Update for some streaming things

gfs-reforecast.py

@@ -41,7 +41,7 @@ _LICENSE = "US Government data, Open license, no restrictions"
 # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
 _URLS = {
-    "GFSv16": "gfs_v16.json",
+    "gfs_v16": "gfs_v16.json",
     "raw": "raw.json",
     "analysis": "analysis.json",
 }
@@ -129,41 +129,53 @@ class GFEReforecastDataset(datasets.GeneratorBasedBuilder):
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         urls = _URLS[self.config.name]
-        #data_dir = dl_manager.download_and_extract(urls)
+        streaming = dl_manager.is_streaming
+        if streaming:
+            urls = dl_manager.download_and_extract(urls)
+        else:
+            with open(filepath, "r") as f:
+                filepaths = json.load(f)
+                data_dir = dl_manager.download_and_extract(filepaths)
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": urls,
+                    "filepath": urls if streaming else data_dir,
                     "split": "train",
+                    "streaming": streaming,
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": urls,
+                    "filepath": urls if streaming else data_dir,
                     "split": "test"
+                    "streaming": streaming,
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": urls,
+                    "filepath": urls if streaming else data_dir,
                     "split": "valid",
+                    "streaming": streaming
                 },
             ),
         ]
 
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, filepath, split):
+    def _generate_examples(self, filepath, split, streaming):
 
         # Load the list of files for the type of data
-        with open(filepath, "r") as f:
-            filepaths = json.load(f)
-            filepaths = ['zip:///::https://huggingface.co/datasets/openclimatefix/gfs-reforecast/resolve/main/' + f for f in filepaths]
+        if streaming:
+            with open(filepath, "r") as f:
+                filepaths = json.load(f)
+                filepaths = ['zip:///::https://huggingface.co/datasets/openclimatefix/gfs-reforecast/resolve/main/' + f for f in filepaths]
+        else:
+            filepaths = filepath
         if "v16" in self.config.name:
             idx = 0
             for f in filepaths: