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Python was first released in 1991 as a successor to the ABC programming language. Python was founded on the core philosophy that beautiful is better than ugly, explicit is better than implicit and complex is better than complicated. Its emphasis on high extensibility has made it a particularly popular program.
Unlike other languages Python boasts a high code readability and allows the programmer to use English keywords instead of punctuations. This allows users to build custom applications without writing additional code. The programming language offers several open-source libraries, frameworks, and modules which can be used for web development and data science applications. This makes Python a reliable, but unusually versatile programming language.
Web development, generally speaking, is the work involved in developing a website for the internet. It usually refers to coding and formatting and relies on the use of a programming language such as Python. Python is ideally suited for web development as it simplifies the development process and uses different frameworks depending on what the programmer is developing. The most popular frameworks are Django, Pyramid, Turbogears and Flask. The fluidity of the programming language allows for easy code improvement and a quick development of the initial prototype into a final product.
Python is widely used in data analysis as there are massive libraries that can be used for data manipulation tasks and are very easy to learn for beginning data-analysts. Some of the more popular libraries include Scikit Learn, TensorFlow, Seaborn, Pytorch and Matplotlib. Python also offers a variety of options for visualisation. The Matplotlib library can be used to create publication-quality figures in a variety of formats and also provides a foundation for other function libraries like Ggplot, Pandas Plotting and Pytorch.
Many tech companies today use python to build their websites. Instagram for example uses the Django web framework, which is written entirely in Python. It encourages rapid development and a clean, pragmatic design. The engineers of Google and Facebook also use Python for ease of maintenance and fast delivery. Developers at Netflix use Python to develop various features for the application and take advantage of its reliability, such as Netflix Cassandra Operations. This uses Python for automation and monitoring tools. Netflix’s data-science and engineering teams rely on the programme to help surface insights from the vast quantities of data produced and held by the organization.
The low entry level of Python makes it ideal for new learners and junior developers. The language is extremely user friendly, especially compared to programming languages such as Java. Java is adapted to handle complicated, detailed tasks but as a result, projects written with Java can often take years to complete. In contrast, the speed and accessibility of Python allows projects to be developed in a matter of weeks or months.
There are drawbacks when using Python however, one of which is its high memory consumption rate. Often during a project, the memory consumption must be tracked constantly to ensure that the program can continue to run efficiently. Some data scientists prefer to use statistically typed languages, which reduces the number of bugs in the system when a large amount of data is processed. Python is a dynamically typed language, which means the variable is checked at runtime instead of compile time, leading to an increased risk of scripting errors in the program. A statistically typed program such as Java cannot move on until the bug is fixed, making it ideal for data scientists focused on accuracy.
Python’s popularity in recent years has led it to become a leading programming language of the 21st century. It is predicted to grow considerably still in the future, paving the way for statistical programme development and bringing new people into the fast growing world of coding.
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