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Mastering flat_map in Python with List Comprehension

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Introduction In Python, when working with nested lists or iterables, one common challenge is flattening them into a single list while applying transformations. Many programming languages provide a built-in flatMap function, but Python does not have an explicit flat_map method. However, Python’s powerful list comprehensions offer an elegant way to achieve the same functionality. This article examines implementation behavior using Python’s list comprehensions and other methods. What is flat_map ? Functional programming  flatMap is a combination of map and flatten . It transforms the collection's element and flattens the resulting nested structure into a single sequence. For example, given a list of lists, flat_map applies a function to each sublist and returns a single flattened list. Example in a Functional Programming Language: List(List(1, 2), List(3, 4)).flatMap(x => x.map(_ * 2)) // Output: List(2, 4, 6, 8) Implementing flat_map in Python Using List Comprehension Python’...
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How to Explain String Immutability in Python Correctly

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Here is an answer to explain the immutability of Strings in Python. It means that you can't modify the string. Due to this, you can use strings securely in many places of your project.


Strings Immutability


How to check string immutability

Here is an example. In the python shell, assign a value of your choice to a string. Here my choice is ABCD, and I have assigned it to myString. I have tried to replace A with Z. But, it gave an error due to the immutability of strings.


>>> myString = 'ABCD'
>>>myString [0] = 'Z'


What is learning here

The strings immutability is an interview question. In interviews, you can say that strings are immutable, and you can't replace its data.

Benefits of strings immutability

  1. It saves a lot of time since the data in strings are immutable. It results in high performance.
  2. String objects you can reuse as no one can modify its value.
  3. Strings are elemental. So no activity can change its value ( these are more like numbers).

References

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