Python, used in around 53% of all Lambda functions, is the most popular language for doing Serverless. Because of that, in the following weeks, I’m going to introduce you to the facts and best practices in building Lambda functions with Python. First up in the series is an overview of the need-to-knows for error handling Python in AWS Lambda.

Failure types

There are a lot of different things that can go wrong in your Lambda so let’s break each of them down.

Syntax Errors

Syntax errors, also known as parsing errors, are perhaps the most common kind of failure. They get thrown before any program command is executed. Here’s how one looks like:

>>> while True print('Hello world')
  File "<stdin>", line 1, in ?
      while True print('Hello world')
                     ^
SyntaxError: invalid syntax

Exceptions

Exceptions occur if a statement or expression is syntatically correct but an error is caused when executing it. As a developer, you can handle exceptions and make them non-fatal to your program. However, most execptions are not handled and result in an error message like this:

>>> 10 * (1/0)
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
ZeroDivisionError: division by zero
>>> 4 + spam*3
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
NameError: name 'spam' is not defined
>>> '2' + 2
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
TypeError: Can't convert 'int' object to str implicitly

Failed to import module

Worth noting separately is the import module exception. In essence, this is an exception as every other, yet it requires some special attention in Lambdas. It is raised before the execution reaches the function handler, meaning it does not reach the execution wrapped by the function handler. This usually prevents this type of failure to be reported by error alerting agents.

#python #python error #python error handling