To get the best results while practicing for a Python coding interview, it is important to efficiently solve problems. This will make the process faster and help you understand the code better. In this article, we will learn how to do so by looking at some examples of code and discussing them in detail. We will also take sample inputs so that we can test the output and verify if the code works correctly.

1. Use proper data structure

Using the proper data structure will help your code run more efficiently. It will reduce the amount of time and memory required to execute your code.

Python supports various built-in data structures like list, tuple and dictionary. But most programmers use list for all purposes, instead of using a proper data structure. Tuples are immutable and provide a more efficient way to store data than lists. They also perform operations faster than lists because they are interpreted only once when the program is executed.

2. Avoid global variables

Global variables can be helpful in python problem solving but should be used sparingly. Using too many global variables can lead to inconsistencies and fragile code that is difficult to debug and maintain. It can also cause problems with encapsulation, because the same variable can be accessed or modified from multiple places in your program.

You can create global variables in Python by using the global keyword or the globals() function. However, this is not a good practice and can result in complex, hard-to-read, and hard-to-test code. Instead, try to pass values through function arguments and return them to avoid relying on global variables. Another option is to use global constants, which are read-only and cannot change during code execution. They can be an effective replacement for global variables in many cases.

3. Use while loop instead of for loop

Using a while loop instead of a for loop can decrease your code’s runtime. A for loop can be used to iterate over a list of objects, while a while loop can only be iterated over if a certain condition is true.

A for loop can be stopped by pressing Ctrl+C, but a while loop will keep running until it is terminated. This is because a while loop will continue to execute unless its boolean condition is changed. The break and continue statements are also useful in a while loop, giving you an added means of short-circuiting the loop. Just be careful to use these statements carefully so you don’t accidentally break an intentional infinite loop! Also, be sure to include an else clause after your while loop.

4. Avoid recurrence relation

Recursion is an important programming concept that allows you to solve complex problems in Python. However, it can be dangerous if not used properly. It can result in functions that never stop running or use excess memory.

To avoid this, you should use iteration instead of recursion. Iteration is faster and more memory-efficient. It also avoids the risk of infinite calls that can occur with recursion. To iterate, you can use 'for' or 'while' loops in your code. You should define a variable that will store the results of each iteration. You should then perform arithmetic operations on that variable each time you iterate. This will ensure that the function does not reach an infinite call state. This will keep the function fast and efficient.

5. 
   

6. Take sample inputs

In Python, there are many ways to obtain input from users. For example, you can use the input() function to collect a string or a number. Moreover, you can also use the "input()" method to convert the user's input into a data type and save it for later reference in your program.

To do this, you need to know about a special type of algorithm called dynamic programming. It's an approach to solving problems in a bottom-up manner by combining the solutions of subproblems. It works similarly to divide and conquer algorithms, but it's more efficient than other recursive techniques.