Python is an interpreted, object-oriented programming language. Its high-level built-in data structures and dynamic typing make it highly useful for the rapid development of new applications, as well as for scripting or "glue" code that integrates components written in different languages.
Python's simple, easy-to-learn syntax emphasizes readability, which helps reduce the cost and complexity of long-term program maintenance. Additionally, Python's rich set of error types simplifies the debugging process, enabling coders to identify and resolve issues more efficiently.
Python error types are essential for diagnosing problems, handling unexpected situations, and ensuring code quality.
Some common error types in Python are, syntax errors, logic errors, assertion errors, index error, key error, name error, type error.
Error types are like clues that guide you on how to fix the problem. Here are some examples of the different error types.
Syntax errors are the result of incorrect syntax, kind of like a typo.
Example:
Here, python is saying that on line 115 there is an extra or misplaced character. The "*" character is causing Python to raise a syntax error because it’s unexpected in this context. Syntax errors can include missing colons, unclosed parentheses, or unmatched quotation marks.
Logic errors are not perceived as errors by Python. To find a logic error a programmer will need to utilize tools like pdb.
One instance of a logic error, is if a function is meant to add two numbers but it is subtracting them instead, Python won’t raise an error, but the output will be incorrect.
An assertion error, is raised when an assert statement fails, meaning that an expected condition was not met.
Example:
Assertions are commonly used in testing and debugging to ensure certain conditions are met during runtime. If an assertion fails, Python immediately raises an error with a custom message, which can be helpful for tracking down logical issues.
Index errors are raised when you try to access an element at an index past the end of the list.
Example:
In the example above we are trying to access the value 10 but it is not available in the list.
A key error is raised when trying to access a dictionary key that doesn’t exist. This happens if you reference a key not present in the dictionary.
A name error occurs when you try to use a variable or function name that hasn’t been defined or is out of scope.
A type error is when an operation or function is applied to an object of the wrong type.
In the example above we have a type error because "123" and 123 are different data types.
In conclusion, understanding Python errors might seem intimidating at first but understanding these common types can simplify the debugging process and improve your coding confidence. Each error type serves as a clue, guiding you toward a solution and helping you write more robust code. The next time you encounter an error, use it as a learning tool, it’s just Python’s way of showing you the path to a more refined program. Python encompasses a broader range of error types than those mentioned above. Attached below is a comprehensive list of additional error types.
References:
Cover Photo: https://realpython.com/python312-error-messages/
Information: https://realpython.com/python312-error-messages/
https://learning.flatironschool.com/courses/8112/assignments/291923?module_item_id=717717
List of Error Types: https://docs.python.org/3/library/exceptions.html
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