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Posts Tagged ‘Java

The big languages are popular for a reason: They offer a huge foundation of open source code, libraries, and frameworks that make finishing the job easier. Sometimes the vast resources of the popular, mainstream programming languages aren’t enough to solve your particular problem. Sometimes you have to look beyond the obvious to find the right language, where the right structure makes the difference while offering that extra feature to help your code run significantly faster without endless tweaking and optimizing. This language produces vastly more stable and accurate code because it prevents you from programming sloppy or wrong code.

The world is filled with thousands of clever languages that aren’t C#, Java, or JavaScript. Some are treasured by only a few, but many have flourishing communities connected by a common love for the language’s facility in solving certain problems. There may not be tens of millions of programmers, who know the syntax, but sometimes there is value in doing things a little different, as experimenting with any new language can pay significant dividends on future projects.

The following six languages should be on every programmer’s radar. They may not be the best for every job — many are aimed at specialized tasks. But they all offer upsides that are worth investigating and investing in. There may be a day when one of these languages proves to be exactly what your project — or boss — needs.

Erlang: Functional programming for real-time systems

Erlang’s secret is the functional paradigm. Most of the code is forced to operate in its own little world where it can’t corrupt the rest of the system through side effects. The functions do all their work internally, running in little “processes” that act like sandboxes and only talk to each other through mail messages. You can’t merely grab a pointer and make a quick change to the state anywhere in the stack. You have to stay inside the call hierarchy. It may require a bit more thought, but mistakes are less likely to propagate.

The model also makes it simpler for runtime code to determine what can run at the same time. With concurrency so easy to detect, the runtime scheduler can take advantage of the very low overhead in setting up and ripping down a process. Erlang fans like to flourish about running 20 million “processes” at the same time on a Web server.

If you’re building a real-time system with no room for dropped data, such as a billing system for a mobile phone switch, then check out Erlang.

Go: Simple and dynamic

Google wasn’t the first organization to survey the collection of languages, only to find them cluttered, complex, and often slow. In 2009, the company released its solution: a statically typed language that looks like C but includes background intelligence to save programmers from having to specify types and juggle malloc calls. With Go, programmers can have the terseness and structure of compiled C, along with the ease of using a dynamic script language.

While Sun and Apple followed a similar path in creating Java and Swift, respectively, Google made one significantly different decision with Go: The language’s creators wanted to keep Go “simple enough to hold in one programmer’s head.Thus, there are few zippy extras like generics, type inheritance, or assertions, only clean, simple blocks of if-then-else code manipulating strings, arrays, and hash tables.

The language is reportedly well-established inside of Google’s vast empire and is gaining acceptance in other places where dynamic-language lovers of Python and Ruby can be coaxed into accepting some of the rigor that comes from a compiled language.

If you’re a startup trying to catch Google’s eye and need to build some server-side business logic, Go is a great place to start.

Groovy: Scripting goodness for Java

The Java world is surprisingly flexible. Say what you will about its belts-and-suspenders approach, like specifying the type for every variable, ending every line with a semicolon, and writing access methods for classes that simply return the value. But it looked at the dynamic languages gaining traction and built its own version that’s tightly integrated with Java.

Groovy offers programmers the ability to toss aside all the humdrum conventions of brackets and semicolons, to write simpler programs that can leverage all that existing Java code. Everything runs on the JVM. Not only that, everything links tightly to Java JARs, so you can enjoy your existing code. The Groovy code runs like a dynamically typed scripting language with full access to the data in statically typed Java objects. Groovy programmers think they have the best of both worlds. There’s all of the immense power of the Java code base with all of the fun of using closures, operator overloading, and polymorphic iteration.

Finally, all of the Java programmers who’ve envied the simplicity of dynamic languages can join the party without leaving the realm of Java.

CoffeeScript: JavaScript made clean and simple

Technically, CoffeeScript isn’t a language. It’s a preprocessor that converts what you write into JavaScript. But it looks different because it’s missing plenty of the punctuation. You might think it is Ruby or Python, though the guts behave like JavaScript.

