As a programmer (or would-be programmer), you will at some point lookout for a language that is easy to learn, cross-platform, has great developer community support, and has good in-built features that could help you develop your applications quickly. One of those languages is Python.
Python is a ubiquitous programming language that has a wide variety of applications. From machine learning to web development, the Python language finds uses in industries and companies most of you are already familiar with.
This step-by-step guide will take you through the ins and outs of the Python programming language. It covers what Python is, where it is used and why it is so popular, how to install Python, as well as some fundamentals of the language.
What is Python Programming Language?
The Python language type is a high-level, dynamically typed one that is among the most popular general-purpose programming languages. It is among the world’s fastest-growing programming languages and is used by software engineers, mathematicians, data analysts, scientists, network engineers, students, and accountants.
Python is also interpreted and object-oriented. It is called an interpreted language as its source code is compiled to bytecode which is then interpreted. CPython usually compiles Python code to bytecode before interpreting it.
Why is Python Popular?
Python’s features, among other things, are what make it popular. For instance, It supports dynamic typing and dynamic binding. In languages like Java, C, and C++, you cannot initialize a string value to an int variable and in such cases, the program will not compile. Python does not know the type of the variable until the code is executed.
Python has an easy syntax that enhances readability and reduces the cost of code maintenance. The code looks elegant and simple.
Here’s a summarized list of why Python is popular:
- The Python framework also has modules and packages, which facilitate code reusability.
- Open source: You can download Python for free. You can also read and modify the source code.
- No code compilation: the cycle of edit-test-debug is fast
- Exception handling: Any code is subject to an error. Python generates exceptions that can be handled hence avoiding the crashing of programs.
- Automatic memory management: Memory management in Python involves a private heap (a data structure that represents a queue) containing all Python objects and data structures.
How Long Does it Take to Learn Python?
Despite its versatility and wide use, Python is actually one of the easier languages to learn. If you take a look at the same code for a simple program written in 3 different languages, chances are Python will require the fewest lines of code, besides being “human-readable.”
It is very well possible to learn the fundamentals of Python, and begin your own projects, in a matter of 3 - 6 months. This will vary depending on the individual’s ability and how much effort you put into it, but rest assured, if you’re learning to program, the Python language is one of the easier options.
Recommend Python Course
Complete Python Bootcamp From Zero to Hero in Python
What is Python Used For?
The uses of Python are varied and quite impactful. Here is a list of fields where Python is commonly used:
Web Development
As a web developer, you have the option to choose from a wide range of web frameworks while using Python as a server-side programming language. Both Django and Flask are popular among Python programmers. Django is a full-stack web framework for Python to develop complex large web applications, whereas Flask is a lightweight and extensible Python web framework to build simple web applications as it is easy to learn and is more Python-based. It is a good start for beginners.
Application giants like Youtube, Spotify, Mozilla, Dropbox, and Instagram use the Django framework, whereas Airbnb, Netflix, Uber, and Samsung use the Flask framework.
Machine Learning
As Python is a very accessible language, you have a lot of great libraries on top of it that make your work easier. A large number of Python libraries that exist help you to focus on more exciting things than reinventing the wheel. Python is also an excellent wrapper language for working with more efficient C/ C++ implementations of algorithms and CUDA/cuDNN, which is why existing machine learning and deep learning libraries run efficiently in Python. This is also super important for working in the fields of machine learning and AI.
Data Analysis
Python has tools for almost every aspect of scientific computing. The Bank of America uses Python to crunch its financial data and Facebook looks upon the Python library Pandas for its data analysis.
While there are many libraries available to perform data analysis in Python, here are a few to get you started:
- NumPy: For scientific computing with Python, NumPy is essential. It supports large, multi-dimensional arrays and matrices and includes an assortment of high-level mathematical functions to operate on these arrays.
- SciPy: This works with NumPy arrays and provides efficient routines for numerical integration and optimization.
- Pandas: This is also built on top of NumPy, and offers data structures and operations for manipulating numerical tables and time series.
- Matplotlib: A 2D plotting library that can generate data visualizations as histograms, power spectra, bar charts, and scatterplots with just a few lines of code.
Games
Python and Pygame are good languages and frameworks for rapid game prototyping or for beginners learning how to make simple games. Pygame is a free and open-source Python programming language library for making multimedia applications like games.
The famous Disney multiplayer online role-playing game Toontown Online is written in Python and uses Panda3D for graphics. Battlefield 2, a first-person shooter military simulator video game, uses Python for all of its add-ons and a lot of its functionality. Frets on Fire, an open-source Finnish music video game, is written in Python and uses Pygame.
Desktop Applications
As a part of the Python standard library, Tkinter allows you to create small, simple GUI applications. The PyQt library is most useful for desktop creation python bindings for the Qt (C++ based) application development framework. The PySide library is the python binding of the cross-platform GUI toolkit Qt.
