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With a 29% global market share, Python is the most sought-after programming language

Python is one of the main programming languages at Intel, Google, and IBM. It is also responsible for the development of YouTube, Reddit, and Instagram. 


What is Python?

Python is a coding language that helps develop web apps, mobile apps, and software with fewer coding lines. It is a general-purpose programming language and can be used for backend development, data science, and system scripts development.


Why do we use Python applications?

For app developers, Python programming offers unique benefits because of its coding capabilities. One of the main reasons why people prefer using Python applications is because they can run time series analysis. Python helps you extract meaningful statistics from volumes of data and improves your sales predictions.

Data insights scrapped with Python tools can help a business boost its revenue by pointing it to the best suitable revenue stream. Python applications are also in demand for their language processing capabilities. They improve human-computer interactions and can run sentiment analysis to figure out what your customers truly want.

The Importance of Python in App Development

Python is a highly productive programming language. It surpasses the programming capabilities of C++, Java, Ruby, and almost every other language. It allows developers to write a few lines of code for executing even the most complex tasks.

Python is widely used by programmers not because it is an easy language but because it can help them write more functional codes in app development. It is not limited to the web app or mobile app development. Python can help you develop everything from websites to the software. It also works perfectly well with C, C++, and Java languages. It has been more than two decades since its launch and Python continues to be the most evolutionary programming technology.

With Python 1.0, developers could adopt a module system with varied functioning tools. With Python 2.0, additional support was extended to coding. Python 3.0 provided constructive designs on avoiding module duplicacy. Today, developers are using Python 3.5 and higher versions for enabling the apps with new versatile features.

Making an app more interactive, modular, and interpreted is the main reason why Python is good for your business applications. Programmers working with tech giants use Python to leverage these characteristics. Its dynamic coding covers the development process from multiple angles. Its object-oriented scripts reuse codes and implement polymorphism.

Python business applications are portable and developed with high levels of quality assurance. They are designed to be extensible in Java, C, and C++. Python programmers can diversify application development across gaming, web frameworks, user interfaces, and graphic designs. They can create an app that understands your customers accurately with language processing and data analytics. Extensive support libraries provided by Python are useful in solving issues with string operations,  and web services. Python tools can optimise your app for operating system interfaces and web protocols. They can shorten the length of codes written for advanced programming tasks.

Python is best at integrating enterprise applications. It makes web service integrations easy. Its COM or COBRA components are powerful in controlling calls made directly via Jython implementation. Python also processes markup languages such as XML and ensure that its apps run on all modern operating systems with the same byte code.

The role of Python in a programmer’s productivity is considerably high. This language supports clean designs to increase the programmer’s productivity, even while using Java, VB, or Perl. With its strong features on process integration and a comprehensive unit testing framework, Python delivers the best development outputs. It also enhances the control capabilities of developers in contributing to agile environments. The productivity of Python applications leads to building smart and scalable apps for your business.


Python – Coding Done Efficiently

Python offers dynamic coding capabilities to developers. It improves their coding efficiency and also saves their efforts and costs on programming iterations.

Web development – Python is a more accessible language in web development. It is a go-to tool that offers numerous solutions in content management, UI?UX development, and more. It can adopt web frameworks developed with Django, Pyramid, and Flask. Python is also known for creating advanced content management systems such as Django CMS. Libraries and modules available in these web frameworks simplify development tasks such as database interaction, interfacing, and security.  

Web scraping – Web scraping is if not the best application of Python. As a web scraping tool, Python runs contact scraping scripts for web indexing, data mining, and web mining of applications. It helps in monitoring online price changes and comparisons. It is also used to scrape product reviews in competition analysis. From gathering listings to monitoring data, Python’s web scraping solutions can detect any and every change made on websites.

Data visualisation  – Python is used by data scientists to run data visualisations on arguments and hypotheses. It helps your business strategists explore the marketplace in different ways. Creating visualisations is easy and quick with Python’s Seaborn and Matplotlib tools.

Embedded applications – Python is based on C language, hence can be used for embedded C applications. You can perform higher-level applications on nascent devices through Python computing. The most well-known Python embedded application is Raspberry Pi.


Use Cases for Python Applications

Use Case 1 – Python-based AI/ML Solutions

Artificial Intelligence and Machine Learning projects are inherently different from typical app development projects. In the creation of effective AI/ML tools, web technologies play a pivotal part. Python programmers have the skill sets required to transform conventional technology projects into smart applications. AI/ML tools are built with Python for gaining stability, flexibility, and security. Python scripts are equipped with programming tools that can handle the complex and unique requirements of AI/ML projects. Python is qualified as an ideal programming language among data scientists for creating AI products and ML systems.

The simplicity in Python’s programming is useful for building intelligent solutions to real-world problems. Python’s AI applications are built with consistency and are platform-independent. The language has a vast collection of resourceful libraries. It also has an active developer community that supports perfecting the development of AI and ML applications. A wide range of Python packages is available for AI and ML developers.

SciPy is an advanced computing kit used for building complex ML algorithms and workflows. Pandas are used for analysing general-purpose data with Python scraping modules. Seaborn is a popular data visualisation tool running in Python that is integrated into dozens of AI products. Leading tech companies use TensorFlow, Scikit-Learn, and Keras for developing ML tools. NumPy is the latest addition to Python’s ML packages. It is used for running data analysis with high-performance scientific computing. Python-based libraries such as PyTorch, NLTK, and Accord.NET are also of great use to develop AI/ML solutions.

Use Case 2 – Enterprise Apps with Python

An enterprise-level application and a standard application differ on various grounds. A business app demands readability, scalability, and extensibility. Enterprise application development is organisation-centric. It aims to cater to the needs of the business than individual customers. To make these apps, Python development kits are used. Python-based enterprise applications are capable of legacy system integrations. They can adopt existing databases regardless of their volumes. They can run non-web services on the apps to support offline usability.

Python business applications focus on custom requirements while tending to specific organisational needs. They can coherently adopt an operating model in their entire development process, no matter how complicated it is. Python makes a significant difference with its high performance, flexibility, and readability. Its scalability features are also crucial for developing fully-functional business apps. An efficient enterprise application built with Python serves as an all-in-one solution. Tryton is a popular application platform that uses Python tools for building enterprise applications.

Use Case 3 – Python and Gaming

Python is loaded with useful extensions, and most of them find application in the development of interactive games. PySoy is a 3D game engine developed with Python 3 that runs in the background of almost every digital game. PyGame is a Python-based library used for developing multiplayer web games. Popular games like Battlefield 2, World of Tanks, Frets on Fire, Vega Strike, Disney’s Toontown Online, and Civilisation-IV are all built with Python tools. They simplify writing codes for specific actions and improve the capabilities of dialog tree creation and level designing.

Use Case 4 – Desktop GUI Development

Python is praised for its English-like syntax and modular architecture. It brings the ability to work on multiple OS through its rich text processing tools. Python is an excellent choice for developing desktop-based GUI applications. GUI toolkits and frameworks built with Python are useful in creating desktop apps. PySide, PyGtk, Tkinter, and WxPython are the best GUI frameworks written in Python enabling the creation of highly functional graphical user interfaces.

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