CoffeeScript began when semicolon haters were forced to program in JavaScript because that was what Web browsers spoke. Changing the way the Web works would have been an overwhelming task, so they wrote their own preprocessor instead. The result? Programmers can write cleaner code and let CoffeeScript turn it back into the punctuation-heavy JavaScript Web browsers demand.

Missing semicolons are only the beginning. With CoffeeScript, you can define a function without typing function or wrapping it in curly brackets. In fact, curly brackets are pretty much nonexistent in CoffeeScript. The code is so much more concise that it looks like a modernist building compared to a Gothic cathedral. This is why many of the newest JavaScript frameworks are often written in CoffeeScript and compiled.

Haskell: Functional programming, pure and simple

For more than 20 years, the academics working on functional programming have been actively developing Haskell, a language designed to encapsulate their ideas about the evils of side effects. It is one of the purer expressions of the functional programming ideal, with a careful mechanism for handling I/O channels and other unavoidable side effects. The rest of the code, though, should be perfectly functional.

The community is very active, with more than a dozen variants of Haskell waiting for you to explore. Some are stand-alone, and others are integrated with more mainstream efforts like Java (Jaskell, Frege) or Python (Scotch). Most of the names seem to be references to Scotland, a hotbed of Haskell research, or philosopher/logicians who form the intellectual provenance for many of the ideas expressed in Haskell. If you believe that your data structures will be complex and full of many types, Haskell will help you keep them straight.

Julia: Bringing speed to Python land

The world of scientific programming is filled with Python lovers who enjoy the simple syntax and the freedom to avoid thinking of gnarly details like pointers and bytes. For all its strengths, however, Python is often maddeningly slow, which can be a problem if you’re crunching large data sets as is common in the world of scientific computing. To speed up matters, many scientists turn to writing the most important routines at the core in C, which is much faster. But that saddles them with software written in two languages and is thus much harder to revise, fix, or extend.

Julia is a solution to this complexity. Its creators took the clean syntax adored by Python programmers and tweaked it so that the code can be compiled in the background. That way, you can set up a notebook or an interactive session like with Python, but any code you create will be compiled immediately.

The guts of Julia are fascinating. They provide a powerful type inference engine that can help ensure faster code. If you enjoy metaprogramming, the language is flexible enough to be extended. The most valuable additions, however, may be Julia’s simple mechanisms for distributing parallel algorithms across a cluster. A number of serious libraries already tackle many of the most common numerical algorithms for data analysis.

The best news, though, may be the high speeds. Many basic benchmarks run 30 times faster than Python and often run a bit faster than C code. If you have too much data but enjoy Python’s syntax, Julia is the next language to learn.

Polina Mikhan

Polina Mikhan
Polina.Mikhan@altabel.com 
Skype ID: poly1020
Business Development Manager (LI page)
Altabel Group – Professional Software Development

 

Over the years dynamic languages such as Python and Ruby have become cherished by startups. As for .Net it is more rarely heard to be used by startups. That’s interesting indeed, because this platform is definitely bigger than most of the popular ones.

So I wonder why a platform as widely adopted and supported as .NET isn’t more visible in startup culture. Let’s try figuring out the main arguments in favor and against making .Net a startup technical choice.

1. Community culture

 Some people say the main reason is the culture of the .NET community itself, not anything specific to the platform. Being centered mostly around the needs of enterprise market .NET developers’ concerns are often regarding supporting legacy systems, building enterprise architectures, large systems for supporting business processes. This implies solving problems which are not so relevant for startups at least at their initial point.

As for members of the startup community, they fuss over different issues – concurrency, experience design, supporting multiple clients and browsers, etc.

As a result the startup community and the .NET community don’t overlap as much as they do for other technologies. That’s why startup founders don’t get much exposure to .Net and don’t think of it as an applicable tool for their purposes. The same way many .Net developers who want to work for hot startups don’t have as many opportunities to do so unless they abandon the platform for a more startup-friendly one or start a company themselves.

