Upload folder using huggingface_hub

processed_data/upload_processed_data.py

@@ -1,34 +1,18 @@
-from huggingface_hub.utils import RepositoryNotFoundError, HfHubHTTPError
-from huggingface_hub import HfApi, create_repo
+from huggingface_hub import HfApi
 import os
 
 repo_id = "SharleyK/TourismPackagePrediction"
 repo_type = "dataset"
-local_data_folder = "tourism_project/data/model_building"
 
 # Initialize API client
 api = HfApi(token=os.getenv("HF_TOKEN"))
 
-# Step 1: Check if the space exists (this check is more robust for subsequent uploads)
-try:
-    api.repo_info(repo_id=repo_id, repo_type=repo_type)
-    print(f"Space '{repo_id}' already exists. Uploading files.")
-except RepositoryNotFoundError:
-    print(f"Space '{repo_id}' not found. Creating new space and uploading files.")
-    create_repo(repo_id=repo_id, repo_type=repo_type, private=False) # private=False makes it public
-    print(f"Space '{repo_id}' created.")
+# Upload the processed data folder
+api.upload_folder(
+    folder_path="tourism_project/data/model_building",
+    repo_id=repo_id,
+    repo_type=repo_type,
+    path_in_repo="processed_data"
+)
 
-# Step 2: Upload the processed data files to the Hugging Face space
-try:
-    api.upload_folder(
-        folder_path=local_data_folder,
-        repo_id=repo_id,
-        repo_type=repo_type,
-        path_in_repo="processed_data", # Upload into a subfolder named 'processed_data'
-        commit_message="Upload processed training and testing data"
-    )
-    print(f"Successfully uploaded files from '{local_data_folder}' to '{repo_id}' under 'processed_data/'.")
-except HfHubHTTPError as e:
-    print(f"Hugging Face Hub HTTP Error: {e}")
-except Exception as e:
-    print(f"An unexpected error occurred during upload: {e}")
+print("Processed datasets uploaded to Hugging Face data space under 'processed_data' folder.")