Python For Web

A complete guide to web development in Python –

Think of a toolbox. A web framework is a collection of packages and modules made up of pre-written, standardized code that supports the development of web applications, making development faster and easier, and your programs more reliable and scalable. In other words, frameworks already have built-in components that “set up” your project, so you have to do less grunt work.
Python web frameworks are only utilized in the backend for server-side technology, aiding in URL routing, HTTP requests and responses, accessing databases, and web security. While it is not required to use a web framework, it is extremely recommended because it helps you develop complex applications in significantly less time.
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What are some popular Python web frameworks?
Django and Flask are, by a wide margin, the most popular Python web development frameworks
Django is a Python web framework that offers an open-source, high-level framework that “encourages rapid development and clean, pragmatic design. ” It’s fast, secure, and scalable. Django offers strong community support and detailed documentation.
Django is incredibly flexible in which you can work with MVPs to larger companies. For some perspective, some of the largest companies that use Django are Instagram, Dropbox, Pinterest, and Spotify.
Read out tutorial on Django for more details: What is Django Python? Build your first program from scratch
Flask is considered a microframework, which is a minimalistic web framework. It’s less “batteries-included, ” meaning that it lacks a lot of features and functionality that full-stack frameworks like Django offer, such as a web template engine, account authorization, and authentication.
Flask is minimalistic and lightweight, meaning that you add extensions and libraries that you need as you code without automatically being provided with it by the framework.
The philosophy behind Flask is that it gives only the components you need to build an app so that you have the flexibility and control.
Flask is also a prevalent and powerful web framework as it’s used by large companies like Netflix, Linkedin, and Uber.
Other notable frameworks:
Which should you use?
So, you might ask yourself: what framework should I choose? The answer is that it depends. Consider your skill level as a web developer. If you are quite experienced, consider developing your program with something more “barebones. ”
Whereas if you are a junior dev, it might be better to use a framework that provides more support like Django.
Also, ask yourself, would you prefer a “foundation” codebase to build off or have the flexibility to build the backbone of your codebase? If you prefer the first option, go with Django; if you prefer the second option, go with Flask.
At the end of the day, they can both achieve the same functionality, and it’s more important to start coding rather than fretting over which framework is better.
Applications for Python

Applications for Python

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Python is used in many application domains. Here’s
a sampling.
The Python Package Index lists
thousands of third party modules for Python.
Python is widely used in scientific and numeric computing:
SciPy is a collection of packages for mathematics,
science, and engineering.
Pandas is a data analysis and
modeling library.
IPython is a powerful interactive shell that
features easy editing and recording of a work session, and
supports visualizations and parallel computing.
The Software Carpentry Course teaches
basic skills for scientific computing, running bootcamps and providing
open-access teaching materials.
The Tk GUI library
is included with most binary distributions of Python.
Some toolkits that are usable on several platforms are available
Kivy, for writing multitouch applications.
Qt via pyqt or pyside
Platform-specific toolkits are also available:
Microsoft Foundation Classes through the win32 extensions
Python is often used as a support language for software developers,
for build control and management, testing, and in many other ways.
SCons for build control.
Buildbot and Apache Gump for automated continuous compilation and testing.
Roundup or Trac for bug tracking and project management.
Python is also used to build ERP and e-commerce systems:
Odoo is an all-in-one management software that offers
a range of business applications that form a complete suite of enterprise management
Tryton is a three-tier high-level general purpose application platform.
Advantages and Disadvantages of Python - Squareboat

