load_data(content, metadata)
+        return timeseries, timeseries_metadata
+
+    @staticmethod
+    def get_sample_file_name(metadata: Metadata):
+        return f"data/{metadata.statistic}_{metadata.time.sampling}_{metadata.time.start.date()}_{metadata.time.end.date()}.zip"