Python is an incredibly powerful and useful computer programming language that many of the biggest websites in the world rely on for their foundation. Python provides reliable results that are functional and involve a variety of dynamic scripted and non-scripted contexts. And because it is free and open source, it has remained a popular choice for a variety of different developers who are looking to build new sites on one of the most reliable languages available. Here is a look at 10 of the most famous software programs that are written in Python and what they do.

YouTube
If you love watching hours of homemade and professional quality video clips on YouTube, you can thank Python for giving you that option. The foundation for Python helped YouTube integrate streaming videos into their pages, as well as the ability to like videos and embed certain information. YouTube is one of the most popular sites on the Internet, and it runs off of one of the most powerful languages in Python.

DropBox
What started as a powerful app, DropBox is now used by a variety of individuals, businesses, companies, organizations and more. This program lets you save files to a cloud-based service, that you can then access from anywhere in the world. With Python at the root of DropBox, there is no longer a need for USB sticks or blank CDs, since you can now save and share everything with your cloud-based account.

Google
It takes a lot of power to be able to handle the most popular search engine in the entire world. That is why Google uses Python for its mainframe foundation, as well as in addition to various apps that it runs in conjunction with the main site. The ease that Google provides for finding certain information, would be impossible without Python at the core.

Quora
Got a question? Ask it on Quora. This site compiles a list of questions and answers that come from a community of individuals. Those questions are then organized by various members of the community, which puts the most relevant information at the top. The creators of Quora, who happened to be former Facebook employees, decided to use Python to help them create the world’s best Magic 8 ball in Quora.

Instagram
If you love taking photos of your food or a new outfit and posting it online for all of your friends to see, you can thank Python for that ability. Granted, Instagram has both a very powerful app and a website, but the latter runs on Python language. The system allows for users to browse, find and post pictures that they like on the site.

BitTorrent
BitTorrent has evolved quite a bit in recent years, but its foundation and earlier years were built on Python. When it comes to one of the largest databases of knowledge, media and content, BitTorrent is the way to go. But you wouldn’t be able to get any of those lectures or other legal stuff that you are downloading from BitTorrent, if it wasn’t for Python.

Spotify
Spotify changed the music game when it allowed you to listen to ad-free music of your choice. This wasn’t a program where you got to select a playlist, but rather full songs that you love, on repeat as many times as you can imagine, if you so desire. But whether you are rocking out to the latest K-Pop song from Psy or a classic jazz tune, you are doing so because Spotify was built on Python.

Reddit
Reddit is one of the biggest open communities on the web. You have a question, want to talk about something in specific, or find tons of information regarding a particular topic, you can just look on Reddit. The site relies on Python to help them store user names, categorize subreddits, upload links to GIFs and, of course, award gold to valued posters.

Yahoo Maps
Much like Google, Yahoo also uses Python for a variety of different resources. Most valued may be Yahoo Maps. The API and programming behind the maps program, which is built with Python, allows for users to find locations, get directions and even find reviews about local places.

Hipmunk
If you love to travel, you have likely come across Hipmunk. And while the site lets you save money on booking your itinerary through Hipmunk, it is Python that keeps everything organized. Python also helps sort the best discounts and rates, so you can get the best packages available.

Python is an incredibly powerful tool for web development. More and more sites rely on it, including 10 of the most powerful sites in the world that are listed here.

Related:

Current Active List of Organizations that use Python 

Working With Lists In Python

Python and Ruby, each with roots going back into the 1990s, are two of the most popular interpreted programming languages today. Ruby is most widely known as the language in which the ubiquitous Ruby on Rails web application framework is written, but it also has legions of fans that use it for things that have nothing to do with the web. Python is a big hit in the numerical and scientific computing communities at the present time, rapidly displacing such longtime stalwarts as R when it comes to these applications. It too, however, is also put to a myriad of other uses, and the two languages probably vie for the title when it comes to how flexible their users find them.

A Matter of Personality...

That isn't to say that there aren't some major, immediately noticeable, differences between the two programming tongues. Ruby is famous for its flexibility and eagerness to please; it is seen by many as a cleaned-up continuation of Perl's "Do What I Mean" philosophy, whereby the interpreter does its best to figure out the meaning of evening non-canonical syntactic constructs. In fact, the language's creator, Yukihiro Matsumoto, chose his brainchild's name in homage to that earlier language's gemstone-inspired moniker.

Python, on the other hand, takes a very different tact. In a famous Python Enhancement Proposal called "The Zen of Python," longtime Pythonista Tim Peters declared it to be preferable that there should only be a single obvious way to do anything. Python enthusiasts and programmers, then, generally prize unanimity of style over syntactic flexibility compared to those who choose Ruby, and this shows in the code they create. Even Python's whitespace-sensitive parsing has a feel of lending clarity through syntactical enforcement that is very much at odds with the much fuzzier style of typical Ruby code.

