Ready? Then let\u2019s get going.<\/p>\n
1. What is Python?<\/h2>\n
Let\u2019s start with the absolute basics.<\/p>\n
Like all computer programming languages, Python is used to create algorithms \u2014 or sets of instructions \u2014 that can be read and implemented by a computer. It is one of countless programming languages used to develop software on the web, and in apps\u2026 perhaps including the app you\u2019re using to read this blog right now! Other programming languages you might have heard of include JavaScript<\/a>, Ruby, C++, and PHP.<\/p>\n Python\u2019s creator, Guido Van Rossum, first released the language in 1991 (fun fact: he named it after Monty Python!) Python is now on its third major release, and has enjoyed a recent surge in popularity. Its syntax (the set of rules that govern its structure) focuses on readability and ease of use, making it a great programming language for beginners. That\u2019s also why it\u2019s perfect for rapid prototyping.<\/p>\n While Python was initially used to produce simple scripts, the simplicity and versatility of its code have found a wide range of applications in the digital age. Its applications have grown to include data analytics<\/a>, web development, machine learning, and more\u2014but we\u2019ll explore these later on.<\/p>\n \u00a0<\/strong>The aim of every computer programming language is to solve computational problems. The ways languages do this can be lumped into different programming styles (known as “paradigms”). It\u2019s important to note here that programming paradigms aren\u2019t mutually exclusive, and that one language can fit into multiple paradigms.<\/p>\n This is exactly the case for Python.<\/p>\n In this section we\u2019ll cover some of Python\u2019s main features, helping you to get a better grasp of how it works. We\u2019ll also familiarize you with some of the terms you might encounter as you learn more about Python, and computer programming in general.<\/p>\n Python is what is known as a general-purpose programming language. Simply, this means it has a wide variety of applications. For instance, it is commonly used for web and software development. However, it is also popular for backend (or server-side) programming<\/a>, data analytics, and for producing system scripts (instructions that tell a computer what to do).<\/p>\n Python is a high-level programming language. This means it comes with many operations built-in behind the source code. Using a process known as \u2018abstraction\u2019, programmers can hide the majority of what the computer needs to do, making it easier for coders to focus on achieving their desired goal. In contrast, a low-level language requires much more consideration for how a computer \u2018thinks\u2019.<\/p>\n To make this clearer, imagine you have a list of names that you want to sort in alphabetical order. In a high-level language, you\u2019d do this by executing a command such as: \u2018sort alphabetically\u2019. In a low-level language, you would have to be far more specific, e.g. \u2018A comes before B, B comes before C\u2019, and so on.<\/p>\n While the strengths and limitations of high- and low-level programming are quite nuanced, in general, high-level languages are preferred. They minimize complexity and are more efficient \u2014 they\u2019re also easier for beginners to learn.<\/p>\n Two key programming paradigms (or “styles” of programming) are imperative and declarative. Python is an imperative language. This means that it uses a series of statements to tell a computer exactly how to do something. Meanwhile, a declarative language tells the computer what to do, but doesn\u2019t explain how to do it.<\/p>\n For instance, if you wanted a computer to draw a picture of a dog using an imperative language like Python, you would explain each step of the process, i.e. \u2018draw a tail, give it a nose, put two eyes above the nose\u2019, and so on. Meanwhile, using a declarative language (like SQL) you would simply instruct the computer to draw a dog, but the computer would decide how to draw it based on pre-existing algorithms.\u00a0You can learn more about the differences between imperative and declarative programming here.<\/a><\/p>\n As a general-purpose language (see above!), Python supports procedural, functional, and object-oriented programming. What does this mean? Without getting into too much detail, the key thing to take away is that each programming paradigm\u2014procedural<\/a>,\u00a0object-oriented<\/a>, and functional<\/a>\u2014is suited to different kinds of projects. As a multi-paradigm programming language, Python\u2019s strength lies in the fact that it can support all three. This gives Python a wider range of applications, and a broader appeal to different types of programmers. Definitely a strength!<\/p>\n Also known as \u2018scripting\u2019 languages, interpreted languages like Python take human-readable code, and put it through an interpreter (a program that executes the code, line by line). By contrast, another type of programming language\u2014compiled languages\u2014must be completely translated into computer-readable code before they are executed.