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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

 
 
Python is a powerful tool that can be used for many automation tasks in the workplace. It’s notorious for being one of the most simple and versatile options available in the world of programming languages. For this reason, many people choose to automate an enormous amount of their workflow with Python. We’ve compiled a few ideas for automating the boring stuff using Python. Let’s take a look.
 
Managing Emails
 
Most businesses rely on emails being sent out regularly in order to ensure everything runs smoothly. Doing this by hand can be boring and time-consuming. To alleviate this, there are packages written with and for Python that enable you to automate certain aspects of this process. Adding and removing individuals from mailing lists can be automated as well, especially if your business has a policy to automatically add and remove people from certain mailing lists when certain conditions are met. For example, after a customer of yours doesn’t interact with your company after an extended period of time, it may be prudent to remove them from your mailing list, or you can send them a premade email reminding them of your services. This is just one way that you can save your company time and money using automation with Python.
 
Repetitive File System Operations
 
Even for personal tasks, Python excels at performing repetitive file system operations. For example, it can convert files, rename, move, delete, and sort files as much as you need it to. This can be useful in many ways. If you have a folder of mp3 files that you need to compress, this can be sped up using Python. Additionally, you can create a set of criteria that need to be met in order for a given file to be considered useless, and then delete it. As a side note, be extremely careful when automating any sort of file deletion or altering, because a bug in your program can cause severe damage to your data and even to your computer. Still, these tools are extremely powerful and can be life-saving when used properly. 
 
Start-up Tasks
 
Whether you’re running a server or just using your own personal computer, there are always tasks that need to be done when your computer starts up, or you’re beginning a certain process. For example, you can automate the task of backing up your email inbox. This can ensure your files are being kept safe, and it can be triggered whenever your start up your computer. Additionally, if you need to collect or create any sort of logging data in order to document daily operations, you can use Python to alleviate some of these time-consuming processes. 
 
Web Scraping
 
And finally, we have Web Scraping. This process may be slightly more advanced for a beginner Python user, but it doesn’t take a terribly long time to learn, and it opens up a whole new world of opportunity in terms of data collection and management. Web scraping is extremely important because it not only allows you to automatically search for certain pieces of content on the internet, but it can also alert you to changes and updates to existing websites. If your business relies on certain trends on social media, you can scrape sites while searching for the presence of certain keywords, and if you’re a stock trader or bitcoin guru, you can automate some of your price-checking and set custom alerts for price changes. The field of web scraping is enormous, and there is a practically infinite amount of content written on this particular subject. If you’re interested in learning more, there are vast amounts of free resources on the internet that can help you get started. Web scraping is certainly one of the most important skills to have in almost any line of work.
 
Get Creative!
 
At this point, we’d like to advise you to get more familiar with the libraries and APIs that are available to you. Each individual workflow is different and requires familiarity with different technologies. Because of this, you will know better than anybody else which items are worth automating and which aren’t. Some people try to automate everything, and some people prefer to do certain tasks manually, but sometimes spending a few hours automating a job that takes one minute will end up being a time-saver after only a few months.
 
We’ve gone over quite a few options in this article, but no single human alive is familiar with absolutely everything Python can do. Hopefully, you’re now more familiar with the options available to you, and you should now be better equipped to search for further information that is more relevant to your specific use case. Have fun digging into the many nuances and functionalities that the Python language has to offer!

I will begin our blog on Java Tutorial with an incredibly important aspect of java development:  memory management.  The importance of this topic should not be minimized as an application's performance and footprint size are at stake.

From the outset, the Java Virtual Machine (JVM) manages memory via a mechanism known as Garbage Collection (GC).  The Garbage collector

  • Manages the heap memory.   All obects are stored on the heap; therefore, all objects are managed.  The keyword, new, allocates the requisite memory to instantiate an object and places the newly allocated memory on the heap.  This object is marked as live until it is no longer being reference.
  • Deallocates or reclaims those objects that are no longer being referened. 
  • Traditionally, employs a Mark and Sweep algorithm.  In the mark phase, the collector identifies which objects are still alive.  The sweep phase identifies objects that are no longer alive.
  • Deallocates the memory of objects that are not marked as live.
  • Is automatically run by the JVM and not explicitely called by the Java developer.  Unlike languages such as C++, the Java developer has no explict control over memory management.
  • Does not manage the stack.  Local primitive types and local object references are not managed by the GC.

So if the Java developer has no control over memory management, why even worry about the GC?  It turns out that memory management is an integral part of an application's performance, all things being equal.  The more memory that is required for the application to run, the greater the likelihood that computational efficiency suffers. To that end, the developer has to take into account the amount of memory being allocated when writing code.  This translates into the amount of heap memory being consumed.

Memory is split into two types:  stack and heap.  Stack memory is memory set aside for a thread of execution e.g. a function.  When a function is called, a block of memory is reserved for those variables local to the function, provided that they are either a type of Java primitive or an object reference.  Upon runtime completion of the function call, the reserved memory block is now available for the next thread of execution.  Heap memory, on the otherhand, is dynamically allocated.  That is, there is no set pattern for allocating or deallocating this memory.  Therefore, keeping track or managing this type of memory is a complicated process. In Java, such memory is allocated when instantiating an object:

String s = new String();  // new operator being employed
String m = "A String";    /* object instantiated by the JVM and then being set to a value.  The JVM
calls the new operator */

Here is a list of the organizations that use Python. This list is periodically updated by HSG’s software fans as well as the community at large.
 

Web Development

1.       Yahoo Maps
Yahoo acquired Four11, whose address and mapping lookup services were implemented in Python. Yahoo Maps still uses Python today, as can be seen by examining its URLs.
 

2.       Yahoo Groups
A comprehensive public archive of Internet mailing lists that was originally implemented in pure Python. At one point Scott Hassan, one of the founders of Findmail/eGroups (the company that was later acquired by Yahoo), reported that they had 180,000 lines of Python underlying everything from their 100% dynamic website to all email delivery, pumping out 200 messages/second on a single 400 MHz Pentium.

 

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A successful career as a software developer or other IT professional requires a solid understanding of software development processes, design patterns, enterprise application architectures, web services, security, networking and much more. The progression from novice to expert can be a daunting endeavor; this is especially true when traversing the learning curve without expert guidance. A common experience is that too much time and money is wasted on a career plan or application due to misinformation.

The Hartmann Software Group understands these issues and addresses them and others during any training engagement. Although no IT educational institution can guarantee career or application development success, HSG can get you closer to your goals at a far faster rate than self paced learning and, arguably, than the competition. Here are the reasons why we are so successful at teaching:

  • Learn from the experts.
    1. We have provided software development and other IT related training to many major corporations in Germany since 2002.
    2. Our educators have years of consulting and training experience; moreover, we require each trainer to have cross-discipline expertise i.e. be Java and .NET experts so that you get a broad understanding of how industry wide experts work and think.
  • Discover tips and tricks about Microsoft SQL Server programming
  • Get your questions answered by easy to follow, organized Microsoft SQL Server experts
  • Get up to speed with vital Microsoft SQL Server programming tools
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  • See the big picture and have the instructor fill in the gaps
  • We teach with sophisticated learning tools and provide excellent supporting course material
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