python-sdk-best-practices

Yes, async context managers are the recommended pattern for the Bright Data Python SDK. Using async context managers with BrightDataClient prevents resource leaks and ensures proper connection cleanup during web scraping and dataset retrieval workflows.

The best way to handle exceptions in the Bright Data Python SDK is to implement safe result and exception handling around your scrape_url calls. Wrap scraping logic in try-except blocks to catch and manage errors without crashing your async or sync workflows.

To retrieve datasets, use the Bright Data Python SDK's built-in dataset functions within your async or sync workflow. The SDK provides comprehensive patterns for dataset usage, allowing you to safely fetch and process scraped data results.

To configure the BrightDataClient in Python, import the necessary SDK modules and initialize the client using your environment-based token. This setup allows you to perform scraping, searching, and browser integration with recommended defaults.