Python Error Handling

Python Error Handling is the practice of anticipating failure, catching expected exceptions, and responding clearly. In Brevvie Python + AI — Section 2: Control Flow & The Treasure Hunt, it is taught through try / except and logging-friendly recovery. In Brevvie Python + AI — Section 4: APIs, Postman & Calling the Web, the same idea is applied to network code and API failures.

Core points from the source

• outside-world code and missing data can fail
• catch specific exceptions like KeyError
• notify when failure happens; do not fail silently
• use broad catch-alls sparingly
• prefer warnings and recovery over crashing the whole workflow when appropriate

Added from Brevvie Python + AI — Section 4: APIs, Postman & Calling the Web

• call resp.raise_for_status() after HTTP requests
• catch specific exceptions like httpx.TimeoutException, httpx.HTTPStatusError, and httpx.RequestError
• branch on status codes like 401, 429, and 5xx
• treat retries, timeouts, and third-party outages as normal engineering concerns

Why it matters

Across the sources, error handling is framed as the difference between brittle scripts and resilient software: bad rows, missing keys, and flaky APIs should be handled intentionally rather than ignored.