What are the reserved keywords in Python

What are python reserved keywords?

When coding in the Python language there are particular python reserved words that the system uses, which cannot be accessed as a variable or a function as the computer program uses them to perform specific tasks.

When you try to use them, the system will block it and throws out an error. Running the below code in Python

import keyword
keywordlist = keyword.kwlist

Produces the below keyword values
['False', 'None', 'True', 'and', 'as', 'assert', 'async', 'await', 'break', 'class', 'continue', 'def', 'del',
'elif', 'else', 'except', 'finally', 'for', 'from', 'global', 'if', 'import', 'in', 'is', 'lambda', 'nonlocal',
'not', 'or', 'pass', 'raise', 'return', 'try', 'while', 'with', 'yield']

When writing your code, it is important to follow the following guidelines:

(A) Research the keywords first for the language you are writing in.

(B) Ensure that your programming language highlights keywords when used, so you can fix the issue.

(C) Setup your computer program in debug mode to highlight keywords use.

With some programs running into thousands of lines of code, with additional functions and variables, it can become harder to spot the problem, so good rigour in the initial stages of coding will help down the road any issues that you may find that need to fixed.

This code was run in Python version 3.8


Estimated reading time: 2 minutes

What is recursion?
To start a recursion is looking to solve a problem, by breaking it down into smaller chunks, which contribute to the final answer.

If it is calling itself, then it is commonly known as a recursive function.

By breaking down the problem at hand, it can then lead to a quicker understanding and solution to the problem.

A simple example might help here, explaining through factorial:

4! = 4*3*2*1 = 24
simple factorial example

From studying maths at school, the simple example above breaks down as:

  • The result 24 is a product of all the values from 4 down to one.
  • As each value that makes it up is known, it then can be seen how the result is made up.
  • The above can be viewed as a recursive function as it keeps repeating on itself until it reaches one, the base.
  • The recursion knows there are three steps before it reaches one; this is where the breakdown into smaller chunks comes in.

So it could be broken down as follows:

Step 1
4*3 ---> Not reached one, try again from the start.
Step 2
4*3*2 ---> Not reached one, try again from the start.
Step 3
4*3*2*1 ---> Reached one, so the recursion stops and the result is outputted.

Steps 1 to 3 are the steps within the function it takes until it reaches the base value, where the function stops and outputs the final value calculated.

Attributes of a recursion

  • A function which calls on itself, this is the repeated steps above until it reaches the base of 1, meaning it doesn’t loop infinitely.
  • Must be possible to break the problem down into smaller parts.
  • As the problem gets broken down, it must become easier to solve without further calculations.
  • Once a smaller part has calculated, this just becomes part of the answer to the overall problem.

Things to watch out for when using recursion

  • Ensure you always have a base value; without it, you could encounter an infinite loop.
  • Not having the ability to break up the problem into smaller steps won’t allow the calculation of the final answer.

Why use recursion?

  • It helps to break up a complicated task into smaller bits.
  • Assists a programmer to see what steps have already coded for so can be solved with other functions already written.
  • Where there are multiple recursive functions, allows to see if similarities in steps, hence only need to programme once for them.

A good source to provide further knowledge can be found here Wikipedia – Recursion

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