So platform doesn’t always dictate its use – that’s people who make the choice. Enterprise and startups aren’t mutually exclusive – they’re just different stages in the evolution of software, and there’s no reason why the startup community shouldn’t look at .NET as an attractive starting point for a new business.

2. Startup tech compatibility

A startup is a risky venture with no guarantee of success. So tech startups seek advantages in order to succeed. Hence startups take what big enterprises consider risky bets on technology. This objective can be achieved by using technology that is popular in startup environment.

Many features of .NET, facilitating the productivity of big companies, are not always useful to startups. There is too much choice of implementation methods. If anything, web startups are looking to have this choice taken away – their technology choices come from the subset that is built for the web.

Also it is said that innovation is quicker with other ecosystems which have a bigger set of libraries and tools. As for .Net there are a few open source projects however most of them are pretty much an implementation of concepts that have already been implemented for a while in the Java world, for example.

3. Open source vs proprietary

Although many startups don’t mind paying for tools and services, most of them still pick things based on cost. For a long time the “enterprise” level tools, services, databases, etc were hardly affordable by startups. That’s why startups adopt so much open source.

It’s also hard to justify the use of proprietary software from a business perspective. If you want to be acquired it is wise to develop your product using an open stack rather than Microsoft’s.

However luckily for many startups Microsoft saw a huge value in giving their stuff away to startups and startups have benefited greatly. Microsoft has been running their Bizspark program for several years, which eliminates most of the startup costs normally associated with employing a .NET framework. To get into the BizSpark program you just need to get checked by BizSpark team if your startup is eligible (developing a real product). Then you’ll get free licenses to basically every product they make, including SQL Server, and a free MSDN gold subscription, for 3 years. They figure 3 years is long enough for you to get going so after that they want you to pay for new licenses. The great part is that they let you keep the licenses you’re already using. So Microsoft has basically taken the cost factor completely out of the equation for new startups.

4. Velocity vs performance

Some people say that it’s all about the velocity. If you agree with an assumption that a startup goal is to find a niche vs build a product, then the goal of a startup is to learn about the market, customers, and product needs as quickly as possible. Python, Js, Ruby, etc allow you to iterate quickly without a lot of infrastructure and boilerplate. However a company that has already has a market has a little different goal, for them the objective is to build a stable product that they can maintain.

Some people say that .Net is not suitable for quick changes. This is a pretty outdated view of C# these days, it’s actually fairly easy to write extremely terse code with. As an added bonus refactoring is so incredibly easy compared to JS, Ruby, Python, etc. that it’s ideal for rapidly switching directions in code as you can refactor so fearlessly without being slowed down by massive amounts of tests. Unfortunately what’s bad about .Net is the tooling and the supporting ecosystem.

Python is much better suited to quick prototypes that can be fleshed out into a reasonably reliable product without too many headaches. The key difference comes when you have to change features mid-stream. The lack of strict typing and interfaces means you can add, change, and remove features much quicker than C# for example. On top of that, you just write fewer actual lines of code to get the same thing done, although sometimes readability can suffer if you get too concise. There is a price to be paid with Python and Ruby though and performance is the biggest one.

5. Team and project size

The team and project size always matters. So when the solution is being built with a small team, then it is easier to use something like Python. Obviously the goal is to be fast to develop in and have a bunch of libraries to be used. On the other hand when building something with a big team, you feel like using something like C#. In this case it keeps it safe to develop in and easy to catch mistakes. Any optional documentation provided by a developer is incomplete. On the contrary the quality level of the available .Net documentation is outstanding.

However if the company is starting as very small at the initial point, it hopefully grows and builds up quite a sizeable codebase by some point. Python, JS & Ruby are fine for small programs but anything more than that and they become their own enemies because the programs they make are quite brittle.

6. Scalability

The common opinion is that .Net scales well.So, if your startup does make it, you’ll probably have a much easier time scaling the .Net stack than you would with say Ruby or PHP.