Advantages and Disadvantages of Python – Squareboat

There is a multitude of programming languages used for application development across the world. Each has its specific features as well as the pros and cons. One of the most favored programming languages today is Python. Do you know what is python good for? Python has become one of the few languages that hold relevance in the present, as well as have a high potential for the future. Since it was founded in 1991 by a developer named Guido Van Rossum, Python’s reach has grown with each passing day, with several multinationals using it for their application development activities.
While that says a lot about it, there are a few downsides to Python, which often make application developers prefer other languages over it. Through this post, we aim at highlighting the ups and downs of Python development such that you can evaluate whether or not to use it for your next project. In this article, we will talk about Python advantages and disadvantages.
First things first – A few popular applications of Python
Before we move to the focal point of this article, let’s take a quick look at some applications of Python.
Being an advanced programming language, Python is used in the development of high-level applications like:
Web Server Programming: Developers can perform server-side programming through Python libraries like Django and Flask.
Prototyping: Through Python, developers can create quick prototypes to present to the client.
Game development: It is widely used in the development of games, including GUI, through libraries like PyGame.
Data science and machine learning: Python is the best and most commonly used language for machine learning and data science. Because it has a great community and a vast range of libraries, Python aids a great deal to application development in the field of data science. It has libraries available for data manipulation, data visualization, data cleaning, and several other related functionalities.
Now that we’ve established the premise, let’s proceed to take a look at the good and bad side of Python. As there are various pros and cons of python which we will talk about.
Key Advantages of using Python
There is a reason that developers choose to code in Python. It has some unique features that make programming much more straightforward. Let’s take a look at some features which make working with Python advantages:
Easy to read and learn
Python is a simple language to read and learn. It doesn’t have complex syntaxes like other high-level languages such as C or C++. Thanks to lesser complexity, Python allows you to think more clearly and focus on logic building.
Reduces Maintenance Cost
Owing to its simplicity, Python makes application maintenance easier and, thus, reduces the costs involved, which is a massive advantage.
Avoid the Harms from Software Bugs
Python doesn’t let a code bug initiate a segmentation fault within the application. Due to this, it is considered to be a preferred language.
Wide Applicability
Another essential feature of this language is that it is widely applicable. Engineers, scientists, and mathematicians broadly use it.
Memory Management
Python has a vast library with memory management capabilities, and this makes it stand out from the other programming languages. It includes a private heap containing all Python objects and data structures and a built-in memory manager to maintain this private heap.
Straightforward and Speedy
The Python community provides rapid and practical support to users as well as the fast adaptation of code. Some experts like to give Python the moniker, “ready-to-run language” because it only requires simple code to be executed. Enhancing and testing code is much more comfortable with Python.
Asynchronous Coding
Asynchronous coding uses a single event loop to complete a job in small intervals. Python is very useful for writing asynchronous code because it is easy to write and maintain. It doesn’t require any complex research contentions, deadlocks, or any other complexity.
Integration with Other Languages
Python has libraries like Cython and Jython, which allow integration with other languages like C, C++, and Java to enable cross-platform development. This is one of the main perks of Python as no language is perfect, and sometimes development requires diverse language functionalities that are impossible to have in one language.
Enterprise Application Integration
Python is the best choice for Enterprise Application Integration (EAI). It makes web application development, invoking CORBA or COM components, and direct calling to and from Java/C++/C easier. Moreover, it offers reliable process control features and implementation of internet data formats and protocols. Further, Python helps users in processing markup languages like XL, executes through the same byte code on advanced operating systems, and can be utilized as a scripting language.
Phew! That was quite an exhaustive list of the plus points that Python has. But let’s not see only one side of the coin. Let us be fair and also cast a glance at the minus points of the language in the next section.
Primary Disadvantages of using Python
Along with several pros, Python has some restrictions in the areas of performance and security. The following are some significant disadvantages of using Python.
Slow Execution Speed
Python is an interpreted language, which means it works with an interpreter, not with a compiler. As a result, it executes relatively slower than C, C++, Java, and many other languages.
Large Memory Consumption
Python’s structures demand more memory space. This language is not suitable to use for development under limited memory restrictions.
Not suitable for Mobile and Game Development
Python is mostly used in desktop and web server-side development. It is not considered ideal for mobile app development and game development due to the consumption of more memory and its slow processing speed while compared to other programming languages.
Developer’s Restrictions
Once a developer gets used to the ease and simplicity of this language, it becomes difficult for them to switch back to other languages.
Error Detection in Codes
As Python is executed through an interpreter instead of a compiler, errors and bugs can’t be detected during compilation, and that’s not good for developers.
Database Access
Python is considered to be highly insecure and involves security risk. There are some limitations to using Python to access databases. As compared to other popular technologies such as JDBC and ODBC, the Python database access layer is a little underdeveloped and primitive. It is, therefore, not considered suitable if developers are looking for a smooth interaction of complex legacy data.
Design restrictions
One of the significant issues of Python is its design restrictions. The reason behind this constraint is that Python is dynamically typed.
Difficult to test
Since it is an interpreter based language, it is tough to run tests on code written in Python. All errors and bugs turn up only during the run time, which makes it very tough to test code snippets written in Python.
There you have it – an unbiased and precise evaluation of Python. Didn’t we tell you to look at both aspects before making a decision?
To Conclude
Python is a vastly used programming language. Despite all Advantages and Disadvantages of Python, it is still one of the most preferred and trusted languages for desktop and web server-side application development. It is best suited for machine learning and artificial intelligence and not suitable for mobile development and GUI. While we review its performance, we can conclude that the advantages of Python can overcome its disadvantages. If used in the right way by a skilled developer, Python is among the best choices for coding.
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Frequently Asked Questions about python for web

Is Python used for web development?

Web and Internet Development Python offers many choices for web development: Frameworks such as Django and Pyramid. Micro-frameworks such as Flask and Bottle. Advanced content management systems such as Plone and django CMS.

Why Python is not good for web development?

Not suitable for Mobile and Game Development Python is mostly used in desktop and web server-side development. It is not considered ideal for mobile app development and game development due to the consumption of more memory and its slow processing speed while compared to other programming languages.

Is Python good for backend web development?

Python has several powerful libraries with a huge amount of pre-written code. Hence developers don’t need to write the code from scratch, thereby speeding up the development time. This makes it an ideal choice to use Python for backend development.Jan 27, 2021

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