Python Fundamentals for Beginners

As mentioned in my previous blog, Python is one of the most popular programming languages in the world. There is a huge, increasing demand for Python professionals in many fields.

The fields include Data Science, Data Analytics, Machine Learning, Deep Learning, MarTech Automation(including SEO Automation, Content Writing Automation, Email Automation), and much more.

This free beginner’s guide will help you to grow from Zero to Programming in Python. You need absolutely no prior programming experience while going through the guide! Just a bit of familiarity with computers!

You will get a stable foundation by the end of this blog, to level up your Python programming skills further. Let’s begin our learning journey.

What is Python? Introduction to Python

Python is a high-level, interpreted language. Guido van Rossum was the main person behind the development of the language.

He published his first code in February 1991. The main features of Python are:

• It is easy to code, developer-friendly language.
• It is free and open-source. You don’t need permissions.
• Python supports Object-oriented programming(OOP).
• It is a portable language too: Write code once and for all.
• It is a case-sensitive language: easy to comprehend.
• Large standard libraries provide a lot of modules and functions.

How to Install Python Step by Step?

In SEO the main use of Python comes into Data Extraction or Web Scraping, Data Analysis and Automation.

In order to start working on Python SEO tasks on your device, you need to install the latest version of Python from a trusted source.

As it is an open-source language, there can be many ways to install Python. The source is available in the public domain to use, copy and share.

Download the latest Python version

To simplify the process, go to the official website of Python and download the required version as per your device specification. You can also check the download link given below

After downloading, just follow all the instructions in order. This way, Python will be easily installed into your device.

Check if Python is installed?

If you have correctly followed all the instructions, you will now have successfully installed Python on your system. To check:

1. Go to “Start Menu”.
2. Open “Command Prompt”.
3. Type the following command:

python --version
Python 3.9.9

If you get something like 3.x.x or 2.x.x as the output, this means you are ready to use Python.

You can now run Python commands in your system and learn further with real-time hands-on using the Python command lines.

Python Basics

Every language is built upon some basic components. To start learning Python, you need to know about the different components of Python language with their meaning.

Now you get to know about the terminology of Python. It includes data types, variables, comments, and various operations on data and strings.

Variables in Python

Do you remember variables x, y, z, etc. from Mathematics?

Similarly, in Python also, variables are used to store some information to be referenced and modified while working in a computer program.

Unlike other languages, Python does not need to explicitly declare a variable. When you assign a value, of a certain type, to them they are declared at the same time.

There can be different data types of variables which are explained further.

Data Types in Python

A type is a way Python represents different types of data we work on. There can be many types of Data.

The four primary types of data in Python are:

The other data structures can be made using these data types as fundamental units. You will get the overview in the next section

To check the data type of a variable, use the following command:

type(variable_name)

Now try out the following code in your machine and check the output. I have displayed the output in the following figure.

a = 10
b = 10.0
c = "Python SEO Fundamentals"
d = True

print(
      " data type of a:",type(a),
      "\n","data type of b:",type(b),
      "\n","data type of c:",type(c),
      "\n","data type of c:",type(d),
     )

Output of the above code:

Comments in Python

To make code understandable, programmers use comments to explain the code.

You can create a comment by using the pound (#) sign before your text.

# This is a comment
print("This is a normal line")

In the above code, the first line will not be executed by the interpreter.

You can also make a multi-line comment in Python by using enclosing your comment in triple quotes:

"""
This is going
to be a multi-line
comment in Python
"""
print("The above 3 lines are ignored")

Output of the above code:

Data Structures in Python

Data Structures are an important part of a programming language. They are responsible for efficient data management.

Although Python holds the power of high-end data structure libraries like Pandas, it has four basic in-built data structures that cover almost 80% of real-world requirements. Let’s take a brief look at them.

1. List:
   • It is the most versatile and commonly used collection object type in Python.
   • Since lists are mutable, you can perform operations like slicing, concatenation very easily.
   • List satisfy the need of most of the collection data structures available in other languages.
2. Dictionary:
   • It is the alternate of maps in other languages like Java e.g. Hashmap.
   • It is used to store data which is in the form of key-value pairs.
   • The keys in a dictionary are unique and immutable objects.
3. Tuple:
   • A tuple is generally a collection of comma-separated Python objects.
   • They are exactly like Python List but are immutable.
   • The similarity with List includes indexing, nested objects, and repetition.
4. Set:
   • Set is an unordered collection comprised of unique objects.
   • You can do operations like union, intersection, and difference on Set objects.
   • They are based on a hash table, which is highly optimized.

