Undoubtedly, Python has become one of the most dominant programming languages today. As per stats by major survey sites, Python has ranked among the top coding language for the past few years now. There are tons of reasons for choosing Python as the primary language if compared with others such as Java, C++, or PHP. Since we’re here to talk about web development, surprisingly even in web development, Python has reached its peak with tons of features, and improvements, and over the period it is becoming popular every day.
What’s the most crucial point from a developer’s point of view is to pick the right language that can deliver the desired results with ease, especially when we talk about web development, there are certain factors to consider that include management of database, security, and data retrieval and so on. Now, how these factors fit in with Python is still clueless for most programmers because they’ve been using Java, PHP, etc. for web development but today, even big tech giants like Netflix, Google, and NASA have been actively using Python for web development. So, in this article, we will see why Python can be considered for web development and became famous among the top programming language over these years.
5 Reasons to Choose Python for Web Development:
1. Multi-Purpose Programming Language
In contrast, Multi-purpose can simply be referred to as a multi-functionality having capabilities to operate in multiple ways. Surprisingly a developer can do wonders and can easily develop software by implementing easy methods. Being an interpreted language (smoothness in dev. process), this platform is absolutely free and open for all, it also offers platform independency, meaning their (Python’s) code can run on any platform without making any changes (such as Linux, macOS, etc.)
Besides this, Python can also be used in various ways:
- For Web Applications: Python is acing of the web development field and offers many frameworks to work with. Some of the most popular tools are Django, Flask, etc.
- Desktop Applications: It is being used to create fascinating desktop applications by many companies these days and some of the widely used tools are Tkinter, PyGUI, Kivy, etc.
- Cybersecurity: For malware analysis, developers are actively using highly secured tools to prevent any cyber attacks, tools like NumPy, Pandas, etc. are considered the perfect choices for it.
- Scientific Calculation & Computing: The simplicity of Python allows developers to write more reliable systems and working on complex algorithms is much easier with this.
This makes Python one of the most demanding languages for all tiers of businesses (small to large) and that is what makes it one of the perfect choices for web development.
2. Database Connectivity
Establishing database connectivity is pretty simple with Python and accessing (including implementation) can easily be done on major databases such as Oracle, MySQL, PostgreSQL, etc and they can be called up by their respective APIs when required. Mention a demographic image below for best reference on how connectivity is being established.
Some of the most common used DB connections are:
- .cursor()
- .commit()
- .rollback()
- .close(), etc.
Steps involved in this process: DB connectivity in python consists of 5 major processes that include:
- import module (MySQL.connector.module)
- create connection
- create object
- execute query
- terminate the object
How to establish a connection – MySQL server?
- Connect with the server
- Create a DB
- Connect with DB (newly created) or an existing one
- Execute a SQL query to pull up results
- Inform the DB (in case of any changes)
- Close the connection
Python
from getpass import getpass from mysql.connector import connect, Error try: with connect( host="localhost", user=input("Enter username: "), password=getpass("Enter password: "), ) as connection: print(connection) except Error as e: print(e) |
3. Simplifies -> Debugging – Deployment – Prototyping
As we’ve discussed the multi-tasking capability of Python programming language, application testing is one of the major advantages that developers get and eventually saves time and money. It enables ease in debugging, deployment, and building prototypes.
The reason is, that it offers ease in terms of syntax, and readability and is perfect for learning automation. It also offers an easy-to-employ UT framework by which you can even perform geolocation testing (for mobile devices).
For Testing
There are 2 major testings that can be performed within python programming:
- Doctest: It offers execution that starts with >>> while comparing to the desired outputs. To initiate the doctest module below is the process that can be followed easily (along with an example). Also, refer to this article to learn more: Testing in Python using doctest module.
Step I
- Import
- Input function with a docstring and provide 2 liner code for execution
Step II
- >>>funtions_name(*args).
- OUTPUT (desired one)
Example:
Python
# import testmod for testing our function from doctest import testmod # define a function to test def factorial(n): ''' This function calculates recursively and returns the factorial of a positive number. Define input and expected output: >>> factorial(3) 6 >>> factorial(5) 120 ''' if n <= 1: return 1 return n * factorial(n - 1) # call the testmod function if __name__ == '__main__': testmod(name ='factorial', verbose = True) |
Output:
Trying:
factorial(3)
Expecting:
6
ok
Trying:
factorial(5)
Expecting:
120
ok
1 items had no tests:
factorial
1 items passed all tests:
2 tests in factorial.factorial
2 tests in 2 items.
