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Python map() and lambda() Use Cases and Examples

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 In Python, map() and lambda functions are often used together for functional programming. Here are some examples to illustrate how they work. Python map and lambda top use cases 1. Using map() with lambda The map() function applies a given function to all items in an iterable (like a list) and returns a map object (which can be converted to a list). Example: Doubling Numbers numbers = [ 1 , 2 , 3 , 4 , 5 ] doubled = list ( map ( lambda x: x * 2 , numbers)) print (doubled) # Output: [2, 4, 6, 8, 10] 2. Using map() to Convert Data Types Example: Converting Strings to Integers string_numbers = [ "1" , "2" , "3" , "4" , "5" ] integers = list ( map ( lambda x: int (x), string_numbers)) print (integers) # Output: [1, 2, 3, 4, 5] 3. Using map() with Multiple Iterables You can also use map() with more than one iterable. The lambda function can take multiple arguments. Example: Adding Two Lists Element-wise list1 = [ 1 , 2 , 3 ]

How to Decode Python Exception Messages Like a Pro

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While developing python programs, you might see exception messages from python. Here's an explanation to understand each part of the message. Here're tips on how to understand python exceptions. You can find two kinds of exceptions. These are StandardError and StopIteration errors. Here is a chart that shows the types of python errors. Python exceptions class Python exceptions are basically three parts. Reading an error message produced by  Python is not very difficult . The error type, the error description, and the traceback. Understand the python exception message The Error Type There are so many in-built exception types in python. Here is the command to get all the exception types: [x for x in dir(__builtins__) if 'Error' in x] The Error description The text message right after the error type gives us a description of what exactly the problem was. These descriptions are sometimes very accurate, sometimes not. Sample error Traceback (most recent call last):       Fil