<\/p>\n A helpful way to think of this is to imagine an interpreter at an international conference. Their job is to translate each line of a speech as it is being spoken, so that the foreign delegates can understand. In computer programming, the interpreter plays a similar role\u2014it must take each piece of source code and translate it, one line at a time, into a language that the computer can understand. In this analogy, a compiled language would be more like a translated book, i.e. it needs to be converted from beginning to end before it can be read (in this case, by a machine).<\/p>\n Now that we\u2019ve covered some of Python\u2019s key characteristics, let\u2019s explore how it is used.<\/p>\n In this section, we\u2019ll briefly cover why Python is so popular, before looking at some real-life applications.<\/p>\n We\u2019ve touched on some of Python\u2019s benefits and features, but here\u2019s a quick reminder of why developers, data analysts and data scientists love using it:<\/p>\n Python was initially developed as a back-end scripting language, used to automate \u2018mundane\u2019 behind-the-scenes tasks. While scripts have grown more sophisticated over the years, Python remains popular. It can be used to write scripts in a fraction of the time it would take to do so using a more complex language. Today, Python is used to automate everything from web searches and content downloads, to completing online forms, and sending emails.<\/p>\n Python is also a popular language among web developers. Google, Instagram, and reddit are all examples of sites built using Python. Thanks to\u00a0Django<\/a> and\u00a0Flask<\/a>, two extensive Python web frameworks (which are foundation platforms on which software can be built), Python web development is a relatively straightforward process. Django is one of the most well-known web frameworks in existence, providing a robust architecture of free reusable code.<\/p>\n Astronomers, biologists, and neuroscientists all use Python. Even organizations like CERN and NASA\u2026pretty cool, huh? Better yet, thanks to an enthusiastic and active community, Python boasts an almost endless pool of third-party libraries. These include general data manipulation tools, such as\u00a0Pandas<\/a>, to niche frameworks like\u00a0PsychoPy<\/a> (used within experimental psychology). Python is also easily scalable\u2014on the most basic level, it can output data in a simple .csv file. However, it can also produce formats suited to ingestion by a variety of more complex systems.<\/p>\n Within machine learning, Python is used for everything from speech and image recognition, to the algorithms used by companies like Netflix. It is even used within the financial sector, most notably as the architecture behind the New York Stock Exchange. This is testament to its reliability and security. There’s a huge range of Python machine learning libraries<\/a> available, such as\u00a0TensorFlow<\/a>\u2014a high-level neural network library. Python\u2019s uses in the area of AI are only going to grow.<\/p>\n Developers have been using Python to create graphic user interfaces (GUI) for quite some time. However, with a range of Python 3D animation packages available, it has also found applications in computer gaming and special effects. Libraries available for budding game developers include\u00a0PyGame<\/a>,\u00a0PySoy<\/a>, and\u00a0PyKyra<\/a>. The digital special effects house ILM (whose work has appeared in all the recent Star Wars and Marvel films) also uses Python.<\/p>\n You can learn more about what Python is used for in this guide<\/a>.<\/p>\n Python is an excellent language for beginners. Its straightforward syntax is relatively intuitive, making it far less complex to learn than some computer programming languages. What\u2019s more, its range of third-party libraries is easily accessible through the\u00a0Python Package Index (PyPI)<\/a>. PyPI contains over 70,000 libraries of reusable, open-source code, which can be adapted for any number of purposes.<\/p>\n For those dipping a toe into computer programming, Python\u2019s level of abstraction (keeping only the most important information, in order to make it easier to reuse) is highly beneficial.<\/p>\n More experienced coders will find much to like about Python, too. While some argue that it is a little slow during execution, this is more than made up for in productivity time. A highly succinct and expressive coding language, Python requires much less time, effort and lines of code to perform operations, than more complex, or lower-level languages (such as C).<\/p>\n Finally, Python\u2019s burgeoning community makes it easy to problem solve \u2014 and quickly! Now on its third release, and regularly updated, Python is constantly improving with a community that is there to help each other when it\u2019s needed. There is certainly no need to worry about support disappearing any time soon.<\/p>\n Still wondering if Python is a good language to learn? Here are five reasons you\u2019ll want to start learning Python right now<\/a>.