Create utils.py

utils.py

@@ -0,0 +1,89 @@
+def upload_to_hf_dataset(file_path, dataset_name, token, repo_type="dataset"):
+    """
+    Upload a file to a Hugging Face dataset repository.
+    
+    Args:
+        file_path (str): Path to the file to upload
+        dataset_name (str): Name of the dataset in format 'username/dataset-name'
+        token (str): Hugging Face API token
+        repo_type (str): Repository type, defaults to 'dataset'
+    """
+    from huggingface_hub import HfApi
+    import os
+
+    # Initialize the Hugging Face API client
+    api = HfApi()
+    
+    try:
+        # Upload the file to the dataset repository
+        api.upload_file(
+            path_or_fileobj=file_path,
+            path_in_repo=os.path.basename(file_path),  # Use filename as path in repo
+            repo_id=dataset_name,
+            repo_type=repo_type,
+            token=token,
+            commit_message=f"Upload {os.path.basename(file_path)}",
+            commit_description=f"Automated upload of {os.path.basename(file_path)} to dataset"
+        )
+        print(f"Successfully uploaded {file_path} to {dataset_name}")
+    except Exception as e:
+        print(f"Error uploading file: {str(e)}")
+
+
+
+
+def download_from_hf_dataset(file_path, dataset_name, token, repo_type="dataset"):
+    """
+    Download a file from a Hugging Face dataset repository.
+    
+    Args:
+        file_path (str): Path in the repository to download from
+        dataset_name (str): Name of the dataset in format 'username/dataset-name'
+        token (str): Hugging Face API token
+        repo_type (str): Repository type, defaults to 'dataset'
+    """
+    from huggingface_hub import HfApi
+    import os
+
+    # Initialize the Hugging Face API client
+    api = HfApi()
+    
+    try:
+        # Download the file from the dataset repository
+        api.hf_hub_download(
+            repo_id=dataset_name,
+            filename=file_path,
+            repo_type=repo_type,
+            local_dir=".",
+            token=token
+        )
+        print(f"Successfully downloaded {file_path} from {dataset_name}")
+    except Exception as e:
+        print(f"Error downloading file: {str(e)}")
+
+
+
+
+def load_hf_dataset(csv_filename, token, dataset_name_input):
+    """
+    Load a CSV dataset from Hugging Face and return as pandas DataFrame
+    
+    Args:
+        csv_filename (str): Name of the CSV file in the dataset
+        token (str): Hugging Face authentication token
+        
+    Returns:
+        pandas.DataFrame: DataFrame containing the dataset
+    """
+    from datasets import load_dataset
+    
+    try:
+        dataset = load_dataset(dataset_name_input, 
+                                data_files=csv_filename,
+                                split="train",
+                                token=token)
+        return dataset.to_pandas()
+    except Exception as e:
+        print(f"Error loading dataset: {e}")
+        return None
+