20 Valuable and Essential Python Hacks for Beginners

20 Valuable and Essential Python Hacks for Beginners

20 Valuable and Essential Python Hacks for Beginners

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  • Programming

A short, useful guide for quick and efficient Python

Python is among the most widely used market programming languages in the world. This is because of a variety of driving factors:

  • It’s simple to understand.
  • It’s incredibly versatile.
  • It contains a broad collection of modules and libraries.

The brevity and higher readability make it quite prominent among all developers.

As a vital part of my job as a data scientist, I use Python every day. Along the way, I’ve gained a few amazing hacks. I’ve listed some of those below.

20 Necessary Python Hacks

1. Swapping values

Number swaps normally involve values storage in temporary variables. Yet we could do it by using a single line of code through this Python tip, with no transient variables.

2. One string of all items within a list

When you have to convolve a string list, you could do this one after another through updating each item with the help of a for loop. It will, nevertheless, be cumbersome, particularly if the list has been lengthy. Within Python, strings are immutable. Thus, in each duo of concatenation, the left and right strings should be copied into a fresh string.

Using a join() function, as seen here, is a cleaner solution:

p = ["Python", "is", "a", "popular", "language"] 
print(" ".join(p))output
Python is a popular language

3. The most common element in the list

Identify the most frequently occurring value in a list. If various items occur equally print one of them.

Create a list set to remove the redundant values. So the maximum number of events of each item is found in the set, and then we consider the maximum.

list1 = [0, 1, 2, 3, 3, 2, 3, 1, 4, 5, 4] 
print(max(set(list1), key = list1.count))output

4. Test if two strings are anagrams

Solve the problems above to figure out whether two strings are anagrams. Given two strings string_1 and string_2, test if both the strings are anagrams of each other.

5. Reverse a string

Slicing is a handy tip in Python which can also be used to reverse the sequence of items within a string.

6. Reverse a list

A copy of the list is created from this approach, and as well, the list is not sorted in order. To create a copy, you need more room to hold all the existing elements.

7. Transpose a matrix

Transposing a matrix means transforming columns to rows and vice versa. With Python, you can unzip a list that is a transpose of the matrix by using the following code with the zip function in combination with the * tool.

8. Chained comparison

In programming, it is quite normal to test more than two conditions. Let’s assume that we need to test the following:

p < q< r

There is indeed a smarter process of writing it with comparison chaining in Python. The operator chaining has been represented as below:

if p< q< r:

Comparisons return boolean values True or False.

See the example below:

9. Dictionary ‘get’

Below is a traditional way of accessing a value for a key in Python dictionaries.

dict = {"P":1, "Q":2} 

The concern is that the third line of the code yields a key error:

Traceback (most recent call last):
  File ".\dict.py", line 3, in 
    print (dict["R"])
KeyError: 'R'

To prevent these cases, the get() function is used. This technique provides the value for a specific key when available in the dictionary. when it isn’t, None will be returned (if only one argument is used with get()).

10. Sort the dictionary by value

Sorting has always been a useful utility in day-to-day programming. Dictionary in Python is widely used in many applications, ranging from the competitive domain to the developer domain.

Construct a dictionary, as well as show all keys in alphabetical order. List both the alphabetically sorted keys and values by the value.

11. List comprehension

To construct fresh lists from different iterables, list comprehensions are used. Since list comprehensions yield lists, they contain parentheses that include the expression which gets executed to every element. List comprehension is simpler, as the Python interpreter is designed to detect a recurring pattern in looping.

12. Time consumed to implement a part of the program

This one focuses on showing how to compute the time taken by the program or a section of a program to execute. Calculating time helps to optimize your Python script to perform better.

13. Merge dictionaries

This is a trick in Python where a single expression is used to merge two dictionaries and store the result in a third dictionary. The single expression is **. This does not affect the other two dictionaries. ** implies that an argument is a dictionary. Using ** is a shortcut that allows you to pass multiple arguments to a function directly by using a dictionary.

Using this, we first pass all the elements of the first dictionary into the third one and then pass the second dictionary into the third. This will replace the duplicate keys of the first dictionary.

14. Digitize

Here is the code that uses map(), list comprehension, and a simpler approach for digitizing.

15. Test for uniqueness

Some list operations require us to test when total items in the list are distinct. This usually happens when we try to perform the set operations in a list. Hence, this particular utility is essential at these times.

16. Using enumeration

Using enumerators, finding an index is quick when you’re within a loop.

17. Evaluate the factorial of any number in a single line

This one gives you a method to find the factorial of a given number in one line.

18. Return several functions’ elements

This function is not offered by numerous computer languages. For Python, though, functions yield several elements.

Kindly review the following instance to understand how it performs.

19. Incorporate a true Python switch-case statement

Below is the script used to replicate a switch-case structure with a dictionary.

20. With splat operator unpacking function arguments

The splat operator provides an efficient way of unpacking lists of arguments. For clarification, please go through the following illustration:

The Ending Note

I hope the aforementioned 20 necessary Python hacks will allow you to accomplish your Python jobs swiftly and effectively. You can further consider those or your assignments and programs.

Some I found while browsing the Python Standard Library docs. A few others I found searching through PyTricks.

If you think I should include more or have suggestions, please do comment below.

Thanks for reading!

Tags: Essential,Python