Temporary fix: use explicit file listing instead of wildcards

permutation-groups.py

@@ -7,6 +7,35 @@ _DESCRIPTION = "Permutation composition datasets with dynamic filtering by group
 _HOMEPAGE = "https://huggingface.co/datasets/BeeGass/permutation-groups"
 _LICENSE = "MIT"
 
+# TEMPORARY: Define the actual file structure explicitly
+# TODO: Revert to wildcard patterns once datasets library supports them properly
+_DATA_FILES = {
+    "symmetric_superset": {
+        "train": ["data-00000-of-00003.arrow", "data-00001-of-00003.arrow", "data-00002-of-00003.arrow"],
+        "test": ["data-00000-of-00001.arrow"]
+    },
+    "alternating_superset": {
+        "train": ["data-00000-of-00003.arrow", "data-00001-of-00003.arrow", "data-00002-of-00003.arrow"],
+        "test": ["data-00000-of-00001.arrow"]
+    },
+    "cyclic_superset": {
+        "train": ["data-00000-of-00001.arrow"],
+        "test": ["data-00000-of-00001.arrow"]
+    },
+    "dihedral_superset": {
+        "train": ["data-00000-of-00001.arrow"],
+        "test": ["data-00000-of-00001.arrow"]
+    },
+    "psl25_data": {
+        "train": ["data-00000-of-00001.arrow"],
+        "test": ["data-00000-of-00001.arrow"]
+    },
+    "f20_data": {
+        "train": ["data-00000-of-00001.arrow"],
+        "test": ["data-00000-of-00001.arrow"]
+    }
+}
+
 class PermutationGroupsConfig(datasets.BuilderConfig):
     def __init__(
         self, 
@@ -23,7 +52,7 @@ class PermutationGroupsConfig(datasets.BuilderConfig):
         Configuration for loading permutation groups.
         
         Args:
-            group_type: Type of group (symmetric, alternating, cyclic, dihedral, special)
+            group_type: Type of group (symmetric, alternating, cyclic, dihedral, psl25, f20)
             min_degree: Minimum group degree to include
             max_degree: Maximum group degree to include
             min_order: Minimum group order to include
@@ -168,43 +197,64 @@ class PermutationGroups(datasets.ArrowBasedBuilder):
                               "cyclic_superset", "dihedral_superset", 
                               "psl25_data", "f20_data"]
         
-        # Download files
-        train_files = []
-        test_files = []
+        # TEMPORARY: Build explicit file URLs instead of using wildcards
+        # TODO: Revert to wildcard pattern once supported:
+        # data_urls = {
+        #     "train": f"data/{dataset_name}/train/data-*-of-*.arrow",
+        #     "test": f"data/{dataset_name}/test/data-*-of-*.arrow",
+        # }
+        train_urls = []
+        test_urls = []
         
         for dataset_name in datasets_to_load:
-            data_urls = {
-                "train": f"data/{dataset_name}/train/data-*-of-*.arrow",
-                "test": f"data/{dataset_name}/test/data-*-of-*.arrow",
-            }
-            try:
-                downloaded = dl_manager.download(data_urls)
-                if isinstance(downloaded["train"], list):
-                    train_files.extend(downloaded["train"])
-                    test_files.extend(downloaded["test"])
-                else:
-                    train_files.append(downloaded["train"])
-                    test_files.append(downloaded["test"])
-            except:
-                # Skip if dataset doesn't exist
-                pass
+            if dataset_name in _DATA_FILES:
+                # Build full URLs for each file
+                for filename in _DATA_FILES[dataset_name]["train"]:
+                    train_urls.append(f"data/{dataset_name}/train/{filename}")
+                for filename in _DATA_FILES[dataset_name]["test"]:
+                    test_urls.append(f"data/{dataset_name}/test/{filename}")
         
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "files": train_files,
-                    "config": self.config,
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "files": test_files,
-                    "config": self.config,
-                },
-            ),
-        ]
+        # Download files
+        if train_urls and test_urls:
+            downloaded_files = dl_manager.download({
+                "train": train_urls,
+                "test": test_urls
+            })
+            
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "files": downloaded_files["train"],
+                        "config": self.config,
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "files": downloaded_files["test"],
+                        "config": self.config,
+                    },
+                ),
+            ]
+        else:
+            # Return empty splits if no files found
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "files": [],
+                        "config": self.config,
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "files": [],
+                        "config": self.config,
+                    },
+                ),
+            ]
     
     def _generate_tables(self, files, config):
         """Yield arrow tables with filtering."""