Python Cheat Sheet - A Guide for Beginner to Advanced Developers

Python is one of the most popular programming languages and its popularity is growing more and more. One of the best things about Python is that you can use it for a wide variety of purposes, such as web development, software development, game development, etc. Here are some of the key highlights of the Python programming language:

• Python is a multi-paradigm, general-purpose, object-oriented programming language.
• It is a cross-platform programming language, which means that a Python file can run across multiple platforms or operating systems in the same way.
• It is easy to learn.
• Simple syntax and akin to pseudocode.
• Comes with the Automatic Garbage Collection feature.
• Open-source and free to use.

In this Python cheat sheet, we will cover a wide range of Python concepts that you should remember as a Python developer. Also, we have provided relevant examples to help you understand the concepts better. Now, let's start this Python cheat sheet by discussing the applications and characteristics of Python.

Applications of Python

Python is a highly versatile language and it has applications in many IT fields such as:

• Web Development (back-end)
• Desktop Applications
• Data Science
• Machine Learning
• Artificial Intelligence

Characteristics of Python

Following are the major characteristics of Python:

• Simple programming language.
• Python has the most libraries.
• Supports object-oriented programming.
• Robust and secure.
• Highly scalable.
• Uses interpreter.
• Dynamic programming language.
• Supports multi-threading.

Best Python IDE’s

There are many IDEs available for Python, however, the following ones are the most recommended:

• PyCharm (By Jetbrains)
• Atom (Powered by GitHub)
• Visual Studio Code (By Microsoft)
• Spyder
• Jupyter Notebook

Online Python Compilers or Interpreters

We can use online Python compilers or interpreters to run a Python source code on any device without installing the Python. Following is a list of the best online Python compilers:

• OnlineGDB
• Replit
• Ideone
• JDoodle

Python Implementations

The most widely used Python3 offered by python.org is CPython, which is written in the C programming language. Apart from CPython, there are many other implementations of Python, such as the ones listed below:

• IronPython (Runs on .NET)
• Jython (Runs on Java Virtual Machine)
• PyPy
• Stackless Python (CPython Branch that supports micro threads )
• MicroPython (Runs on Micro Controller)

Standard Data Types in Python

Python has two data types:

• Base Type
• Container Type

Base Type

Examples

#integer (int): It represents all the integer numbers 
a = 23

#float (float): It represents all the decimal or floating point numbers 
b = 23.0

#Boolean (bool): It represents two Boolean values - True and False
c = True
d = False

#string (str): It represent a sequence of chracters
e = 'Hello World'
f = "Hello World"
g = '''Hello World'''
h = """Hello World"""

#bytes (bytes): It is a sequence of Byte chracters 
i = b"3"

Container Type

Examples

#List (list): A list is a mutable sequence of items.
a = [1,2,3,4,5]

#Tuple (tuple): A tuple is an unmutable sequence of items
b = (1,2,3,4,5)

#Dictionary (dict): Dictionary store items in the form of key:value pairs
c = {'x1':10, 'x2':40 ,'y1':3, 'y2':19}

#Set(set): A set is an unorder collection of unique items 
d = {1,2,3,4,5,6,7}

Python List

A list is a collection of different data types, and it stores all elements in a contagious memory location.

• Create a list

To create a list we use square brackets [ ].

Example:

lst = [100, 200, 300, 400, 500]

• Indexing

Python lists support indexing. With the help of indexing, we can access a specific element of a list.

Example:

>>> lst =[100, 200, 300, 400, 500]
>>> lst[0]
100
>>> lst[3]
400

• List Slicing

With list slicing, we can access a sequence of elements present in a list.

lst [start :  end : steps]

Example:

>>> lst[1:3]
[200, 300]
>>> lst[2:1000]
[300, 400, 500]
>>> lst[1:5:2]
[200, 400]

• List Unpacking

a, b, *c = lst

• Loop through a List

for i in lst:
    pass
for index, value enumerate(lst):
    pass

• Add Elements in a list

lst.append(600)
lst.insert(0,50)

• Remove Elements from a list

lst.pop()               #pop out last element
lst.pop(0)            #pop out element at index 0
lst.remove(200)                 #remove 200
del lst[3:]             #delete list all element from index 3

• If condition with a list

if 200 in lst:
    print(True)

• List Comprehension

lst_2 = [i for i in lst ]

• Condition inside a list comprehension

lst_3 = [i for i in lst if i %3 ==0]

• Zip function to combine two lists

a = [1,2,3]
b = ["i", "j","k"]
zip(a,b)

• Map and Filter on a list

str_lst = list(map(str,lst))
list_3_div = list (filter (lambda x : x%3 ==0 , lst))

List Operations

Python Tuples

A tuple in Python is similar to a list. However, the only difference between a tuple and a list is that tuples are immutable.

• Create a tuple

tup =  (1,2,3,4,5,6)

• Convert a list into a tuple

lst = [1,2,3,4,5,6]
tup= tuple(lst)

• Indexing In tuple

print(tup[1])

Python Arrays

Python does not have inbuilt support for arrays, but it has a standard library for the array data structure.