Now try out this code on your machine, and check what you get in the output.

example_list = ['title','description','header','url','content']
example_tuple = ('ahrefs','semrush','search engine journal','backlinko')
example_set = {'seo','python','content','automation','marketing'}
example_dict = {"name":"author","country":"india","work":"blogging"}

print("",
    type(example_list),": ",example_list,"\n",
    type(example_tuple),": ",example_tuple,"\n",
    type(example_set),": ",example_set,"\n",
    type(example_dict),": ",example_dict
    )

Output of the above code:

Here is a quick recap of Python collection data types, summarizing their properties:

Now you have a basic idea of in-built Python data structures. Later on, you will get to know about their methods, and detailed operations available in Python.

Operators in Python

Operators are used to perform different types of operations on values, and variables. There are many types of operators available in Python as:

Out of so many operators, many of them are used rarely, on specific requirements only.

Here is the list the most frequently used Python Operators with a quick description:

Now you are familiar with Python, let us take a brief look at some Python programming fundamentals. Here you will understand how to combine different Python components to make a useful Python Program.

Programming Fundamentals in Python

Almost everybody has started their coding journey with a “Hello World!” program. Let’s begin our learning with small Python programs.

Print something in the output

print(str) is an inbuilt function in Python that takes a string as an argument. Using this function, we instruct the interpreter to print the argument passed in the print function.

print("Hello Python Fundamentals for SEO and Automation!")
#output Hello Python Fundamentals for SEO and Automation!

Type conversion from one object type into another

Python supports typecasting, which means interchanging the type of a variable when required. For example, converting [int -> float] or [int -> str] etc.

type(3) # verify that this is an integer type

#typecast 3 into float, and check again 

type(float(3)) #the output will be 'float'

Also remember, not all type conversions are possible. For example:

If you want to convert a float into an int, you might lose some data as it will give the nearest round off of the original value.

Another example: If you try to convert a string into float or int that is not a perfect match for that data type, it will give an error.

int(3.6) # it will give 3 as output

int('1 two') # it will produce "Value Error"

Python Expressions

Expressions in Python means operations among values of compatible data types (e.g. integers or floats) using different Python operators.

#example 1
40 + 16 + 7 + 8 # gives output 71

#example 2
distance = 200
time = 3
speed = distance/time
print("speed: ",round(speed,2),"km/h") # gives output => speed:  66.67 km/h

For more complex operations, we can use ( ) to couple multiple variable together and perform operations. For example:

Maths = 30
Science = 49
Computer = 46

Average = (Maths + Science + Computer)/3
print(round(Average,2)) #print 41.67

Working with Python Strings

Most of the SEOs are involved with a large amount of content. Whether it is from a competitor’s website or our own website. This means we need to know how to handle the content aka “Strings in Python”.

Strings is a combination of characters enclosed within either ” “(double inverted comma) or ‘ ‘(single inverted comma). The character can be anything like digits, alphabets or special characters.

str_digits = "1 2 3 4 5"
str_sp_ch = "!@#$%^&"
str_alpha = "this is an ideal string"
str_al_num_sc = "hY8r!d $+r!n6"

Output of the above code:

String Traversal and Indexing

While working with a string, think of it as an ordered sequence of characters. You can access each element of the string using its index, represented by the array of numbers as shown:

The index starts with 0 and increases gradually until the last character.

Name = "Michael Jackson"

print(Name[0]) # print first element in the string i.e. M

print(Name[8]) # print J

print(Name[-2] # print o
"""
This is called negative indexing: accessing a string from its end.
"""

Length of String

While working on On-page SEO, we usually focus on the length of the title, meta description, heading, and URL length. How do we get that using Python?

We use the inbuilt Python function, len(str), to find the length i.e., the total number of characters in the string.

len(Name) #print 15

Slicing a String

We can extract a slice from a string using slicing. To get a part of the string, you need the start index and the end index(excluded) of the slice separated by “:”

Continuing with our example of Name, we can obtain the first name and last name as follows:

first_name = Name[0:7] #store Michael into the variable
last_name = Name[8:15] #store Jackson into the variabe

Concatenate Two Strings

You can combine or concatenate two strings using a “+” operator. It is used whenever you want to attach data into a previously existing string or a new string.

str1 = "Learn Python SEO"
str2 = "from scratch"
str3 = str1 + " " + str2 
print(str3) # print a new string: Learn Python SEO from scratch

Escape Sequences in String

Escape Sequences are used to insert characters that are normally difficult to be placed inside a string.