Who Uses Python Today?
Now that you’ve seen the wide variety of uses for Python, you won’t be surprised to know that every entity, from the largest tech companies to government agencies, uses Python.
Companies that use Python include Google, Netflix, Facebook, PayPal, Uber, Spotify, Reddit — and so many more!
Python Compared to Other Languages
While Python is an excellent language for beginners and is very versatile, it’s not without its flaws. Some programming languages are inherently better for some purposes, and it’s worth knowing how the Python language fares against others.
Java and C++
Python typically runs slower than Java and C++, even if the code size and development time is shorter. This is partly because Python is a dynamic binding language. It has a syntax that uses simple functions and variables.
Perl
Python and Perl come from a similar background, which is essentially Unix scripting. Perl emphasizes support for common application-oriented tasks, such as extracting information from a text file, report printing, text file conversions into other formats. Python emphasizes support for common programming methodologies such as data structure design and object-oriented programming and encourages programmers to write readable (and thus maintainable) code by providing an elegant syntax.
Tcl
Like Python, Tcl is used as an application extension language, as well as a stand-alone programming language. However, Tcl is weak when it comes to data structures and typically executes code much slower than Python. Tcl also lacks features needed for writing large programs, hence a large application using Tcl usually contains extensions written in C or C++ that are specific to that application, and an equivalent application can often be written purely in the Python language.
Smalltalk
Like Python, Smalltalk also has dynamic typing and binding, and everything in it is an object. Smalltalk's standard library of collection data types is superior, while Python's library has more facilities for dealing with Internet and web requirements such as email, HTML and FTP.
How to Install Python
Installing Python is fairly straightforward. You can install it on Windows, Mac OS X, and Linux (Ubuntu).
Installing Python on Windows
We’ll focus on the Windows installation here, but you can also choose the Mac OS X and Linux options to install it on those respective systems. To install it on more esoteric operating systems, visit this page.
- First, visit the Python website and download Python 3.7.3 (you may see a different version number, depending on what the latest release is)
- Run the downloaded executable file to install Python. The installation includes IDLE, pip, and documentation. IDLE is an integrated development environment(IDE) with a GUI for Python, which comes bundled with the default implementation of the language.
You could also install Pycharm, a Python IDE developed by JetBrains. Pycharm helps developers to write neat and maintainable code, and provides all the tools needed for productive Python development. It’s up to you whether you want to download Pycharm, which is available for Linux/Unix, Mac OS X, and Windows.
Writing Your First Program in Python
Now that you have the required IDE setup, you can start writing your first program.
If you are using Pycharm, then follow these steps:
- Click “Create New Project” on the PyCharm welcome screen
- Enter a valid project name
- Create a new python file, so right-click on the folder name and select New -> Python File
- Type this code:
# this program prints Hello World on the screen
Print(‘Hello World’)
- Save the file as HelloWorld.py
- Run the file HelloWorld.py
- The output will be seen on the screen as - Hello World
Your first Python program is ready! Now let's see what Python’s features are and how they help.
The Python Language: Features
The Python language has several basic features that will help you write your own program applications in Python. You might be familiar with this if you have some experience with another programming language.
- Comments
- Keywords and Identifiers
- Variables, Constants, and Literals
- Data types
- Flow control
- Functions
- Classes and objects
- Exception handling
- File handling
Comments
When we look at most programs, understanding the logic of it can be difficult through a cursory glance. Comments are statements in any program which are not executed — it doesn’t affect the output, but it does improve the readability of the code. Comments written in plain English, allow any user to read and understand what’s going on in the program.
There are two ways in which you can comment in Python:
Single line comment: as shown below
# this line is a sample python comment. The program adds two numbers.
X = 6
Y = 10
Z = x + y
Print(“”# Hello World)
print(z)
However ‘#’ inside a program statement is not a comment. The output will be:
# Hello World
16
If the comment was outside the program statement, it would not be printed, but only visible to the reader of the code.
Multiline Comment
For a multi-line comment in Python, you need to use triple single quotes at the beginning and at the end of the comment, as shown below.
‘’’
This is a sample multi
Line comment Python will ignore these
Lines.
‘’’
print(“Hello World”)
Keywords and Identifiers
Keywords are reserved words in the Python language. You cannot use keywords to name your variables, classes, functions, and so on. These keywords define the language syntax, flow, and structure.
Identifiers are names given to the variables, functions, and classes that you define. There are certain rules that you need to remember when you name identifiers.
- Identifiers can be a combination of letters in lowercase (a to z) or uppercase (A to Z) or digits (0 to 9) or an underscore _. Names like displayNamesClass, intSalary_1, _myName all are valid identifiers.