Conclusion: it’s all about stereotyping

Eventually, I found different opinions on my question of .Net being not so popular with startups such as “platform lock-in,” “no open standards,” “licensing costs.” Sure, these are issues preventing many developers from adopting .NET in the startup space, but not enough to bar all of them from using it. Most of the arguments are just stereotypes that can be dispelled under closer examination.

All languages have strengths and weaknesses. For a startup, you need to do due-diligence and research what the right language to use for your idea will be because recoding in a different language can get costly.

So do you use .Net in your startup projects? Please share your feedback and experiences with us.

 

Aliona Kavalevich

Aliona Kavalevich
Aliona.Kavalevich@altabel.com
Skype ID: aliona_kavalevich
Business Development Manager (LI page)
Altabel Group – Professional Software Development

The IT sector is flourishing. If you’ve used a computer for at least a couple of times in the last few years, you’ve probably noticed this. I’ve noticed it myself even more after a business trip to Stockholm where I was lucky to attend some conferences and learnt more about Swedish IT industry tendencies. These tendencies reflect our life in general. Life changes rapidly with new technologies bursting into it. And when it comes to programming languages, we get a chance to see very different trendy styles. Programming languages which were popular some years ago are not useful today. And no one can exactly predict which programming language will be popular in future. That’s why a programmer who wants to stay in developer fields has to adopt the right programming language from time to time.

As the Swedish software maker Erik Starck pointed out, “programming is about managing complexities”. And it’s really so. An understanding of at least one programming language makes an impressive addition to any CV nowadays.

It is also very difficult to get the exact number of users for any programming language. Many of us use multiple programming languages. The more experience you have, the more programming languages you use. The more programs you write or work with, the chances of using more languages rise. The larger the company, the more languages you’re likely to use.

There are a number of ways to measure the popularity of a programming language, for example, based on the number of: 1) new applications written in the language; 2) existing applications written in the language; 3) developers that use the language primarily; 4) developers that use the language ever; 5) web searches; 6) available jobs that require skills in the language; 7) developers’ favorites, etc.

My survey attempts to rank which programming languages are most popular in Sweden, each using a different measure. So, they are the following:

1) Python

Python is an object-oriented programming language which allows developers to work quickly while integrating their systems more efficiently and effectively. Designed by Guido van Rossum in 1991, Python is one of the most easy to use programming languages.

Python is characterized by its use of indentation for readability, and its encouragement for elegant code by making developers do similar things in similar ways.

Top Employers: Amazon, Dell, Google, eBay, Instagram, Yahoo

2) Java

Java is a class-based, object-oriented programming language founded by Sun Microsystems in 1995. Java is one of the most in-demand programming languages today for many reasons. First of all, it is a well-organized language with a strong library of reusable software components. Secondly, programs written in Java can run on many different computer architectures and operating systems because of the use of the JVM (Java virtual machine).

Top Employers: Amazon, Deloitte, Sun, eBay, Symantec Corporation, Cisco Systems, Samsung

3) C++

C++ is a compiled, multi-paradigm language written as an update to C in 1979 by Bjarne Stroustrup.

Due to its high-level compatibility and object-orientation, C++ is used for developing a wide-range of applications and games which makes it a popular and sought after programming language by the employers.

Top Employers: Intel, the Math Works, Microsoft, Qualcomm, Amazon, Mozilla, Adobe, Volvo

4) Ruby

Ruby is an open source, dynamic programming language designed by Yukihiro Matsumoto in 1995 with a key focus on productivity and simplicity .It is one of the most object-oriented languages in the world.

Ruby is a mix of elegant syntax which is easy to read and write and hence it has attracted many organizations and developers.

Top Employers: Spokes, VMware, Accenture, Cap Gemini, Siemens, BBC, NASA

5) JavaScript

JavaScript is an object-oriented scripting language founded in 1995 by Netscape.

Being a client-side language, it runs in the web browser on the client-side with a simplified set of commands, easier code and no need for compilation.  JavaScript is simple to learn and it is used in millions of web pages to authenticate forms, detect browsers and improve design.

Top Employers: Microsoft, Sales Force, IBM, Yahoo, Dell

6) C#

C# is a compiled, object-oriented language developed by Microsoft.

