Python Keywords - Boolean, Conditionals, Logical Operators, Membership Checks, Exceptions and Loops

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The Python programming language has important "reserved" commands called keywords. Each one of them provides specific special instructions for the interpreter. Using the keywords comes with certain caveats, and it is handy to have a complete overview of their use.


This Python tutorial provides a listing and overview of all Python keywords. These keywords are categorized according to their function: Boolean, conditionals, logical operators, membership checks, exceptions, and loops, along with explanations and examples. Note: These are only the keywords; built-in methods or other methods from external libraries are not discussed.

Python Keyword Overview

Here is the list of all keywords in alphabetical order:

  • and
  • as
  • assert
  • async
  • await
  • break
  • class
  • continue
  • def
  • del
  • elif
  • else
  • except
  • False
  • finally
  • for
  • from
  • global
  • if
  • import
  • in
  • is
  • lambda
  • None
  • nonlocal
  • no
  • or
  • pass
  • raise
  • return
  • True
  • try
  • while
  • with
  • yield

Let's group them functionally, explaining what each of them does and how they work.



These are the ubiquitous Boolean values. Unlike other programming languages, both are capitalized. The evaluation result of directly comparing two variables (or testing them for equivalency) will return either True or False.

a = 'SQL'
b = 'MySQL'
print(a != b)
print(a == b)
basic check with outcome true or false

Additionally, a variable can be assigned to the True or False value:

a, b = True, False
print(a, b)
boolean value assignment

Finally, you can assign the actual check for a value to a variable. This variable will return True or False. In this case, we check if the value of a is a certain integer. With the help of the and, or, and not keywords, this technique can help to construct complex logic checks:

a = 1
c = a == 2
logical condition assigned to a variable


These keywords are vital in constructing control flow logical checks.


The elif is short for else if. The two most common ways to use these keywords are in if-else or if-elif-else statements, where the elif may be repeated as many times as branches are needed.

Here is a simple example:

a = 0
if a == 1:
    print('Variable a has value of 1')
elif a == 2:
    print('Variable a has value of 2')

Note: The placeholder value pass under the else clause: The program will not do anything here, but will not pause.

Another way to use the if-else conditional statement is by using only the if clause. This sometimes occurs when you check for a specific value of a variable without any other branches. A common use of this technique is in a for-loop:

for i in range(10):
    if i == 3:
        print('Level 3 reached')
check with only the if clause

Finally, check the ternary use of if-else in my tip, Python Control Flow Logic including IF, ELIF and ELSE. While it is convenient as a one-liner, I would not recommend it for nested checks.

Logical Operators

These are logical operators.


The and operator accepts multiple expressions which evaluate to True or False and returns one Boolean value as a result. If any of the inputs is False, the result will be False. With or, it is enough for one of the inputs to be True for the whole result to be True. On the other hand, not is the logical negation operator. It is commonly used to reverse the value of a Boolean variable, i.e., a True variable will become False if negated with not.

Here is a tabular overview:

boolean grid

Membership Check

This keyword has two functions. The first is to perform a membership check against an iterable.


Here is an example that also makes use of not in combination with in:

my_var_a = 'a'
my_var_d = 'd'
sequence = ['a', 'b', 'c']
if my_var_a in sequence:
    print(f'Variable {my_var_a} present.')
if my_var_d not in sequence:
    print(f'Variable {my_var_d} added.')
membership check with in

The second function of in is iterating over a sequence in a for loop, for example:

for i in range(3):
    print(i) # prints 0, 1, 2

range generates an immutable sequence; therefore, in can be used with it.


These are the keywords related to developing robust code that expects errors might arise and is prepared to handle them gracefully.


The main clause, try, "tries" the code block for an exception. except will raise one or more exceptions depending on the error that might have occurred. The code under finally will execute regardless of if an exception was raised or not. The else clause can also be used prior to finally to execute a code block only if no exception occurred. I have written an extensive tip on exception handling called Python Try Except Code Samples.

The with keyword is a special case but still belongs to the exceptions section.


 It is a generalization of a lengthier code that would look like this:

    # do smth
    # clean-up

The general syntax of with is:

with expression [as variable]:

The expression must support the context management protocol, which implements special __enter__ and __exit__ methods. The former ensures that whatever we do is set up correctly, and the latter ensures that even if an exception is raised, clean-up will be performed.

In practice, there are two main situations when you will use with:

1 - File Objects

with enables us to quickly set up read or write blocks of code with little effort. In this example, file.txt contains three lines of text:

path_to_file = r'C:\Users\file.txt' 
with open(path_to_file, 'r') as f: 
   read_data = 
reading file objects with with

With the help of with, here we have ensured that the target file is handled efficiently while there were data lines to be retrieved.

2 - Context Managers

A database connection is a context manager; therefore, it can be used in a with-statement:

import pyodbc 
connection_str = 'DRIVER= {ODBC Driver 17 for SQL Server}; \ 
SERVER=.; \ 
DATABASE=AdventureWorks2019; \ 
query = 'SELECT TOP 100 * FROM Person.Person' 
with pyodbc.connect(connection_str) as connx: 
   cursor = connx.cursor() 
   data = cursor.fetchone() 

The output is the first result of the query (because of the fetchone method):

with in db connection context manager

An extensive tip, How to Query SQL Data with Python pyodbc, explains how to use the pyodbc library.

For Loops and While Loops

In this next category, we arrive at all loop-related keywords:


for and while are used to construct a loop. The loop is a construct that allows repeating a block of code according to a predefined rule or condition. For example, with for and enumerate, we can easily go over every element from a sequence together with its index:

my_list = ['a','b','c']
for i, v in enumerate(my_list):
for and enumerate

On the other hand, while enables us to construct a loop that executes only when a certain condition is true. For example, if we take a target number, we can decrease it and display if every single number less than or equal to it is odd or even:

my_num = 10
while my_num > 0:
  if my_num % 2 == 0:
    print(f'The number {my_num} is even')
    print(f'The number {my_num} is odd')
  my_num -= 1
while loop example with if and else

With while, you must always beware of the risk of designing a runaway loop. In the example above, forgetting to decrease my_num by one will create such a loop.

Next is the break keyword. Its core usage is when you want to terminate a loop's execution if a certain condition has been reached. For example, we can "break" the previous loop if our number gets to 7:

while my_num > 0:
  if my_num == 7:
  if my_num % 2 == 0:
    print(f'The number {my_num} is even')
    print(f'The number {my_num} is odd')
  my_num -= 1
while loop example with if, else and break

Therefore, the loop exits as soon as the variable my_num becomes 7.

Unlike break, continue will allow the loop to proceed but skip a certain action. Using the same example, with continue, we can skip the number 7:

while my_num > 0:
  if my_num == 7:
    my_num -= 1
  if my_num % 2 == 0:
    print(f'The number {my_num} is even')
    print(f'The number {my_num} is odd')
  my_num -= 1
while loop example with if, else and continue

However, we must still decrease the my_num variable by one; otherwise, we will create an infinite loop.


This tutorial examined Python keywords related to Boolean variables, conditional expressions, logical operators, membership checks, exception handling, and loop construction. This was the first one of a two-part subseries on Python keywords. The next tip will examine the keywords related to modules, classes, functions, coroutines, and others.

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About the author
MSSQLTips author Hristo Hristov Hristo Hristov is a Microsoft certified data professional, specializing in Power Apps, Power BI and Python.

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Article Last Updated: 2022-10-13

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