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Python Keywords : Everything You Need to Know

Basics of Python
Basics of Python
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As we very well know, every language has a vocabulary and a system of rules that gives meaning to sentences. The Python language in the same way has its own library which consists of predefined words called Keywords. It is against the rules to name variables, functions, or classes with Python keywords. In this article, we will learn Python keywords in this article and how to use them for various tasks.

List of Python Keywords

False await else import pass
None break except in raise
True class finally is return
and continue for lambda try
as def from nonlocal while
assert del global not with
async elif if or yield

 

Identification of Python Keywords

As we’ve already covered, your keywords may vary based on your version. Therefore, it’s crucial to verify that your keywords are accurate. You can determine whether a word you’ve used is a keyword or not using a few different techniques. These techniques are as follows:

 

  • Employ a Syntax Highlighting IDE

 

Syntax highlighting is one of the features offered by several IDEs. The keywords are highlighted when you use these IDEs to write Python code. When writing or reviewing code, programmers can more easily identify keywords using different colours or styles.

 

  • Use a REPL to Check Keywords with Code

 

Another option is to use a REPL (Read-Eval-Print Loop) environment, like Jupyter Notebook or the interactive Python interpreter. They offer tools to assist developers in testing brief code passages with possible keywords. This will assist them in determining whether the keywords they are using are recognised by Python as keywords, allowing them to make the necessary adjustments immediately.

 

  • Seek out any syntax errors

 

Searching for SyntaxError in your Python code is an additional technique. Because keywords such as variable names and function names cannot be used as identifiers in Python, if you see a SyntaxError, you have used a keyword incorrectly.

 

Also Read: Relational Operators in Python

Getting All of the Python keywords

With the code below, we can also obtain the names of all the keywords.

 

import keyword

 

print(“Keywords in Python: “)

print(keyword.kwlist)

 

Output:

 

Keywords in Python:

 

[‘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’]

Python Keywords Usage

Value Keywords: True, False, None

There are three values that are keywords in Python. The same object is always referenced by these singleton values, allowing for repeated use. These values will probably be seen and used frequently by you.

 

The True and False Keywords

 

In Python code, the Boolean true value is represented by the True keyword. Similar to the True keyword in Python, but with the opposite Boolean value of false, is the False keyword. These keywords (true and false) are written in lowercase in other programming languages, but they are always written in uppercase in Python.

It is not advisable to compare a value’s truthiness directly to True or False when creating conditional statements. Python is a reliable tool for performing the truthiness check in conditionals:

>>> x = "this is a true value" >>> if x is True:  # Don't do this print("x is True")   >>> if x:  # Do this print("x is true")   x is true

The None Keyword

None is a Python keyword and denotes no value. None is represented by null, nil, none, undef, or undefined in other programming languages.

 

In the event that a function lacks a return statement, it will also default to returning None:

 

>>> def func():

print(“hello”)

 

>>> x = func()

hello

>>> print(x)

None

Operator Keywords: and, or, not, in, is

Numerous keywords in Python are employed as operators. &, |, and! are the symbols used by these operators in other programming languages.

 

Python programmers create readable code due to which a large number of operators in Python are keywords.

 

The and Keyword

 

To ascertain whether the left and right operands are both true or false, utilise the Python keyword. The result will be true if both operands are true. The outcome will be false if one of them is false:

 

<a1> and <a2>

 

Keep in mind that an and statement’s outcomes aren’t always True or False. This is a result of and’s peculiar behaviour. It returns <a1> if the operand is false and <a2> otherwise, without evaluating the operands to their Boolean values. The output of a and statement can be utilised in a conditional if statement or passed to bool() to obtain the explicit True or False value.

 

The or Keyword

 

The keyword in Python ascertains whether at least one of the operands is true. If the first operand is true, an or statement returns it; if not, it returns the second operand.

 

<a1> or <a2>

 

Similar to the and keyword, the operands of or are not converted to their Boolean values. Rather, it uses their veracity to ascertain the outcomes.

 

The not Keyword

 

Python’s not keyword is used to get the opposite Boolean value of a variable:

>>> val = "" >>> not val True   >>> val = 5 >>> not val False

To reverse the meaning or outcome, use the not keyword in conditional statements and other Boolean expressions. As opposed to and and or not, which returns the opposite after determining the explicit Boolean value, True or False.

 

The in Keyword

 

The in keyword in Python is an effective membership or containment check operator. It will return True or False depending on whether the element was located in the container given an element to find and a container or sequence to search:

 

<element> in <container>

 

The is Keyword

 

Identity check is a keyword in Python. The == operator verifies equality; this is not the same. Two items may occasionally be regarded as equal even though they are not the same thing in memory. To find out if two objects are the same, use the is keyword:

 

<obj1> is <obj2>

 

This will return True if <obj1> is the same object in memory as <obj2>, or else it will return False.