It is highly used on Windows platform and labelled as the premium language for Microsoft .NET framework. C# is known for strong typing, procedural and functional programming discipline which is the reason it has acquired so much popularity.

Top Employers: Microsoft, HP, Digi-Key Corporation, Allscripts, Intel

Those are the top 6 programming languages which are in great demand among Swedish developers.

And one more thing: remember that opinions are like noses, everyone has one and they all smell ;) If you disagree, please feel free to email me or write your own opinions in the comments.

Katerina Kviatkovskaya

Katerina Kviatkovskaya
Kate.Kviatkovskaya@altabel.com
Skype ID: kate.kviatkovskaya
Business Development Manager (LI page)
Altabel Group – Professional Software Development

Working with many startups I was wondering recently why Python and Ruby are so popular and common with young and promising startups, especially Scandinavian ones as my experience shows. I am curious if anyone has analyzed the trend towards Python over Ruby with startups? Also I would like to find out what are the advantages of Python over Ruby if they are so?

I think a lot about choices and decisions at startups. Picking the language/platform to use at a startup is one of the harder decisions. Here I would like to mention the fact that most of startups today make their choice toward Python or Ruby over PHP or Java. From what I have read, PHP is just an inferior language to Python and Ruby. Even though a lot of people are using PHP because it is easy to get started, it seems to be easier to develop bad habits with PHP. Why jump on a bandwagon when you obviously know is broken? I’ve come to realize that the main reason why PHP gets into trouble with the purists is that there are just so many ways of doing one thing — it is not that standardized. I think it became the most popular language only because it’s so easy to pick up!

Python/Ruby win over Java on speed of development, and conciseness of code. This generally makes Python/Ruby a better choice for small startups for whom speed to market, and ability to implement new features matters most. Most of the modern sites chose Python when they were small startups. Only later did they have to scale. Websites tend to be horizontally scalable, meaning that for a surprising range of volumes of traffic you can just throw more webservers at it and the bottlenecks will be at other layers (for instance the database).

Searching for relevant information to compare both Pyton vs Ruby languages and analyzing customers’ demand on the software development market I found out that Python appeared to be the more popular choice for startups trying to get a minimum viable product launched and seek out potential venture capital.

This has less to do with the merits of either language and more to do with the philosophies of the frameworks represented by either language. RoR really can’t be beat as a rapid application development framework, and developers discussing Ruby on the web are generally referring to RoR. Django purports to do the same, but the overall philosophy of the python community is more minimalistic – python developers generally prefer to make their own selection of tools such as ORMs, Persistency layers and libraries.  A lot of people start Python web development with Django but move on to something more minimalistic like Flask, simply because the community seems predisposed to building its own stack in this way. RoR is more opinionated, and developers who are more predisposed to hitting the ground running, especially in the startup field, often take the Ruby fork in the road.

There is a “coming of age” point for startups coming from RoR or PHP, however.  I’ve heard about several companies who had this exact same experience and ended up moving towards something like Python or Scala.  I’m not certain this is specific to python, but I can say that as startups grow and become more ambitious, they move into problem domains poorly represented strictly by web frameworks/languages.  Search features and data extraction increasingly rely on advanced data mining techniques utilizing things like natural language processing and find they need to reengineer their stack a little to accommodate new ideas. Increasingly I see companies not abandoning their RoR/PHP/Django frontends, but creating separate REST APIs that almost always use bare python or a JVM language to take advantage of more complex computation outside of the HTTP req/response model.  Ruby could be used for this kind of offline processing, but the toolkits are just better and more mature in other languages since RoR is so prevalent in the Ruby community and consumes a great deal of the mindshare.

The fact of the matter is that most web startups represent feature sets early on where development speed is the prime concern, and so the language/framework with the biggest potential hire base and best RAD features typically win out early on.

As my personal point of view that no single language can answer every problem satisfactorily, and it is foolish to stubbornly stick to a single language for every case. Nevertheless a lot of our clients stick to Python when starting up their business. Let’s try to see what are the advantages of Python over Ruby?