An escape sequence starts with a ‘\’ (backslash), followed by the required escape character. Some common escape sequences are given below:

Different String methods

There is much more that you can do with Python Strings. But that is out of the scope right now. So I am sharing them in brief. Some popular String methods are:

Working with Python Lists

A list is a collection of multiple items stored using a single variable. It is used to efficiently store data as arrays do in other languages e.g. Java, C++, etc.

You can also store values of different data types like string, integer, boolean, etc. together into a list.

We can create a list by enclosing our list items inside square brackets ( [ ] ) and assigning them to a variable name.

When you use the type( ) function with that variable, you will get <class ‘list’> as an output. This means lists are defined in Python as an object with the data type of ‘list’.

For example:

#list containing marks of 5 subjects
marks = [36, 44, 49, 43, 42] 

#data type of a variable containing a group of objects within [ ].
type(marks) #output: <class 'list'>

#list of subjects
subjects = ['maths','physics','biology','chemistry','english']

#list of popular blogs
blogs = ['semrush','ahrefs','hoth','neilpatel','backlinko']

#list containing items of different data type
mix_list = [3, ['a','b'], 'learn', '$','P','y','t','h','o','n']

Indexing and Accessing List items

Most of the functions of traversing in a list are similar to that of a String.

Since the list is an ordered collection, you can access any list item by referring to its index number.

Also, you can access elements from the end of the list to the starting using Negative indexing reference.

#taking blogs list from the last example and printing the second blog name
blogs[1] #output:  'ahrefs'

#getting 2nd blog from the end of the list
blogs[-2] #output: 'neilpatel'

Getting the length of the list

You can get the total number of items in the list using ‘len( )‘ function:

#print the length of mix_list from above example
print(len(mix_list))     #output: 10

Slicing a List

You can also fetch a list slice using the start, end index generally called a Range.

Also, you can make a stride selection as well. A stride selection involves picking items that are present at a fixed gap.

Let’s understand slicing with an example.

arr = [ 1,2,3,4,5,6,7]

print(arr[0:4])
#output: [1,2,3,4] => slice within range(0,4)(4 excluded)
print(arr[0:7:2])
#output: [1,3,5,7] => slice with every second element within range(0,7)

You can also make a slice by using just one index i.e. either start index or end index. Python automatically understands the remaining index to be the end of the list or start of the list respectively.

print(arr[:6]) #output: [1, 2, 3, 4, 5, 6] (from start till 5th place)

print(arr[2::2]) #output:[3, 5, 7](every second element from 2nd till last)

Most Useful List Manipulation Techniques

The list is the most commonly used data type to store data and perform data manipulation.

Based on the insights from the above information over lists, we now learn a few useful manipulations on Python Lists.

Change single item inside a list

Since lists are mutable, we can change them as per our requirement using the index reference.

year = [2017,2018,2020,2020,2021,2022] 
year[2] = 2019 #value at position 2 modified to 2019
print(year)
#output: [2017, 2018, 2019, 2020, 2021, 2022]

Change a range of items inside a list

To do so, you need to define a new list which contain new values. Now you refer that list to the range of index you want to change.

colors = ['red', 'c', 'python', 'java', 'black', 'orange',]
colors[1:4] = ['white', 'brown', 'green'] #replace items in range(1,4)
print(colors)
#output: ['red', 'white', 'brown', 'green', 'black', 'orange']

Note: If you choose a range larger than the number of changed items, then your original list size will reduce.

Concatenate two lists

You can join or concatenate two lists in Python by using a ‘+’ operator.

list1 = ['2000','2001','2002']
list2 = ['2020','2021','2022']
list3 = list1+list2
print(list3) #output: ['2000', '2001', '2002', '2020', '2021', '2022']

Split a list into sublists

To split a list into sub-lists, we can utilize our knowledge of slicing a list.

items = ['prefix', 'url', 'suffix', 'get', 'post', 'send', 'receive']
href = items[:3]
data = items[3:]
print(href) #output: ['prefix', 'url', 'suffix']
print(data) #output: ['get', 'post', 'send', 'receive']

Useful List Methods in Python

In Python, there is a large set of in-built methods to be used on list. Here is the collection of commonly used List methods

Working with Python Dictionaries

Lists data structure performs well with independent data items. But what to do with the data items that exist in the form of key-value pairs?

So, Dictionaries in Python are used to store data that exist in key-value form. The most common example that you can relate to is JSON files.

You can create a dictionary by arranging key value pairs inside curly braces( { } ).

dict = {
"name":"author",
"country":"india",
"language":['English', 'Hindi'],
"name":"maxx"
}
print(dict)
#output: {'name': 'author', 'country': 'india', 'language': ['English', 'Hindi']}

If you take a close look at the above example, I have stored a list of items as a value for the ‘language‘ key. This means that you can store any kind of data value inside a Python Dictionary.