• Create an Array

from array import array
arr = array('i' , [1,2,4])
arr[2]
4

Python Sets

A Python set is similar to a set in mathematics.  Also, a Python set does not hold duplicate items and we can perform the basic set operations on set data types.

• Create a Set

s = {1,2,3,4,5,6,7}
s2 = {1,3,6,9}

Basic Set Operations

Dictionary

A dictionary is a collection of key-value pairs , and the key could only be an immutable data type.

• Create a dictionary

dic = {1:2, 3:6 , 4:8, 5:10}

• Convert a list into a dictionary

lst = [(1,2), (2,4), (3,6)]
dict(lst)

• Accessing Dictionary Elements

We use a key to access its corresponding value in the dictionary.

>>> dic = {"hello": "greet", "go":"there"}
>>> dic['go']
'there'

• Looping through a dictionary

for key, value in dic.items():
    print(key,value)

Python String Escape Characters

An Escape character allows us to insert illegal characters in a string, such as a tab, single quote inside a single quote string, etc.

Python String Formatting

With string formating, we can put variables data value inside strings.

• String formatting using f prefix

The latest versions of Python support string formating using the f prefix.

Example

a = 2
b = 3

print(f"The value of a is {a} and the value of b is {b}")

Output

The value of a is 2 and the value of b is 3

• String formatting using format method

The string object also supports the format method to format a string value.

Example

a = 2
b = 3

print("The value of a is {0} and the value of b is {1}".format(a, b))

Output

The value of a is 2 and the value of b is 3

Python Operators

Arithmetic Operators

There are various arithmetic operators in Python that are listed in the table below:

Example

a = 2
b = 4

#addition operator
print('a+b = ', a+b)

#subtraction operator
print('b-a = ', b-a)

#multiplication operator
print('a*b = ', a*b)

#division operator
print('a/b = ', a/b)

#floor division
print('a//b = ', a//b)

#modulo operator
print('a%b = ', a%b)

#Exponential operator
print('a**b = ', a**b)

output

a+b = 6
b-a = 2
a*b = 8
a/b = 0.5
a//b = 0
a%b = 2
a**b = 16

Comparison Operators

There are several operators in Python that you can use to compare two objects or values and return a Boolean value, i.e. True or False:

Examples

a = 2
b = 4

#smaller than operator
print('a<b = ', a<b)

#greater than operator
print('a > b = ', a>b)

#smaller than and equal to operator
print('a<=b = ', a<=b)

#greater than and equal to operator
print('a>=b = ', a>=b)

#not equal to division
print('a!=b = ', a!=b)

#Equal to comparion operator
print('a==b = ', a==b)

Output

a<b = True
a > b = False
a<=b = True
a>=b = False
a!=b = True
a==b = False

Logical Operators

Python has three logical operators:

• and (returns True if and only if both the conditions are True)
• or (returns True if either of the conditions is True)
• not (returns True if the condition is False and vice versa)

Examples

#and operator 
print('2>1 and 2>=2: ',2>1 and 2>=2 )

#or operator
print('2<1 or 2<=2: ',2<1 or 2<=2 )

#not operator 
print('not(2 > 3):', not(2 > 3))

Output

2>1 and 2>=2: True
2<1 or 2<=2: True
not (2 > 3): True

Python Identifiers and Keywords

An identifier is a name given to an object. Identifiers are also known as variable names. There are some rules associated with an identifier or variable name. By using identifiers, we can give a name to variables, functions, modules, and classes.

Identifiers Rules

• The first letter of an identifier could be a lowercase or uppercase alphabet or _ (underscore symbol), and it could be followed by any alphabet, digit (0,9) and _.
• There should be no special symbol in an identifier except _ (underscore).
• You cannot use reserved Python keywords as identifiers.

Python Keywords

Keywords are the reserved names in Python, and there are a total of 33 keywords in Python 3 that are listed below:

Variable Assignment

We use the equal to "=" symbol to assign an object to an identifier. The identifier name should be on the left side and the value on the right side of the assignment operator.

Example

x =20

Python I/O

Example

>>> print("Hello", end = "**")
>>> print("world")
Hello**world
>>> input("Enter a Number: ")
Enter a Number: 20
'20'

By default input() accepts a value as a string.

Type Conversion

There are many reserved keywords in Python you can use to convert the data type of a variable.

Indexing Calling in Python

In Python, string, list, and tuple objects support indexing calling. An index is an integer number. Indexes of the items within an object are available from 0 to n-1 , where n is the total number of items or characters present in the object.

Example:

>>> lst = [100, 200, 300, 400, 500 ,600]
>>> # all items of list
>>> lst[:]
[100, 200, 300, 400, 500, 600]
>>> #all items of list from index point 1 to last
>>> lst[1:]
[200, 300, 400, 500, 600]
>>> # Index slicing
>>> lst[::2]
[100, 300, 500]
>>> # reverse the elements of a list
>>> lst[::-1]
[600, 500, 400, 300, 200, 100]
>>> # last element of the list
>>> lst[-1]
600

Boolean Logic in Python

In Python, we often encounter Boolean values when we deal with comparison operators and conditional statements.

