Supabase provides a powerful storage system that allows you to store and manage files efficiently. In this DevTip, we'll explore how to import files from Supabase in Python efficiently, with practical examples and best practices for handling both single files and directories.

Introduction to Supabase storage

Supabase Storage is built on top of PostgreSQL's Large Object storage and provides a simple way to store and serve large files. It organizes files into buckets, similar to how AWS S3 works, making it ideal for managing application assets, user uploads, and other file-based content.

Overview of the Python ecosystem for handling file imports

Python offers a rich ecosystem of libraries for handling file imports and interacting with APIs. When working with Supabase, the official open-source Python SDK provides a convenient way to interact with your Supabase projects, including storage buckets.

Step-by-step guide for setting up Supabase and Python integration

1. Install required Python libraries

To get started, install the official Supabase Python client:

pip install supabase

This library provides functionality to interact with Supabase services, including authentication, database operations, and storage.

2. Configure access credentials and permissions in Supabase

Before connecting to Supabase from Python, ensure that you have your API URL and API key. You can find these in your Supabase project settings under the "API" section.

Additionally, make sure that your storage bucket has appropriate permissions. For private buckets, you'll need to use a service role key or set up policies to allow access.

3. Establish a connection to your Supabase bucket

Create a Supabase client in your Python application using your project's URL and API key:

from supabase import create_client, Client
import os

url: str = "https://your-project.supabase.co"
key: str = "your-api-key"

supabase: Client = create_client(url, key)

Replace "https://your-project.supabase.co" with your Supabase project's URL and "your-api-key" with your public anon key or service role key, depending on your needs.

How to import files from Supabase using Python

Importing a single file

Here's how you can download a single file from a Supabase bucket:

def download_file(bucket_name: str, file_path: str, destination: str) -> None:
    try:
        response = supabase.storage.from_(bucket_name).download(file_path)
        with open(destination, 'wb') as f:
            f.write(response)
        print(f"File downloaded successfully to {destination}")
    except Exception as e:
        print(f"Error downloading file: {str(e)}")

# Example usage
download_file('my-bucket', 'folder/image.jpg', 'local/image.jpg')

In this example:

  • bucket_name is the name of your Supabase storage bucket.
  • file_path is the path to the file within the bucket.
  • destination is the local path where you want to save the downloaded file.

Importing multiple files from a directory

To handle entire directories of files effectively in Python, you can list all files in a bucket (or within a specific prefix) and download them iteratively:

def import_directory(bucket_name: str, prefix: str = "") -> None:
    try:
        # List all files in the bucket with the given prefix
        files = supabase.storage.from_(bucket_name).list(path=prefix)

        for file in files:
            if not file.get('id').endswith('/'):
                file_path = file.get('name')
                local_path = os.path.join('downloads', file_path)

                # Create directory structure if it doesn't exist
                os.makedirs(os.path.dirname(local_path), exist_ok=True)

                # Download the file
                download_file(bucket_name, file_path, local_path)

    except Exception as e:
        print(f"Error importing directory: {str(e)}")

# Example usage
import_directory('my-bucket', 'images/')

In this function:

  • prefix specifies the folder within the bucket you want to download.
  • The function lists all files within the specified prefix and downloads them to a local directory, preserving the folder structure.

Handling large files efficiently

For large files, it's recommended to implement chunked downloading to manage memory efficiently. Here's how you can modify the download function to handle large files:

def download_large_file(bucket_name: str, file_path: str, destination: str, chunk_size: int = 8192) -> None:
    try:
        response = supabase.storage.from_(bucket_name).download(file_path, decode=False)

        with open(destination, 'wb') as f:
            for chunk in response.iter_content(chunk_size=chunk_size):
                if chunk:
                    f.write(chunk)

        print(f"Large file downloaded successfully to {destination}")
    except Exception as e:
        print(f"Error downloading large file: {str(e)}")

Note that we set decode=False when downloading to get the raw bytes, and we read the content in chunks to avoid loading the entire file into memory.

Common challenges and solutions when importing files

Handling permissions

If you encounter permissions errors, ensure that your bucket policies allow read access. For secure applications, use a service role key or implement row-level security policies as appropriate.

Here's how you can verify access to a bucket:

def verify_bucket_access(bucket_name: str) -> bool:
    try:
        supabase.storage.from_(bucket_name).list()
        return True
    except Exception as e:
        print(f"No access to bucket '{bucket_name}': {str(e)}")
        return False

File type validation

Validating file types before downloading can prevent unnecessary downloads and improve security:

def is_allowed_file(filename: str, allowed_extensions: set) -> bool:
    return '.' in filename and \
           filename.rsplit('.', 1)[1].lower() in allowed_extensions

# Example usage
allowed_extensions = {'png', 'jpg', 'jpeg', 'gif'}
if is_allowed_file('image.jpg', allowed_extensions):
    # Proceed with download
    pass

Progress tracking

To provide feedback during downloads, implement progress tracking:

def download_with_progress(bucket_name: str, file_path: str, destination: str) -> None:
    try:
        response = supabase.storage.from_(bucket_name).download(file_path, decode=False)
        total_size = int(response.headers.get('content-length', 0))
        downloaded = 0

        with open(destination, 'wb') as f:
            for chunk in response.iter_content(chunk_size=8192):
                if chunk:
                    f.write(chunk)
                    downloaded += len(chunk)
                    progress = (downloaded / total_size) * 100
                    print(f"Download progress: {progress:.2f}%")

        print(f"File downloaded successfully to {destination}")
    except Exception as e:
        print(f"Error downloading file with progress: {str(e)}")

Best practices for importing files from Supabase

  1. Handle Exceptions Appropriately: Always use try-except blocks to catch and handle exceptions.
  2. Implement Retry Logic: For network-related errors, implement retries to improve resilience.
  3. Validate File Types: Ensure that only the expected file types are downloaded.
  4. Use Chunked Downloads: For large files, read in chunks to avoid memory issues.
  5. Maintain Secure Credentials: Keep your API keys secure and avoid hardcoding them in your code.

Additional resources to optimize Supabase and Python workflows

Conclusion

Importing files from Supabase in Python is straightforward with the right setup. By leveraging the Supabase Python SDK and following best practices, you can efficiently handle both single file imports and bulk downloads.

If you need to process your imported files further or require advanced file handling capabilities, consider using Transloadit's Python SDK for powerful file processing solutions.