Fix TOO MANY REQUESTS error

ask_a_patient.py

@@ -13,20 +13,16 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import glob
 import os
-import re
 
 import datasets
 
-from .bigbiohub import kb_features
-from .bigbiohub import BigBioConfig
-from .bigbiohub import Tasks
+from .bigbiohub import BigBioConfig, Tasks, kb_features
 
 _DATASETNAME = "ask_a_patient"
 _DISPLAYNAME = "AskAPatient"
 
-_LANGUAGES = ['English']
+_LANGUAGES = ["English"]
 _PUBMED = True
 _LOCAL = False
 _CITATION = """
@@ -52,7 +48,7 @@ mapped to how they are formally written in medical ontologies (SNOMED-CT and AMT
 
 _HOMEPAGE = "https://zenodo.org/record/55013"
 
-_LICENSE = 'Creative Commons Attribution 4.0 International'
+_LICENSE = "Creative Commons Attribution 4.0 International"
 
 _URLs = "https://zenodo.org/record/55013/files/datasets.zip"
 
@@ -109,32 +105,27 @@ class AskAPatient(datasets.GeneratorBasedBuilder):
         dl_dir = dl_manager.download_and_extract(_URLs)
         dataset_dir = os.path.join(dl_dir, "datasets", "AskAPatient")
         # dataset supports k-folds
-        splits = []
-        for split_name in [
-            datasets.Split.TRAIN,
-            datasets.Split.VALIDATION,
-            datasets.Split.TEST,
-        ]:
-            for fold_filepath in glob.glob(
-                os.path.join(dataset_dir, f"AskAPatient.fold-*.{split_name}.txt")
-            ):
-                fold_id = re.search("AskAPatient\.fold-(\d)\.", fold_filepath).group(1)
-                split_id = f"{split_name}_{fold_id}"
-                splits.append(
-                    datasets.SplitGenerator(
-                        name=split_id,
-                        gen_kwargs={"filepath": fold_filepath, "split_id": split_id},
-                    )
-                )
-        return splits
+        splits_names = ["train", "validation", "test"]
+        fold_ids = range(10)
+        return [
+            datasets.SplitGenerator(
+                name=f"{split_name}_{fold_id}",
+                gen_kwargs={
+                    "filepath": os.path.join(dataset_dir, f"AskAPatient.fold-{fold_id}.{split_name}.txt"),
+                    "split_id": f"{split_name}_{fold_id}",
+                },
+            )
+            for split_name in splits_names
+            for fold_id in fold_ids
+        ]
 
     def _generate_examples(self, filepath, split_id):
         with open(filepath, "r", encoding="latin-1") as f:
             for i, line in enumerate(f):
-                id = f"{split_id}_{i}"
+                uid = f"{split_id}_{i}"
                 cui, medical_concept, social_media_text = line.strip().split("\t")
                 if self.config.schema == "source":
-                    yield id, {
+                    yield uid, {
                         "cui": cui,
                         "medical_concept": medical_concept,
                         "social_media_text": social_media_text,
@@ -142,12 +133,12 @@ class AskAPatient(datasets.GeneratorBasedBuilder):
                 elif self.config.schema == "bigbio_kb":
                     text_type = "social_media_text"
                     offset = (0, len(social_media_text))
-                    yield id, {
-                        "id": id,
-                        "document_id": id,
+                    yield uid, {
+                        "id": uid,
+                        "document_id": uid,
                         "passages": [
                             {
-                                "id": f"{id}_passage",
+                                "id": f"{uid}_passage",
                                 "type": text_type,
                                 "text": [social_media_text],
                                 "offsets": [offset],
@@ -155,13 +146,11 @@ class AskAPatient(datasets.GeneratorBasedBuilder):
                         ],
                         "entities": [
                             {
-                                "id": f"{id}_entity",
+                                "id": f"{uid}_entity",
                                 "type": text_type,
                                 "text": [social_media_text],
                                 "offsets": [offset],
-                                "normalized": [
-                                    {"db_name": "SNOMED-CT|AMT", "db_id": cui}
-                                ],
+                                "normalized": [{"db_name": "SNOMED-CT|AMT", "db_id": cui}],
                             }
                         ],
                         "events": [],