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Python is a general-purpose programming language that is very popular and has many applications.
Numerous technological solutions, such as web apps, games, animation software, search engines, and even other programming languages, are built on top of Python.
Python is a veritable jack of all trades, and this is not surprising considering how well-liked it is by specialists.
Because Python is so widely used and has so many uses, it is helpful to learn the fundamentals of the language. Given this, we cover all there is to know about Python in this article, including its history, the reasons it is so popular, the types of jobs that require it, and much more.
What Is Python?
High-level, object-oriented programming is done with Python. High-level languages are those that are simple for humans to understand.
In contrast, object-oriented languages are built around objects (such as data) rather than functions. Python is used in many of the everyday technologies we use at work; YouTube and search engine algorithms are two examples.
Python is used for many different things, such as developing web and mobile applications, manipulating and analyzing data, and machine learning (ML).
Why Is Python So Popular?
Based on multiple rankings, Python is one of the most popular programming languages worldwide. Python was the most popular programming language, according to the TIOBE Computer Programming Index.
Additionally, according to the Stack Developer Survey, Python is the fourth most popular programming language, with 41.53% of programmers using it for web development.
Let's examine a few of the factors that are currently driving Python's popularity.
Python Is Versatile
Python is a general-purpose language useful for many different kinds of work and projects. For example, Python can be used by a data scientist to manipulate data or create visualizations or by a web developer to create a website.
We discuss its use cases in more detail here.
Python Is Simple And Easy To Learn
If you're new to coding, one of the best languages to learn is Python. Because of its straightforward syntax, English based commands, and generally uncomplicated layout, any user, regardless of experience level, can easily understand each line of code and its purpose.
Python's simplicity makes it the ideal language for rapid development.
Python Is Open-Source
Python is open-source software that can be downloaded for free by anybody. The added benefit of this is that anyone can create new Python frameworks, libraries, and tools that are accessible to other users.
For example, premade Python libraries are available for chatbots and cryptography. The thriving Python user community helps to expand the capabilities and applications of the language.
Python Is Used A Lot
Then, there is the matter of ubiquity to consider. A language like Python is used in so many different technological solutions and by so many different businesses that it becomes increasingly important for developers and programmers to know it to be employable or to understand how specific solutions work.
Because of this, a greater number of people are conversant with Python and are more likely to suggest it to others or utilize it for their projects.
When Was Python Created?
Python was first developed in the late 1980s. Originally, it was intended to take the place of the ABC programming language, another all-purpose language developed at the Centrum Wiskunde & Informatica (CWI), a research institute for computer science and mathematics situated in the Netherlands.
Technologically speaking, ABC was developed to replace the antiquated BASIC programming language, which was initially used in 1964.
Despite being a high-level programming language, ABC was rarely used outside of educational environments and had little effect.
In many ways, ABC's greatest claim to fame is that it was an inspiration for Python. The history of Python is closely linked to ABC because the developer who created it (more on him later) spent many years working on it.
Version 0.9.0 of Python was first released in 1991 and was accessible on alt. sources, an online forum where users exchange language source code.
Among other things, this version included functions, object-oriented programming, exception handling, and basic data types like list, dict, and str.
Four Easy Ways to Streamline Your Life with Python
Tip 1 - Utilize The Greatest Concepts Of Contemporary Python
As of right now, Oct. 4, 2023, saw the release of Python 3.10, the most recent stable version. Hence, the first piece of advice is to stay up to date and not restrict yourself to what was offered in earlier Python releases.
In the same vein, if you've previously worked with C, Java, or another programming language, don't restrict yourself to what you know.
Indeed, you can look them up on the internet and find them in several excellent reference Python books. Still, you won't likely do so if you're unfamiliar with decorators or descriptors. Be careful not to overlook those features because they are unique to Python.
Tip 2 - Utilize The Opportunities For Python Integration
Python's primary selling point at launch was its cross-platform compatibility. That is no longer the crucial factor, thanks to cloud computing, web-based apps, and dependable virtualization software.
The important thing is that Python can now act as the "glue" in a software project, enabling developers to interface safely and sustainably with other software components.
Traditionally, APIs would be used for this kind of integration. You would have to learn how to use the Python API for each piece of software you wished to connect to.
On the other hand, using pre-done middleware and simplifying things is the current trend. The project can be completed more quickly because you can connect to different software programs using the same middleware.
More significantly, it makes maintenance simpler because you won't have to worry when that other software is updated.
Tip 3 - Utilize Every One Of Those Python Libraries
The Python ecosystem is very large, very deep, and very broad. It isn't very safe to navigate this open-source forest, and staying current with the best libraries for your goals will take constant work.
Libraries such as bolt-ons, which include over 250 BSD-licensed utility types and functions that can be used individually or as part of a package, can significantly impact a project.