The two are more similar than they are different, in everything from design to disadvantages to common uses – you can’t really go wrong either way, and shouldn’t base your decision on syntactical differences.

As Ruby developers say, Python’s main advantage has nothing to do with the language’s features. It’s more subjective: it seems that Python has more momentum amongst serious computer scientists. It’s increasingly popular in academic and scientific applications, and a lot of the technologists I respect the most seem to prefer it. By comparison, the Ruby community feels more designer-y and relatively more novice.

What this means is that while the Ruby world has very slick out-of-the-box product solutions, the Python world seems to produce more exceptionally well-written components like Tornado (web framework). Combined with it being used at Google and the potential for stuff like LiveNode to be released as open-source, I’d cast my lot with Python if I were starting today.

Thinking Python may be the best choice of startups, what is your opinion on this?

Looking forward to hearing from you!

 

Polina Mikhan

Polina Mikhan
Polina.Mikhan@altabel.com 
Skype ID: poly1020
Business Development Manager (LI page)
Altabel Group – Professional Software Development

Debates about which programming language is the best are always hard and heated. Likewise, there’s no ideal language that works for all web application project requirements. Wikipedia is written in PHP. Gmail is written in Java. Python is number one choice of Google and YouTube. Ruby is used to create Twitter and Hulu. Slashdot is written in Perl. Stackoverflow is written in C#.

Browsing for the best web programming languages, among dynamic ones, you’ll mostly see PHP, Python and Ruby listed. Back in the days several years ago PHP was admitted the best tool for web job but since then both Python and Ruby have matured and grown robust libraries and frameworks around them that make them better candidates for many web projects now.

Today many consider PHP to be great for average everyday web systems. Python and Ruby are thought to be more suitable than PHP for most web applications in general and for more advanced things in particular. Just like PHP, they are free, open source, run on an open source stack (Apache and Nginx / linux, windows and BSD), and play well with any database engine. However, Ruby and Python have better syntax and they both enforce good programming habits by their nature, especially Python. PHP encourages sloppy spaghetti code by its nature. Also, the object oriented features in PHP are very ugly because of its arcane, retarded syntax.

Let’s get deeper insights into these two web programming languages from various standpoints:

As mentioned before, Python and Ruby are two of the most popular dynamic programming languages used in high level application development. In fact, Ruby was built using some of the design elements from Python. Developers often prototype using these two languages before implementing on compiled languages because of their modularity and object oriented features. Many use Python or Ruby instead of Perl as simple scripting languages. Python and Ruby are popular among web developers as well because of their rapid development cycle, with Python boasting computation efficiencies and Ruby boasting code design.

a/ Philosophy
Python really believes that code readability is the most important thing. Hence, there is one-true way of writing code, or as it has been reformulated lately: “There’s a most understandable way to do something and that is how it should be done”. Python is designed to strongly emphasize programmer productivity and it likes things to be structured, consistent, and simple. Python syntax enforces strict indentation rules; in fact, indentation has semantic meaning in Python.
Ruby believes in giving programmer the flexibility, freedom and power. It was designed, first and foremost, to make programming fun for its creator, with guiding concepts as follow: “The Principle of Least Surprise” and “There’s more than one way to do the same thing”. The latter philosophy principle inherited from Perl is the reason why many Ruby methods have alternate names, which may lead to some API confusion among new practitioners. However, this flexibility enables Ruby to be used as a meta language for describing DSL. Also Ruby provides a better way to write concise and compact code. More into the expressiveness of the code and writing code that is clever.
Python people like libraries to be transparent and obvious how they work and hence is easier to learn, while Ruby people tend to provide clean and pretty interfaces with “magic” behind the scenes. This makes development very fast when you understand the magic, but frustrating when you don’t.

