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What Are the Advantages of Python Over Ruby?
[Apr, 03, 2014]    |
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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

Finding the Right Candidate from a Recruiters Perspective
[Mar, 23, 2017]    |
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I’ve been a technical recruiter for several years, let’s just say a long time.  I’ll never forget how my first deal went bad and the lesson I learned from that experience.  I was new to recruiting but had been a very good sales person in my previous position. I was about to place my first contractor on an assignment.  I thought everything was fine.  I nurtured and guided my candidate through the interview process with constant communication throughout.  The candidate was very responsive throughout the process.  From my initial contact with him, to the phone interview all went well and now he was completing his onsite interview with the hiring manager. 

Shortly thereafter, I received the call from the hiring manager that my candidate was the chosen one for the contract position, I was thrilled.  All my hard work had paid off.  I was going to be a success at this new game!  The entire office was thrilled for me, including my co-workers and my bosses.  I made a good win-win deal.  It was good pay for my candidate and a good margin for my recruiting firm. Everyone was happy. 

I left a voicemail message for my candidate so I could deliver the good news. He had agreed to call me immediately after the interview so I could get his assessment of how well it went.  Although, I heard from the hiring manager, there was no word from him.  While waiting for his call back, I received a call from a Mercedes dealership to verify his employment for a car he was trying to lease. Technically he wasn’t working for us as he had not signed the contract yet…. nor, had he discussed this topic with me.   I told the Mercedes office that I would get back to them.  Still not having heard back from the candidate, I left him another message and mentioned the call I just received.  Eventually he called back.  He wanted more money. 

I told him that would be impossible as he and I had previously agreed on his hourly rate and it was fine with him.  I asked him what had changed since that agreement.  He said he made had made much more money in doing the same thing when he lived in California.  I reminded him this is a less costly marketplace than where he was living in California.  I told him if he signed the deal I would be able to call the car dealership back and confirm that he was employed with us.  He agreed to sign the deal. 

Cloud Computing: What It Means and How It Could Threaten the Traditional Outsourcing Model
[Apr, 25, 2014]    |
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Cloud computing is the recent rage in the IT industry. According to the report by Forbes, the estimated global market for cloud computing is expected to reach $35.6 billion in 2015, from the $12.1 billion market of 2010.

How it began

The idea of cloud computing was inspired by the concept of “utility computing” which introduced the idea of computing using the virtual servers. These virtual servers do not actually exist anywhere physically and can be moved anywhere without causing any disturbance to the end users. Thus it minimizes the cost involved on the devices to a great extent and provides innumerable benefits to the companies that adopt this system.

Cloud Computing Types

How does Python integrate with Java?
[May, 06, 2014]    |
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Writing Python in Java syntax is possible with a semi-automatic tool. Programming code translation tools pick up about 75% of dynamically typed language. Conversion of Python to a statically typed language like Java requires some manual translation. The modern Java IDE can be used to infer local variable type definitions for each class attribute and local variable.


Translation of Syntax
Both Python and Java are OO imperative languages with sizable syntax constructs. Python is larger, and more competent for functional programming concepts. Using the source translator tool, parsing of the original Python source language will allow for construction of an Abstract Source Tree (AST), followed by conversion of the AST to Java.

Python will parse itself. This capability is exhibited in the ast module, which includes skeleton classes. The latter can be expanded to parse and source each node of an AST. Extension of the ast.NodeVisitor class enables python syntax constructs to be customized using translate.py and parser.py coding structure.

The Concrete Syntax Tree (CST) for Java is based on visit to the AST. Java string templates can be output at AST nodes with visitor.py code. Comment blocks are not retained by the Python ast Parser. Conversion of Python to multi-line string constructs with the translator reduces time to script.


Scripting Python Type Inference in Java
Programmers using Python source know that the language does not contain type information. The fact that Python is a dynamic type language means object type is determined at run time. Python is also not enforced at compile time, as the source is not specified. Runtime type information of an object can be determined by inspecting the __class__.__name__ attribute.

Python’s inspect module is used for constructing profilers and debugging.
Implementation of def traceit (frame, event, arg) method in Python, and connecting it to the interpreter with sys.settrace (traceit) allows for integration of multiple events during application runtime.

Method call events prompt inspect and indexing of runtime type. Inspection of all method arguments can be conducted. By running the application profiler and exercising the code, captured trace files for each source file can be modified with the translator. Generating method syntax can be done with the translator by search and addition of type information. Results in set or returned variables disseminate the dynamic code in static taxonomy.

The final step in the Python to Java scrip integration is to administer unsupported concepts such as value object creation. There is also the task of porting library client code, for reproduction in Java equivalents. Java API stubs can be created to account for Python APIs. Once converted to Java the final clean-up of the script is far easier.

 

Related:

 What Are The 10 Most Famous Software Programs Written in Python?

Python, a Zen Poem

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In the past, the reason for outsourcing centered on cost savings, lack of resources at home and the need to keep up with market trends. These considerations are proving to be of little merit as many organizations have, consequently, experienced productivity declines, are now finding considerable talent within their immediate location and have realized a need to gain more control over product development.
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