Types of Boolean

There are two types of Boolean values:

• True
• False

Generator Comprehension

Like a list comprehension, we have generator comprehension for which we use parenthesis () instead of square brackets [].

Example

values = (x * 2 for x in range(10000))
for x in values:
    print(x)

Python File Handling

To read or write data to a file, we can use the Python context manager with keyword. By using the with keyword and open function, we can open a file in different modes mentioned in the table below:

Example 1

To open and read from a file

with open('data.txt', 'r') as file:
    #read the complete file as a string
    print(file.read())

Example 2

Open and write into  a file

#write into the file
with open('data.txt', 'w') as file:
    #write into a file
    print(file.write('Hi there.. welcome to techgeekbuzz'))

Example 3

Open and append into  a file

#append into the file
with open('data1.txt', 'a') as file:
    #write into a file in append mode
    print(file.write('Hi there.. welcome to techgeekbuzz'))

Packages and Modules in Python

A package in Python is a collection of multiple Python modules. On the other hand, a Python module is a Python file that contains source code. To define a Python package, we have to create an empty __ini__.py file in the package directory. To use the modules from different packages, we have to import them into our script using from and import keywords.

Modules Name and Import

Python Math Module

Math is the most important and widely used standard module of Python. It provides many methods related to mathematical operations.

Conditional Statement

A conditional statement in Python consists of 3 keywords - if, elif, and else.

Example

if x == 1: 
    print("a")
elif x == 2: 
    print("b")
else:  
    print("c")

Ternary operator

Python Ternary operator is a shorthand to write the conditional statement as a single line of code.

Example

# Ternary operator
x = "a" if n > 1 else "b"

# Chaining comparison operators
if 20 <= age < 45:

Loops

There are two loops statements available in Python:

• for loop
• while loop

Example

#for loop

for n in range(10):
    print(n)

#while loop

while n < 10:
    print(n)
    n += 1

Break

It is a statement used inside the loop statement to terminate the loop flow and exit from the loop immediately.

Example

for n in range(10):
    print(n)
    if n > 5:
        break

Continue

Continue is the opposite of break, and it is used in loop statements to directly jump to the next iteration.

Example

for n in range(10):
    if n > 5 and n < 7:
        continue
   print(n)

Function

To create a user-defined function in Python, we use the def keyword. Also, to exit from a function, we return a value using the return keyword.

Example

def add(a, b):  
    return a + bb
# Keyword arguments
add(2, 4)
# Variable number of arguments
def multiply(*numbers):
    for number in numbers:
        print (number)
multiply(1, 2, 3, 4)
# Variable number of keyword arguments
def save_user(**user):
    print(user)
save_user(first_name= "Sam", last_name="smith")

Exception Handling

With exception handling, we deal with runtime errors. There are many keywords associated with exception handling, such as the ones mentioned in the following table:

Example

# Handling Exceptions
try:
    #try block
except (ValueError, ZeroDivisionError):
    #except block
else:
  # no exceptions raised
finally:
  # cleanup code

Python Class

Classes enable Python to make use of object-oriented programming concepts.

• Create a class

class Employee:
    pass

• Create a constructor for a class:

The constructor is a special method of classes that gets executed automatically during the object creation of a class.

class Employee:
    def __init__(self):
        self.val = 20

Magic Methods of class

Class Private Members

Conventionally, to declare a private attribute, we write its name starting with __ (double underscore). Example

class Employee:
    def __init__(self):
        self.val = 20
        self.__sal =40000

Inheritance

With inheritance, we can use the methods and properties of another class:

Example

class Employee:
    def __init__(self):
        self.id = 20
class Manager(Employee):
    def __init__(self):
        self.__sal= 200000

Multiple Inheritance

class Employee:
    def __init__(self):
        self.id = 20
class Manager:
    def __init__(self):
        self.__sal= 200000
class Sam(Employee, Manager):
    def __init__(self):
        pass

Basic Generic Operations on Containers

Virtual Environment in Python

A Python virtual environment creates an isolated environment for a project where we can install and uninstall packages, frameworks, and libraries without affecting the actual Python environment. To create a Python environment, we can use the built-in Python venv module.

python -m venv myProject

The above terminal command will generate a new virtual environment in the directory myProject . After creating the virtual environment, we need to activate it. The activation script of the virtual environment exists inside the virtual environment's Script directory.

my_project\Scripts\activate

The above command will activate the newly created virtual environment in the myProject directory. To deactivate the environment, we can simply execute the deactivate command on the terminal or command prompt.

To Sum it Up All

We hope that this comprehensive Python Cheat Sheet will help you learn various important concepts in Python. Also, with this cheat sheet, you can easily go through the important aspects of Python that are essential for writing Python code. If you have any suggestions or queries related to this Python cheat sheet, you can share them with us in the comments section below.

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