Also, one more observation is there. dict has changed the second mention of the ‘name‘ key to an updated value.

This concludes that a Dictionary can’t have two items under a common key name as keys are unique in a dictionary.

Length of a dictionary

You can get the length of a dictionary object by using the len( ) function.

len(dict) #output: 3

Accessing items of a dictionary

We get the meaning of some words into an English dictionary by looking for the keyword.

Similarly, in Python, we can get the items by referring to the key. Also, we can use an inbuilt dictionary function called get( ).

print(dict['name'])
print(dict.get('name'))
#output for both queries: author

Accessing all the keys and values at once

Sometimes we want to get all the values of either keys or values or all the dictionary items altogether. Python has inbuilt dictionary methods for these tasks also. These are:

print(dict.keys())
#output: dict_keys(['name', 'country', 'language'])

print(dict.values())
#output: dict_values(['author', 'india', ['English', 'Hindi']])

print(dict.items())
#output: dict_items([('name', 'author'), ('country', 'india'), ('language', ['English', 'Hindi'])])

Add a new item or update an existing item

If you want to add a new item, you can do that using a new key and assigning a value to that key.

You can also update existing keys in the same manner. Just get to the key and assign the updated value.

Python also has an inbuilt method: update( ) for the above task. You can alternately use that as well.

dict['position'] = 'CEO' #this will add a new key 'position'

dict.update({'name':'admin'}) #this will update the value of 'name'

Useful Dictionary methods in Python

You have already take a look at some methods already. Here is a summarized list of common Python Dictionary

Indentation in Python

Before going to the next section, you need to know the importance of indentation in Python.

Other languages like C, Java, C++, use { } (curly braces) to enclose certain lines of code to be executed when the condition matches.

#Java Code
if(true){
System.out.print("True");
}
else{
System.out.print("False");
}

#Python code

if(True):
    print("True") #indentation
else:
    print("False") #indentation

As shown above, Python does not use curly braces.

Instead, it just uses indentation: White space at the beginning of the line, before the code.

So, take special care of proper indentation to get the right results while working with conditional statements

Understanding Python Conditional Statements

When we do the computation, we face many situations where we move ahead following some logic.

Similarly, conditional statements provide a programmatic approach to applying mathematical logic to variables. This is where boolean logic comes into play. You will gradually know how to.

In Python language, we can implement conditional logic in different ways. We can use IF…ELSE blocks, WHILE or DO…WHILE blocks or FOR loops as necessary.

Certain logical operators are regularly applied to test these conditions on variables:

Let’s begin understanding with IF…ELSE blocks

Using IF… statements in Python

We use the “if” keyword to write an if statement.

To brief the working of “if” statement, we can say that:

if the “given condition” is true, perform all the operation written inside the “if” indentation.

x = 20
y = 30
if y > x: #indented code will get executed if "y>x"
    print(y-x) #output: 10

Using IF…ELSE statements in Python

There comes a situation when the condition in the if block is false. To handle that situation we use “else”. This means

If the “given conditions” do not match then do the operations written in “else” indentation.

x = 200
y = 30
if y > x: #indented code will get executed if "y>x"
    print(y-x)
else:     #else block runs when the above condition fails
    print("y is smaller than x")

Making a Nested IF…ELIF…ELSE statement

This kind of statement is used to check multiple expressions and perform accordingly.

‘elif’ is short from of ‘else if’. This means if the condition for ‘if’ turns False, then the interpreter will check the condition in the first occurrence of ‘elif’.

It exits the whole ‘if…elif…else‘ block either at the last ‘elif’ condition or after else. Let’s take an example to know more:

#Try the program using different values for num variable

height = -3

if height > 5:
    print('Tall')
elif height <=5 and height >3:
    print('Medium')
else:
    print('short')

#This program will print Tall/Medium/short based on the height value

Understanding Loops in Python

Generally, loops are used where there is an iteration of tasks. For example, printing a table of 10.

Python supports the following loop commands:

• while loop
• for loop

Let’s understand each one of them briefly

Using WHILE loop

You can execute a set of statements, as long as the condition in a while loop stands TRUE.

var = 1           #initialize a variable
while var<=10:    #Test if condition is true
    print(var)    #perform statement 1
    var += 1      #perform statement 2
                  #exit the loop when condition no longer valid

Using FOR loop

We use for loop to iterate over a sequence inside an object(list, tuple, dictionary, string, etc.)