2 passed and 0 failed.
Test passed.
Unit testing: It’s a technique used by developers to perform testing of a particular segment (of course to check for any bugs) and it provides testing of any individual unit for spotting and fixing errors. Majorly used when a developer is writing a lengthy code, testing a section can save time and resources as well. This test is being performed in chunks to identify whether it’s working properly and changes can be done accordingly without spending much time. Below is the example of executing the unit test function:
Also, you can gather more information from the following article: Unit Testing in Python
Python
# Python code to demonstrate working of unittest import unittest class TestStringMethods(unittest.TestCase): def setUp(self): pass # Returns True if the string contains 4 a. def test_strings_a(self): self.assertEqual( 'a'*4, 'aaaa') # Returns True if the string is in upper case. def test_upper(self): self.assertEqual('foo'.upper(), 'FOO') # Returns TRUE if the string is in uppercase # else returns False. def test_isupper(self): self.assertTrue('FOO'.isupper()) self.assertFalse('Foo'.isupper()) # Returns true if the string is stripped and # matches the given output. def test_strip(self): s = 'neveropen' self.assertEqual(s.strip('geek'), 'sforLazyroar') # Returns true if the string splits and matches # the given output. def test_split(self): s = 'hello world' self.assertEqual(s.split(), ['hello', 'world']) with self.assertRaises(TypeError): s.split(2) if __name__ == '__main__': unittest.main() |
Deployment
This process completes the cycle of software development y putting the app in an environment where it can be pushed for LIVE. For Python, there are 5 major models that developers usually choose:
- PEX: It helps in analyzing the risk and by using its extension (.pex), a python file can be easily executed.
- AWS: Offers free account setup for deployment and an easy-to-go tool for execution.
- Docker: A containerization tool that is actively used by developers for deployment (by using containers).
- Heroku: A PaaS-based cloud platform to manage and scale modern applications.
- Pip: A popular tool used to install and manage software bundles (packages) that contain an online repository of packages (Python Package Index).
Prototyping
Being an easy and multi-purpose programming language, Python is way too easy for accessing and it guides developers to perform actions without much difficulty. A programmer can easily build a prototype to test out the codes and it reduces cost and workload.
4. Bunch of Frameworks
There’s a list of some influential frameworks that help in building sites and can easily fit into your project. And that too by offering enhanced security for either simple or complex websites, Python frameworks won’t disappoint you for sure.
Frameworks? A tool built on top of any programming language to offer enhanced features when trying to build something useful. In Python, there are certain useful frameworks that help speed up the development process and enable developers to build advanced features. They (frameworks) come with bundled codes and modules so that they can be implemented multiple times.
Let’s take a look at some of the best and most popular frameworks that are used in Python programming:
- Django: It includes all the modern functions that can boost web apps. All you need is to install this in your system and get access to all the desired selections (including template engine, user authentication system, etc.) Besides this, it suits well on any project and is considered exceptional (mostly because of its functions), and these capabilities make it more versatile and scalable. To read more about this, refer to this article: Getting Started With Django
- Flask: The reason behind flask is to develop a framework that can work rapidly for scaling any project. Flask is a choice for standalone apps and for prototyping. It focuses more on simplifying functionality and is a micro-framework based n Jinja2 (that’s a template engine. To read more about this, refer to this article: Python | Introduction to Web Development Using Flask
- CheeryPy: Introduced in 2002, Cheerypy is among the oldest framework that follows a minimalistic pattern and became one of the most popular among developers. It’s an object-oriented, open-source (free to use) framework, and the apps can be installed anywhere where python apps can function. Additionally, you may also refer to this link to know more: Introduction to CherryPy
5. Growing Community Base
As per the recent survey, over 10 million developers are helping in making it a strong base and actively offering their inputs whenever someone gets stuck. The number is high and is primarily for rectifying the errors that exist during designing the language. On average, hundreds of queries are being posted, viewed, and replied to by active developers throughout the world. Their community also helps in solving complex problems that you might not find anywhere on the internet and whenever you’re working on any project in any organization, there might be circumstances that can put you in trouble, so next time, don’t forget to visit its official forum for finding out the answer. If you’re at the beginner level, we suggest you go for Python Programming Foundation -Self Paced course and get certified in a structured way in no time.
Bonus:
Easy to create APIs that act as a base for Microservice apps
While using Python, development and deployment are way too simple, whereas in microservice architectures, the apps are highly detached and they connect with each other system (via light agnostic mechanism).