Control Flow Keywords: if, elif, else

For control flow, three Python keywords are used: else, elif, and if. With the help of these Python keywords, you can apply conditional logic and run code under specific circumstances. These are very common keywords that you’ll find in practically every Python program you see or write.

 

The if Keyword

 

An expression that is conditional is started with the if keyword. You can write a block of code that is only executed if the expression after if is true with an if statement.

The if keyword is used at the beginning of the line in an if statement, and then a valid expression that will be assessed for truthiness value comes next:

 

if <n>:

<statements>

 

One of the most important parts of most programs is the if statement. See Conditional Statements in Python for additional details on the if statement.

 

The elif Keyword

 

There are two main differences between the if and elif statements: (1) Using elif is only permitted after an if statement or another elif.

 

elif statements can be used as often as necessary.

 

if <a1>:

<statements>

elif <a2>:

<statements>

elif <n3>:

<statements>

The else Keyword

 

The Python keywords if and elif, when combined with the else statement, indicate a block of code that should only be run in the event that the other conditional blocks, if and elif, are all false:

 

if <n>:

<statements>

else:

<statements>

 

You’ll see that a conditional expression is not accepted by the else statement. Along with if, the elif and else keywords are among the most commonly used parts of any Python program, so knowing how to use them correctly is essential for Python programmers.

Iteration Keywords: for, while, break, continue, else

Iteration and looping are two fundamental programming ideas. To create and manipulate loops, one uses a number of Python keywords. Similar to the Python keywords utilised for conditionals previously mentioned, practically all Python programs will make use of these. You’ll become a better Python programmer if you comprehend them and use them appropriately.

The for Keyword

The for loop is the most used loop in Python. The Python keywords for and in the previously described are combined to create it. A for loop’s fundamental syntax is as follows:

 

for <element> in <container>:

<statements>

 

Example:

>>> for num in range(1, 6): print(num)   1 2 3 4 5

Different programming languages have different syntax for a for loop. Frequently, you will need to define the variable, the if-then statement, and the incrementation method (for (int i = 0; i < 5; i++)).

The while Keyword

The block that follows the while statement will keep running repeatedly as long as the condition that comes after the while keyword is true:

 

while <n>:

<statements>

The break Keyword

If the integers from a list of numbers are being added up and it is required to stop when the total exceeds a certain amount the break keyword is used. Here’s an example of how to use the break keyword:

>>> nums = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] >>> total_sum = 0 >>> for num in nums: total_sum += num if total_sum > 10: break   >>> total_sum 15

When working with loops, the Python keywords break and continue can both be helpful tools. See Python “while” Loops (Indefinite Iteration) for a more thorough explanation of their applications. To investigate an alternative application of the break keyword, discover how to simulate do-while loops in Python.

The continue Keyword

For those who wish to move on to the subsequent loop iteration, Python also provides a continue keyword. The continue keyword lets you end the current loop iteration and go on to the next one, just like in most other programming languages:

 

for <element> in <container>:

if <n>:

continue

 

While loops are supported by the continue keyword as well. In a loop, the current iteration ends and the subsequent one begins when the continue keyword is reached.

The else Keyword Used With Loops

You can use the else keyword as part of a loop in addition to using it with conditional if statements. The else keyword, when used in conjunction with a loop, indicates the code to be executed in the event that the loop ends normally—that is, if the break was not called to end the loop early.

 

When utilising else with a for loop, the syntax is as follows:

for <element> in <container>: <statements> else: <statements>

The prime flag can be used to indicate the method used to exit the loop. In case of a normal exit, the prime flag remains True. If there is a break in the exit, the prime flag will be False. After exiting the inner for loop, you can verify if the prime is True by looking at the flag and, if it is, printing that the number is prime.

Structure Keywords: def, class, with, as, pass, lambda

Use one of the Python keywords listed in this section to define functions, classes, and context managers. Knowing when to use them will make you a better programmer as they are an integral part of the Python language.

 

The def Keyword

 

A function or method of a class is defined using the def keyword in Python. This is equivalent to a function in JavaScript and PHP. The following is the basic syntax for using def to define a function:

 

def <function>(<params>):

<body>

 

In any Python program, functions and methods can be extremely useful structures. See Defining Your Own Python Function to discover more about defining them and all of their details.