<\/p>\n As a beginner, the best way to start learning Python is to download the code and to start playing around with it. This will help bring to life the more complex concepts we have touched (such as the different programming styles, or \u2018paradigms\u2019).<\/p>\n Before installing, you\u2019ll need to choose a text editor or integrated development environment (IDE) for coding in Python. Many modern computers have Python pre-installed, but if not, the Python Wiki provides clear instructions on how to\u00a0download and install Python for Windows, Mac, and Linux systems<\/a>. And it is completely free!<\/p>\n Once you\u2019ve picked a text editor and downloaded the language, a sensible starting point is to check out the\u00a0Python Standard Library<\/a>, or to play with some\u00a0sample code<\/a>.<\/p>\n If you\u2019re completely new to programming, the Python website offers an extensive range of documentation to help you learn about the language and its applications. This includes the\u00a0Python beginner\u2019s tutorial.<\/a> You might also find it useful to seek support from an online community. As a starting point, we recommend the\u00a0Python Internet Relay Chat<\/a>, or\u00a0Stack Overflow<\/a>\u2014both of which are excellent options for getting your queries answered quickly.<\/p>\n And if you\u2019re really enthusiastic, there are tonnes of Python conferences and workshops to attend. These take place regularly, all over the world.\u00a0You can find an extensive list of workshops and conferences on the Python website.<\/a><\/p>\n For a more thorough look at how to learn Python, check out this step-by-step guide<\/a>.<\/p>\n \u00a0<\/strong>While you\u2019ll find countless Python courses and tutorials online, here\u2019s a small handful of beginner courses to get you started:<\/p>\n As you get to grips with the language, you\u2019ll also get a better feel for its potential applications. Then you can start broadening your expertise. For a good overview of the courses that are available, check out this round-up of the best data bootcamps for learning Python<\/a>.<\/p>\n As we\u2019ve shown, Python\u2019s uses are extremely broad, and it has many benefits as a computer programming language:<\/p>\n Beyond the basics, you\u2019ll find a huge amount to learn about Python online, and plenty of resources to help you explore. However, be sure to balance learning with playing around with the language. After all, the most important thing is to have fun!<\/p>\n Want to learn more about the skills and tools you\u2019ll need to become a data analyst? Try out this free introductory data analytics short course<\/a>, and be sure to check out some additional blog posts:<\/p>\n Python is a great addition to any data analyst’s repertoire\u2014but what exactly is it, and what is it used for? Discover everything you need to know about Python in this guide.<\/p>\n","protected":false},"author":101,"featured_media":492,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_lmt_disableupdate":"yes","_lmt_disable":"","footnotes":""},"categories":[3],"tags":[],"class_list":["post-3793","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-analytics"],"acf":{"homepage_category_featured":false},"modified_by":"Matthew Deery","_links":{"self":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/posts\/3793","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/users\/101"}],"replies":[{"embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/comments?post=3793"}],"version-history":[{"count":1,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/posts\/3793\/revisions"}],"predecessor-version":[{"id":29512,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/posts\/3793\/revisions\/29512"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/media\/492"}],"wp:attachment":[{"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/media?parent=3793"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/categories?post=3793"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-json\/wp\/v2\/tags?post=3793"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}2. What type of language is Python?<\/h2>\n
Python is a general-purpose programming language<\/h3>\n
Python is a high-level programming language<\/h3>\n
Python is an imperative programming language<\/h3>\n
Python supports procedural, object-oriented, and functional programming<\/h3>\n
Python is an interpreted language<\/h3>\n
3. What is Python used for?<\/h2>\n
Reasons data analysts and developers love Python<\/h3>\n
\n
Examples of applications built using Python<\/h3>\n
System scripts and automation<\/h4>\n
Web and app development<\/h4>\n
Scientific computing and data analytics<\/h4>\n
Artificial intelligence (AI) and machine learning<\/h4>\n
Gaming and special effects<\/h4>\n
![\"Data](\"https:\/\/careerfoundry.inbearbeitung.de\/en\/wp-content\/uploads\/2020\/03\/python-visualization1-2.jpeg\" "\\"\\"")
<\/p>\n4. Is Python a good language to learn?<\/h2>\n
5. How can I learn Python?<\/h2>\n
6. What are the best courses for learning Python?<\/h2>\n
\n
7. Python in summary<\/h2>\n
\n
\n