- An identifier cannot start with a digit. 1Salary is invalid, but Salary1 is valid.
- Keywords, as mentioned above, cannot be used as identifiers
- You cannot use special symbols such as !, @, #, $, % etc. while naming identifiers
- Python is a case-sensitive language hence employeeName and EMPLOYEEname are not the same
Variables, Constants, and Literals
Variables are used to store data that can be later used and changed in the program if needed.
empName = “Jason”
empNo = 19160
The = operator is used to assign a value to the variable
print(empName)
Will show the output as - Jason
empName = “Susie”
print(empName)
The output will be:
Susie
Since Python is a dynamically typed language, you don’t have to worry about the data type of the variable when you declare it. When the code is executed, the type of variable will be identified based on the value in it.
Constants are types of variables that cannot be changed. You could create a config.py file and store your constants in there. These can be used in your code wherever necessary.
For example:
config.py file will contain constants such as:
COMPANYNAME=DATAINC
COMPANYLOC=SAN FRANCISCO
To use the config.py constants in your code, do the following:
import config
# this is the config.py file that you have included in your program because you have to
# access the constants which are in the file.
print(config.COMPANYNAME)
print(config.COMPANYLOC)
When you run the program the output will be:
DATAINC
SAN FRANCISCO
Literals are the data that is assigned to a variable or a constant. Python has the following literals. String, Numeric, Boolean, a Special Literal called None and collection literals.
Here is an example of a few types of literals.
- String: “Delhi”
- Numeric: 100, -46.89 (float)
- Boolean: True or False. A Boolean literal has only 2 values.
Data Types
In Python, data types are identified based on the values the variables contain. Python is an object-oriented language hence variables are considered as objects and data types are classes. Since Python is a dynamic-typed language, you do not need to declare the variable with their type before using them.
Some of the important data types are as follows:
Numbers
Int, float, and complex are data types that represent numbers.
a = 5
b = 8.77
c = 2+3j
String
A string is a sequence of Unicode characters. You can use single quotes or double quotes to represent strings. Multi-line strings can be denoted using triple quotes, ''' or """. The data type of string in Python is str. Here’s an example:
S = “This is an example of a string.”
Boolean
If the value in a variable is either true or false, Python considers the data type of the variable as Boolean.
If (number % 2) = 0
noEven = True# noEven is of Boolean type
else
noEven = False
List
The list data type is an ordered sequence of values and they are used extensively. All values in a list need not be of the same data type. Lists are changeable (mutable). The value in a list can be modified.
Tuple
Tuples are also similar to lists, as they are an ordered sequence of values. However, the values in a tuple are not changeable (immutable). They are faster than lists as they do not change dynamically.
Set
A set is an unordered and unindexed collection of items. The output of the set will show unique values.
Dictionary
A dictionary is an unordered collection of key and value pairs. A dictionary is accessed by the keys. The keys can be of any data type. You can also convert one data type to the other and it is called type conversion.
Flow Control
If, if …else, if …elif…else – these form the flow control part of decision making in programming. It helps you to run a particular piece of code only when a condition is satisfied.
This is best explained with some sample if statements. The program below checks if the number is positive or negative and displays an appropriate message if the number is positive, negative or zero. You can extend the same program to include elif as well.
num = 3.4
if num > 0:
print("Positive number")
elif num == 0:
print("Zero")
else:
print("Negative number")
You can use nested ifs, i.e., you can have an - if...elif...else statement inside another if...elif...else statement.
Loops
A loop is a sequence of instructions that is continually repeated until a condition is reached. There are three types of loops in Python.
For Loop:
# Program to print values stored in a list
# List of numbers
numbers = [6, 5, 3, 8, 4]
# iterate over the list and print the values one by one
for val in numbers:
print(val)
While Loop:
A while loop is similar to a for loop, however in a for loop you know the number of times you are going to iterate. A while loop executes as long as a condition holds true.
This program prints all numbers from 1 to 9
num = 1
# loop will repeat itself as long as
# num < 10 remains true
while num < 10:
print(num)
#incrementing the value of num
num = num + 1
break and continue are used in loops to alter the flow in the loop. A break is used to exit out of the loop for a particular condition; hence it follows an if condition. A continue is used to skip a set of instructions and move on to the next iteration.
Example of break and continue:
for num in [20, 11, 9, 66, 4, 89, 44]:
# Skipping the iteration when number is even
if num%2 == 0:
continue
# This statement will be skipped for all even numbers
print(num)
# program to display all the elements before number 88
for num in [11, 9, 88, 10, 90, 3, 19]:
print(num)
if(num==88):
print("The number 88 is found")
print("Terminating the loop")
break
Pass:
Pass is an interesting feature in Python, and it acts as a placeholder. If you would like to use a function, but you are not ready with the code for the function, you can use ‘pass’. Here the Python interpreter does not ignore ‘pass’, but it assumes that it has to do nothing as of now.
