Error handling with bigquery python client

okay, let's dive into robust error handling when working with the bigquery python client. we'll cover common errors, strategies for catching them, examining error details, and implementing retry logic for transient failures.

**i. understanding bigquery errors**

bigquery errors fall into a few broad categories:

* **client-side errors:** these occur in your python code before even submitting a job to bigquery. examples:
* `typeerror`: incorrect data type passed to a bigquery client method.
* `valueerror`: invalid configuration parameters.
* `filenotfounderror`: trying to read a file that doesn't exist during data loading.

* `badrequest`: your request is syntactically invalid. could be malformed sql, incorrect schema definition, etc.
* `notfound`: the table, dataset, or resource you specified doesn't exist.
* `conflict`: you're trying to create a resource (e.g., a table) that already exists.
* `forbidden`: insufficient permissions to perform the operation.
* `internalservererror`: bigquery had an internal problem. these can sometimes be transient.
* `serviceunavailable`: bigquery is temporarily unavailable (often due to high load). transient.
* `timeout`: the operation took too long. can be transient.
* `quotaexceeded`: you've hit a bigquery quota limit (e.g., daily query limit).

**ii. basic error handling: `try...except` blocks**

the foundation of error handling in python is the `try...except` block. this allows you to attempt a piece of code and catch specific exceptions that might occur.

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