 

The class Keyword

 

In Python, the class keyword is used to define a class. The following is the standard syntax for defining a class with class:

 

class MyClass(<extends>):

<body>

 

In object-oriented programming, classes are useful tools that you should be familiar with and know how to define. Check out Python’s Object-Oriented Programming (OOP) tutorial to learn more.

 

The with Keyword

 

In Python, context managers are an incredibly useful structure. Before and after the statements you designate, each context manager runs a different set of code. You use the with keyword to use one:

 

with <context manager> as <var>:

<statements>

 

You can specify code to run within the context manager’s scope by using with. The simplest example is using Python’s file I/O functionality.

 

The as Keyword Used With with

 

You must alias it using as if you wish to access the output of the expression or context manager that was passed to it. Additionally, “as” is frequently used to alias imports and exceptions; this is also the case here. The following block contains the alias:

 

with <n> as <alias>:

<statements>

 

These two Python keywords, with and as can be seen being used together.

 

The pass Keyword

 

The pass keyword is used to indicate that a block is purposefully left blank because Python lacks block indicators to indicate when a block ends. It is comparable to an operation or no operation at all. Here are some instances of how to indicate that the block is blank using the pass keyword:

def my_function(): pass   class MyClass: pass   if True: Pass

The lambda Keyword

 

When defining a function with no name and just one statement that returns results, the lambda keyword is used. Lambda functions are functions that have been defined with lambda.

This is a simple illustration of a lambda function that calculates the argument raised to the power of ten:

 

p10 = lambda x: x**10

 

Defining an alternative behaviour for another function is a typical application for a lambda function. Consider sorting a list of strings according to their integer values. By default, sorted() would arrange the strings in alphabetical order. However, you can designate the key that the list should be sorted on using sorted().

Returning Keywords: return, yield

Return and yield are two Python keywords that define what is returned from functions or methods. Learning when and where to use return is essential to improving your Python programming skills. Although it’s a more complex feature of Python, understanding the yield keyword can be helpful.

 

The return Keyword

 

Python’s return keyword can only be used inside of def-defeated functions. Python will exit the function at that point and return the output of whatever follows the return keyword when it encounters this keyword:

def <function>(): return <n>   When there is no input provided, “return” gives None by default.

The yield Keyword

 

Similar to the return keyword in Python, the yield keyword indicates what is returned from a function. On the other hand, a generator is returned from a function that contains a yield statement. The next value returned by the function can then be obtained by passing the generator to Python’s built-in next() function.

 

Python executes a function until it hits the first yield keyword when you call it with a yield statement, at which point it returns a generator. Generator functions are what these are called:

def <function>(): yield <n>

Import Keywords: import, from, as

Python’s standard library contains a number of helpful modules that are only importable. You’ll also need to import a number of other helpful libraries and tools from PyPI into your programs after installing them in your environment.

The three Python keywords that are used to import modules into your program are briefly described below:

 

The import Keyword

 

Python’s import keyword is used to import or include a module in a Python program.The basic usage syntax looks like this:

 

import <module>

 

After that statement runs, the <module> will be accessible to your program.

All of the tools in that module are accessible by using the name. To access Counter, you can reference it from the module collections.

 

The from Keyword

 

The  task of the from keyword is to import a specific component from a module:

 

from <module> import <thing>

 

This will import <thing> from <module> so that it can be used in your program. From and import are two Python keywords that are used in tandem.

 

The as Keyword

 

An imported module or tool can be aliased using the as keyword. It modifies the name of the object being imported when used in conjunction with the Python keywords import and from:

 

import <module> as <alias>

from <module> import <thing> as <alias>

 

As can assist in creating the import alias for modules with lengthy names or for those that are frequently used.

The packages Pandas or NumPy are more frequently used as import aliases. Standard aliases are commonly used when importing these:

 

import numpy as np

import pandas as pd

 

You can shorten the name of the module being imported and it’s a better option than just importing everything from a module.

Exception-Handling Keywords: try, except, raise, finally, else, assert

 

The raising and catching of exceptions is a common feature of any Python program. Since this is an essential component of all Python code, you can make this section of your code as clear and concise as possible by using one of the many Python keywords available.

 

These Python keywords and their basic usage are covered in the sections that follow. See Python Exceptions: An Introduction for a more thorough tutorial on these terms.

 

The try Keyword

 

The try keyword in Python is the first character in any exception-handling block. Most other programming languages with exception handling work in the same way.

 

The code that is expected to throw an exception is kept inside the try block. Try is related to several other Python keywords that specify what should be done in various scenarios or in the event that an exception is raised. These are, in order, except, else, and lastly:

try: <statements> <except|else|finally>: <statements>

If the entire try statement contains at least one of the other Python keywords used for exception handling, the try block is invalid.