For example, Python's much-admired list comprehension feature serves as the most obvious way to build up certain kinds of lists according to initial conditions:

a = [x**3 for x in range(10,20)]
b = [y for y in a if y % 2 == 0]

first builds up a list of the cubes of all of the numbers between 10 and 19 (yes, 19), assigning the result to 'a'. A second list of those elements in 'a' which are even is then stored in 'b'. One natural way to do this in Ruby is probably:

a = (10..19).map {|x| x ** 3}
b = a.select {|y| y.even?}

but there are a number of obvious alternatives, such as:

a = (10..19).collect do |x|
x ** 3
end

b = a.find_all do |y|
y % 2 == 0
end

It tends to be a little easier to come up with equally viable, but syntactically distinct, solutions in Ruby compared to Python, even for relatively simple tasks like the above. That is not to say that Ruby is a messy language, either; it is merely that it is somewhat freer and more forgiving than Python is, and many consider Python's relative purity in this regard a real advantage when it comes to writing clear, easily understandable code.

And Somewhat One of Performance

A business rule is the basic unit of rule processing in a Business Rule Management System (BRMS) and, as such, requires a fundamental understanding. Rules consist of a set of actions and a set of conditions whereby actions are the consequences of each condition statement being satisfied or true. With rare exception, conditions test the property values of objects taken from an object model which itself is gleaned from a Data Dictionary and UML diagrams. See my article on Data Dictionaries for a better understanding on this subject matter.

A simple rule takes the form:

if condition(s)

then actions.

An alternative form includes an else statement where alternate actions are executed in the event that the conditions in the if statement are not satisfied:

if condition(s)

then actions

else alternate_actions

It is not considered a best prectice to write rules via nested if-then-else statements as they tend to be difficult to understand, hard to maintain and even harder to extend as the depth of these statements increases; in other words, adding if statements within a then clause makes it especially hard to determine which if statement was executed when looking at a bucket of rules. Moreoever, how can we determine whether the if or the else statement was satisfied without having to read the rule itself. Rules such as these are often organized into simple rule statements and provided with a name so that when reviewing rule execution logs one can determine which rule fired and not worry about whether the if or else statement was satisfied. Another limitation of this type of rule processing is that it does not take full advantage of rule inferencing and may have a negative performance impact on the Rete engine execution. Take a class with HSG and find out why.

Rule Conditions

Google is one of the most popular websites in the entire world that gets millions of views each day. Therefore, it should come as no surprise that it needs a strong and reliable programming language that it can rely on to run its searches and many of the apps that Google has created. Because of this, Google uses Python to ensure that every time a user uses one of their products, it will work smoothly and flawlessly. That being said, Google uses Python in a variety of different ways, outlined below.

Code.Google.Com
Since its creation, Google has always used Python as part of its core for programming language. This can still be seen today considering the strong relationship the two have with one another. Google supports and sponsors various Python events, and Python works to better itself so that Google remains on top of cutting edge material. One way that they do this is by working with code.google.com. This is the place where Google developers go to code, learn to code and test programs. And with it being built on Python, users can experience exactly what it is that they should expect once they start using the real site.

Google AdWords
Google AdWords is a great way for people to get their websites out there, through the use of advertising. Each time a person types in a certain string of keywords, or if they have history in their cookies, then they’ll come across these AdWords. The way that these AdWords are broadcasted to online web surfers is built on the foundation from Python. Python also helps clients access their AdWord accounts, so that they can tailor where they want their advertisements to go.

Beets
If you have loads of music, but some of it is uncategorized or sitting in a music player without a name or title, Beets is for you. This Google project uses Python and a music database to help arrange and organize music. The best part about Beets is that even if it doesn’t run exactly the way that you want, you can use a bit of Python knowledge to tailor it to be more specific to your desires.

Android-Scripting
Not only does Google run off Python, but Android also has its own value for the language. Whether you are someone who is just creating your own app for your phone or if you are someone who is looking to create the next app that gets downloaded multiple millions of times, you can use Python and Android-Scripting to create an app that does exactly what you want it to do.

YouTube
YouTube one just started as a video viewer on its own, but is now a billion-dollar company that is owned by Google. YouTube uses Python to let users view and upload video, share links, embed video and much more. Much like Google itself, YouTube relies heavily on Python to run seamlessly for the amount of traffic it gets daily.

Python is not your average coding language. Instead, it is a valuable and integral part of some of the biggest websites in the world, one of which is Google. And the resources listed here are just a fraction of what Google uses Python for in total.

Related:

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Working With Lists In Python

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