One good thing: Unlike other languages, Python has the most concise for loop expression.

#example 1: TO print all the items inside a list
websites = ['geeksforgeeks','tutorialspoint','javatpoint','programiz']
for item in websites:
    print(item) #print all the list items

#example 2: To print the square of items in a given range
for i in range(1,10):
    print(i*i) #print the squares of 1 to 9

The range( ) function is used to work on a range of numbers from a starting value till end value-1;

Understanding Python Functions and Arguments

A function is a self-contained block of code, which only runs when it is called. Functions are a classical example of code reusability.

Once created, a function can be called any number of times. You can design functions that accept some arguments as input return something as an output, but it’s not mandatory.

In Python, you can create a function by using the def keyword, followed by function name and arguments(if any).

#function1: no argument passed
def show_title():
    print("Python SEO Beginners Tutorial")

show_title() #output: Python SEO Beginners Tutorial

#function2: with two arguments of type string
def fullname(fname,lname):
    print(fname+" "+lname)
    
fname = "J K"
lname = "Rowling"
fullname(fname,lname) #output:J K Rowling

In the above example, observe the second function. You have stored the first name and last name into two separate variables.

After, by just calling the function name, passing the arguments, you get the full name in the output with just one line of code i.e function call.

Understanding Python Classes and Objects

Python is an object-oriented language which means most of the elements of Python language are objects with unique individual properties and methods.

What is a Class?

You can understand a class as a blueprint for creating objects having user-defined variables and methods. A class determines the skeleton and behavior of its object.

What is an Object?

An object is an element that holds all the properties of the class, as described in the blueprint.

class Car:  #define a Car object, its attributes, and behavior
    #defining object attributes
    def __init__(self, year, make, price):
        self.year = year
        self.make = make
        self.price = price
        
    #defining object method
    def details(self):
        print(str(self.year)+" "+self.make+" "+str(self.price))

car1 = Car(2019,"Toyota",1000000) #make aobject instance of class Car
print(car1.year)
print(car1.make)
print(car1.price)
print(car1.details())

Similarly, you can create any desired class and use its object instances later on. You can also import classes of one program into another program.

How to take user input into Python?

By taking user input, you can make Python programs more interactive, and more lively.

Python has a default method to take the input from a user: input( )

When it is called, the method stops the program execution. When the user enters the input and press enter, it starts the further execution of the program if the user has entered the data of the right data type.

name = input("Enter name of employee:")
print(name)

Popular Python Development Tools

Now that you have gone through so many things, it’s time to introduce with Python toolkit.

Python IDEs

IDE stands for Integrated Development Environment. They are very important to write programs and execute them for testing and development purposes. The IDEs are useful tools from the aspect of software development and web development.

The most popular IDEs and code editors of Python in 2022 are:

1. IDLE: Best tool for beginners who are in their learning phase
2. Sublime: An advanced code editor with syntax highlighting and code formatting features.
3. VS Code: A full-fledged customizable IDE with all necessary tools for Python developer requirements
4. Spyder: Open Source IDE. Comes with Anaconda Packet Manager.
5. Jupyter Notebooks: Web-based IDE with an interactive computational environment.
6. Google Colab: A free Python Notebook environment, running entirely in the cloud.
7. PyCharm: Python-specific IDE, for Data Science and Web Development

Python Virtual Environments

They are used to create projects related to data science, web, and server projects. They provide a separate environment to install Python packages and dependencies in an isolated manner.

Some common Python VEs include:

1. Anaconda: The topmost platform for simplifying Python package management and distribution.
2. Docker: Provide a containerized virtual environment for Software Development and delivery.

Python Packages and Libraries

Python packages and libraries are the heart and soul of Python Language. Even a small Python software involves multiple big or small libraries working from behind.

In the previous blog, I have mentioned some of the most popular libraries. You will come to know more about them in upcoming blogs.

Here’s a list of the popular Python libraries in 2020 technology trends:

1. Mathematics and Computation
   • NumPy
   • SciPy
2. Data Analysis and Manipulation
   • Pandas
   • PySpark
   • Dask
3. Graphs and Plotting
   • Matplotlib
   • Plotly
   • Seaborn
4. Machine Learning
   • Scikitlearn
   • TensorFlow
   • Pytorch
5. APIs and Web Development
   • Django
   • Flask

Here I conclude the fundamentals of Python. With this much knowledge, one can now write and understand basic Python programs.

Check out the GitHub Repository for this blog to get all the code snippets mentioned above.

FAQs for Python programming

We will discuss more about Python SEO programming in the upcoming blogs. Till then, Good Luck!