# pass is just a placeholder for
# functionality to be added later.
sequence = {'p', 'a', 's', 's'}
for val in sequence:
pass# do nothing as of now
Functions
A function is a sequence of steps or a block of code that performs a particular task. It usually accepts an input parameter, performs a process and returns a result. A function can be called from another function or from the main program. Functions are very important in coding.
The advantages of using a function in a program are:
- Improves readability of the code
- Functions can be reused any number of times
- The same Function can be used in any number of programs
- It makes the code modular hence you could avoid errors
There are two types of functions in Python:
- Built-in functions: These functions are predefined. You do not have to define the function, you just need to call the function wherever it is required.
- User-defined functions: The functions that you create in your code for a specific process are user-defined functions.
Sample function in Python:
defmultiply_nos(num1, num2) # thisisthedefinitionofyourfunctionwith 2 inputparameters
returnnum1 * num2 # functionreturnstheproductof 2 numbers
# nowyouarecallingthefunctioninyourprogram
product = multiply_nos(5,6)
print(product)
The output will be:
30
Class and Objects
Python is an object-oriented programming language (OOP), and satisfies the four principles of OOP: encapsulation, abstraction, inheritance, and polymorphism. You can create classes and objects with attributes and methods.
Class:
A class is a blueprint of an object. You can imagine a class as a skeleton with certain attributes and methods. Attributes are the properties of the class and the methods are functions that are specific to the class.
Object:
When you create an instance of the class with specific features it is an object. The example here will help you understand it better.
# this is a class
classbox:
figuretype = “3D” # this is a class attribute
defboxdimension(self, length, breadth, height)
# theseareinstanceattributesandboxdimensionaclassmethod
print (length* breadth * height)
#nowyoucancreateaninstanceofthisclass
objsquare = box() # objsquareisanobject
objsquare.boxdimension(10,20,30)
# youarepassingthesethreenumbersandthevolumeof
# theboxwillbeshownastheoutput
Classes like functions are good to use as it enhances modularity and the code is reusable. They can be used when you need to represent a collection of attributes and methods that will be used repeatedly in other places in your application.
Exception Handling
Errors detected during execution are called exceptions. Exceptions can be handled in Python. There are various types of exceptions that can be handled in your program. A few examples of exceptions are ValueError, KeyboardInterrupt, OSError, and ZeroDivisionError. Here is an example for exception handling:
defthis_fails():
x = 1/0
try:
this _fails()
except ZeroDivisionError as err:
print(‘Handling run time error error name is :’, err)
The output of this program will be:
Handling run time error name is: division by zero
You can define your own exceptions by creating a new exception class. Exceptions should typically be derived from the Exception class, either directly or indirectly.
File Handling
File handling is all about opening a file, reading, writing into it and closing it.
For example to open a text file you could do it with an in-built function ‘open’ in Python
f = open("test.txt") # open file in current directory
f = open("C:/Python33/README.txt") # specifying full path
f.close()
You can close a file using the close function. Files could be opened in various modes like read-only, write-only and so on.
Where Do You Learn Python?
There are several resources you can make use of to learn Python. The best way to learn Python covers both self-study and paid courses. While it’s perfectly possible to learn Python on your own, Python certifications will expedite the process and impart a lot of practical knowledge. But if you’d rather not shell out the cash, there’s also a good number of cheaper and free Python courses available online, and those are well worth checking out.
Get Started on Your Python Journey
What you read through so far is only the tip of the iceberg. There is a lot more to Python programming, which is best learned through reading documentation and actually coding with Python yourself.
If you would like to learn Python, read up on the theory, including more advanced topics such as Python iterators, coroutines, decorators, and generators. And, of course, work on your projects!
Take This Crash Course On Python
Offered by Google
Frequently Asked Questions
1. Should You Learn Python 2 or Python 3?
For most purposes, and certainly for educational purposes, stick to Python 3. It is the most widely used. Python 3 is the newer version with some key changes. Unless explicitly required, you should choose Python 3 over Python 2.
2. Is Python a Free Language?
Yes, Python is completely free! It’s one of the reasons why coding in Python is so popular among beginners.
3. Is Python Open Source?
Yes, Python is open source!
4. Is Python Easy to Learn?
Python is considered one of the easier programming languages to learn for many reasons. One of them is the fact that its syntax somewhat resembles the English language.
People Are Also Reading:
- Best Python Courses
- Best Python Certifications
- Best Python Programming Books
- Top Python Projects
- Top Python Interview Questions
- Best Python IDE
- Difference between Ruby vs Python
- Python Conditional Statements
- Data Science Python Libraries
- What are Python Arrays?
- Python Data Structure