 

The except Keyword

 

Try and the except keyword in Python are used to specify what should happen when particular exceptions are raised. On a single try, you can have one or more except blocks. This is how the basic usage appears:

try: <statements> except <exception>: <statements>

The raise Keyword

 

An exception is raised by the raise keyword. If you discover that you need to raise an exception, you can do so by using raise and the exception that needs to be raised:

 

raise <exception>

 

You print a message to the screen and then raise the exception again when you catch the TypeError.

 

The finally Keyword

 

The finally keyword in Python is useful for defining code that must be executed regardless of the outcome of the try, except, or else blocks. When using finally, include it in a try block and indicate which statements should always be executed:

try: <statements> finally: <statements>

“else” Keyword With “try” and “except”

 

As you now know, the else keyword in Python has another use besides just working with loops and the if keyword. It can be used in conjunction with the Python keywords try and except. Only if you additionally use at least one except block can you use else in this manner:

try: <statements> except <exception>: <statements> else: <statements>

In this case, the else block’s code is only executed in the event that the try block’s exception-raising code is not raised. Stated differently, the else block code would be executed if the try block executed all of the code successfully.

 

The assert Keyword

 

In Python, an assert statement or an assertion concerning an expression can be specified using the assert keyword. If the expression (<n>) is true, an assert statement will produce a no-op; if the expression is false, it will raise an AssertionError. Use assert and an expression to define an assertion:

 

assert <n>

 

Assert statements are typically used to verify that a proposition is true. You shouldn’t rely on them, though, as how your Python program is run may disregard them.

Asynchronous Programming Keywords: async, await

The subject of asynchronous programming is intricate. Async and await are two Python keywords that are defined to help make asynchronous code easier to read and organise.

 

The two asynchronous keywords and their basic syntax are introduced in the sections below; an in-depth discussion of asynchronous programming will not be covered.

 

The async Keyword

 

To define an asynchronous function or coroutine, use the async keyword in conjunction with def. The syntax is the same as when defining a function, but async is added at the start:

async def <function>(<params>): <statements>

The await Keyword

 

When writing asynchronous functions, the await keyword in Python is used to indicate when control should return to the event loop so that other functions can continue. To utilise it, precede any call to an async function with the await keyword:

await <some async function call> # OR <var> = await <some async function call>

When utilising await, you have two options: when the asynchronous function finally returns, you can store the results in a variable or call it and ignore the results.

Variable Handling Keywords: del, global, nonlocal

The del keyword is more commonly used than the global and nonlocal ones. But it’s still helpful to know and understand all three keywords to identify when and how to use them.

 

The del Keyword

 

Python’s del command is used to unset a variable or name. Although it can be applied to variable names, deleting indexes from a list or dictionary is one of its most popular uses. Use del followed by the variable you wish to unset in order to unset it:

 

del <variable>

 

The global Keyword

 

Use the global keyword if you need to make changes to a variable that is defined in the global scope but not in a function. This is accomplished by indicating in the function which variables from the global scope must be retrieved and used within the function:

 

global <variable>

 

Example:

>>> x = 0 >>> def inc(): global x x += 1   >>> inc() >>> x 1 >>> inc() >>> x 2

The nonlocal Keyword

 

Comparable to global, the nonlocal keyword lets you change variables from a separate scope. When you use global, the global scope is what you’re drawing from. When using nonlocal, the parent scope is the scope from which you are pulling. Syntax is comparable to that of global:

 

nonlocal <variable>

 

This keyword isn’t often used, but it can sometimes be handy.

 

Also Read: Difference between For Loop and While Loop in Python

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Conclusion

Python keywords build the basics of every Python program. Knowing their correct usage is essential for enhancing one’s Python skills and knowledge.

 

Throughout this article, you’ve seen a few things for understanding the Python keywords and to help you write more efficient and readable code. You’ve learned about the Python keywords in version 3.8 and their basic usage, several resources to help deepen your understanding of many of the keywords, and how to use Python’s keyword module to work with keywords in a programmatic way.

FAQs
False, True, None, and the following are some of the keywords in Python: break, class, continue, except, finally, for, from, global, if, import, in, is, lambda, nonlocal, not, or, pass, raise, return, try, while, with, and yield.
No, python keywords can't be redefined or overridden, as each keyword has its own special meaning.  
'type' is not a keyword that is reserved like others but actually a built-in function in Python which is used for finding the type of an object or for creating new types dynamically.
Yes, 'is' is used as a keyword in python for identity testing. It is used for checking if two variables are referring to the same object.
There are a total of 35 keywords in Python as of Python 3.11. Keywords change with versions as new ones might be introduced and existing ones might get removed.
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