Lesser-known modules like collection, and concurrent. Futures, logging, and scheduling are present even in the standard library.
Tip 4 - Make Use Of Already-Existing Data Structures To Write Shorter, More Readable Code
By its very nature, Python is a programming language that supports concise, readable code. This tip focuses on making the most of that when utilizing the available high-level data structures.
It is important to make sure you are using data structures correctly whenever you use them. Consider dictionaries as an example. You will frequently come across code that attempts to catch a KeyError exception when using a dictionary.
Python Basics And Advanced Python
Python is accessible to all. Because of its simplicity, even people without any prior coding or programming knowledge can pick up the fundamentals and start using this language right away.
Let's take the scenario where an office worker needs a quicker way to finish repetitive tasks like renaming a lot of files. They could create a simple script in Python to do this work for them. Alternatively, a marketer could use Python to assist in periodically sending emails to prospective clients.
As is often the case, there's a significant gap between what you can accomplish with basic and advanced (or even intermediate) Python skills.
It bears similarities to playing the piano. While many of us grew up learning how to use chopsticks, a select few became concert pianists with ease, capable of playing Rachmaninov.
However, they were only able to reach that level of success through practice and a steady improvement of their skills over time. They most likely began using chopsticks as well.
Python works the same way. You begin with the fundamentals and work your way up to the virtuoso level by gradually improving your skills.
Because there's always something new to learn, experts frequently argue that learning a programming language is a lifelong endeavour. Even though you could learn to code without a manual, there are always new uses for the language.
Experts in Python apply their knowledge to a wide range of challenging tasks. They may be developing AI systems that use massive data sets to create their algorithms.
Alternatively, they could be occupied with creating fresh APIs, creating applications that address pressing problems, or instructing classes. Regardless of your proficiency level in Python—from beginner to virtuoso CIS can assist you in achieving your objectives.
We provide a variety of general and career-specific Python courses for absolute beginners as well as advanced users.
What Can Python Do?
Is it not better to ask, "What is Python incapable of doing?" Python has a wide range of uses, even though it's most commonly associated with web and mobile development, as well as data, AI, and machine learning tasks and projects.
Let's examine some of the (occasionally surprising) applications of Python in more detail:
Data Analysis And Visualizations
Data analytics and visualizations are among the general data science tasks for which Python is a good fit. Analysts can use Python to organize, work with, and extract valuable information from data.
Additionally, they can use the language to craft striking images that draw attention to their discoveries.
For data analytics and visualization, Python libraries and frameworks are becoming more and more prevalent. Matplotlib, Plotly, and Pandas Visualization are just a few examples.
Python has tools that can be used for both simple and complex statistical reports and diagrams.
The fact that Python is an open-source language makes it a popular choice for data science applications. Not all analysts and business intelligence specialists are programmers or developers.
Still, Python is intuitive enough for those without a background in computer science to pick it up quickly. Python and other data science languages are the areas of expertise that CIS specializes in teaching to individuals and staff at big businesses like Google.
To help you get started on the path to a career in data, we provide a large selection of Python courses, skill tracks, and career tracks. To view our course offerings, click this link.
Programming Applications
Python is a versatile programming language that can be used to develop a wide range of online and mobile applications, from sophisticated financial services products to game components for Formula One Racing.
In addition, Python is widely used for programming file directories, application programming interfaces (APIs), and graphical user interfaces (GUIs), among many other things. You can probably build it (or many important components) with Python if you can think of it. Are you interested in learning how to write cool Python code? View the Python Programmer career track at CIS.
AI And Machine Learning
Python is dependable, adaptable, and simple. For this reason, it's the best programming language for applications involving AI and ML, which frequently require extremely complex algorithms.
Experts in AI and ML may write dependable, readable code quickly and easily with Python. Another advantage of its simplicity is that debugging is fast, allowing AI and ML developers to focus more of their time on developing their algorithms and heuristics rather than searching for syntax errors.
For AI and ML projects, there are many Python libraries and frameworks available, including sci-kit-learn, TensorFlow, and Pylearn2, to mention a few.
This facilitates the initial steps for developers. The Machine Learning Scientist with Python career track at CIS can help you achieve your goal of working at the forefront of technology.
Conclusion
Python rose to the top of the programming language rankings by effectively serving a particular market (the data science and machine learning space) and, at the same time, being a robust, user-friendly language that is easy to learn.
Remember that to achieve the best results with Python, you still need to concentrate on the particular project that you are working on.
Make sure you utilize the most recent Python features as well as the tools and libraries that will simplify your life:
- We suggest Connect Bridge if your project calls for data to enter or exit current business applications like Microsoft SharePoint, Microsoft Exchange, or others.
- Don't hesitate to use an existing library if it can help your project.
- To get the most out of a new project, use the most recent version of Python and write "Pythonic" code.
