Multiple miracles touched the surface of the earth due to human efforts and struggle. Since the advent of computer technology, various dreams have come true regarding the transformation of human wishes and desires into reality. The remarkable works in this field are the invention of different computer languages from time to time. Python is an object-oriented programming language with features of interaction and interpretation. The procedural and functional programming is also supported by Python other than object-orientation (Python). Its purpose is general, which means that it is used for multiple purposes other than web development as well. In this way, it is unlike other multiple computer languages such as JavaScript, HTML, and CSS. Its uniqueness lies in its multidimensional purposes, reliability, convenient ways to use, readable coding, easy syntax, speedy application development, back end as well, and software development (Ozgur et al.).
However, its history and production are pretty exciting and have left unforgettable marks in the history of humanity. It was first created as the successor of the ABC language in the Netherlands in the early 1990s. It was invented and produced by Guido van Rossum at Stichting Mathematisch Centrum. Undoubtedly, many personnel contributed to it, but the principal author was Guido (Kumar et al.). The evolutionary perspective of the said language gave it new horizons as Guido and the Core team of Python emerged in May 2000 from the BeOpen Python Labs team. In October of the same year, the Python Lab Team introduced digital creation. Similarly, the next year, the Python Software Foundation (PSF) was created as a non-profit organization. Historically, the Python release has been GPL-compatible and portable.
Furthermore, multiple versions of Python have been introduced by the core team of Python so far. Python 2.0 was introduced in 2000, supporting the Unicode feature and a cycle-detecting garbage collector. In the same way, with some new features and characteristics, Python 3.0 came to market in 2008 (Malloy et al.). Similarly, versions like Python 3.9.3 and 3.8.8 are to be accomplished more quickly and will be available for the use of the general public. It is also worth noting that all previous versions of Python have some security issues that have been tried to resolve in the upcoming and latest versions. In the same way, Python is an easily readable and understandable language. As compared to other computer languages, it uses English keywords instead of punctuation marks. Sometimes, after the statements, semicolons are used, but this is rare. So, the Syntax and Symantec of Python are conveniently readable and understandable.
Meanwhile, programming in Python poses many benefits and advantages with a few disadvantages. It is unique in having extensive support libraries and plans for community development, and its sourcing is open. It is portable, with support available to help students learn effortlessly. The data structure in Python is user-friendly, and its main remarkable features are interpretation and productivity. It is dynamically typed so that it is multidimensional in applications and usages in routine life work normal life functionaries. As far as the disadvantages are concerned, its most harmful aspect is its slow speed compared to other computer languages. It is also not memory efficient; that is why mobile computing is weak compared to other languages. Despite the simplicity, it gives runtime errors along with retarded database access (Techvidvan).
Last but not least, the conclusion rests on the efficiency and remarkable uses of Python in a simple and easy way. Python has eased life with a set of high-level features compared to other computer languages with multiple horizons in this regard. The deficiencies and disadvantages can be removed by making improvements in this regard with the passage of time to make this programming language more efficient.
Work Cited
Kumar, Arun, and Supriya P. Panda. “A Survey: How Python Pitches in IT-World.” 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon). IEEE, 2019.
Malloy, Brian A., and James F. Power. “Quantifying the transition from Python 2 to 3: an empirical study of Python applications.” 2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). IEEE, 2017.
Ozgur, Ceyhun, et al. “MatLab vs. Python vs. R.” Journal of Data Science 15.3 (2017): 355-371.
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