b/ Ease of Use
Python is known for its ease of use. It allows beginners to start building powerful sites more quickly, and has the power to grow in complexity keeping its ease of comprehension. For example, one of the hardest parts of coding is going back to what you coded long ago and trying to remember the logic of it. Because Python uses natural language with white spaces and indenting, it is much more clear and easier to read than languages like Ruby. That makes it easier to fix mistakes or do updates. Also, there are literally thousands of pre-built modules that can be snapped on to let you get up and running on the web immediately. Its intuitive introduction to object-oriented coding concepts, such as communities, modules, and libraries, allows you to move on to other related programming languages as they develop.

c/ Object Oriented Programming
Both Python and Ruby support object oriented programming. Still Ruby’s object orientation is considered to be more ‘pure’ in that all functions exist inside a class of some sort. Python’s object orientation is more akin to that of C++, which allows functions and statements that exist outside of classes. In Ruby, even global variables are actually embedded within the ObjectSpace object. Python doesn’t have global variables, instead using attributes of module objects. In Python and Ruby, an instance of literally any type is an object. However, where in Ruby all functions and most operators are in fact methods of an object, in Python functions are first-class objects themselves.

d/ Syntax
Ruby includes several syntactic features which make dynamic extension of and higher-order interaction with external (library) code more straightforward. In particular these are blocks and mix-ins. Most things implementable with block and mix-in syntax are also achievable in Python, they are simply less syntactically natural and clear, and so less commonly form the centerpiece of major libraries or common styles of programming. These features, combined with a lighter-weight syntax with fewer restrictions (whitespace flexibility, optional parentheses, etc), make Ruby more suitable to pervasive and relatively transparent use of metaprogramming.
At the same time, while this flexibility and the Ruby community’s tendency to use it for metaprogramming can facilitate aesthetically pleasing code, they can also create stylistic variation in how the language is used, and obscure the mechanisms by which code actually works. Python’s more restrictive syntax is intentionally designed to steer developers towards one canonical “pythonic” style to improve accessibility and comprehension.

e/ Style
Ruby code is organized into blocks, with blocks starting with various constructs and ending with the keyword “end”. Python code is indentation-sensitive, with successively larger indentation meaning tighter (nested) scopes. Python’s syntax has been described as executable pseudocode.

f/ Functional Programming
Both languages support some functional programming constructs, but Ruby is arguably better suited to a functional programming style. Lambdas in Python are generally very short, because lambdas in Python are restricted to expressions and cannot contain statements. Ruby’s lambda support is far more flexible, allowing for lambda expressions of arbitrary length.

g/ Speed
The standard CPython implementation is generally regarded as executing code slightly faster than Ruby.If speed is really an issue for a Python project, you also have the option to use Cython, Pyrex,Pypy (JIT) or the ShedSkin tools to compile your code into C or C++.

j/ Features
Both Python and Ruby are high level application development languages. Each of them is estimated to have a Capers Jones language level of at least 15. Both languages promote test driven development.
Both languages have full Unicode support, although the way that support is implemented varies. Python distinguishes between “Unicode strings” and “byte-strings”. Ruby, on the other hand, treats all strings as byte-strings with a semi-hidden flag which causes problems when dealing with badly-encoded data from third-party sources.
Both Python and Ruby support multithreading. Python has the Global Interpreter Lock (GIL), which negates much of the potential advantage of using threads; Ruby has a comparable Global VM Lock (GVL).
There are a number of functions that are available by default in Ruby but for which in Python it is necessary to import a module from the standard library. Python supports generators and generator expressions.

k/ Community
There are great communities behind both frameworks. Some people believe that Python has a more developed community in terms of libraries suited for data analysis, machine learning, natural language processing, scientific libraries. As for community folks, Python ones are believed to be conservative and afraid of change, while Ruby guys welcome changes and love new shiny stuff even if it breaks older things. Consequently, Python world is more stable, and you can update your installation without much troubles, but that also means new technology is only added very slowly.

l/ Frameworks
There are a number of Web frameworks based on both Ruby and Python. The most notable and leading are Ruby on Rails (Ruby) and Django (Python) based on MVC. Django is more declarative, with it you’ll have a clearer understanding of what’s actually going on. It lets you specify most configuration details yourself. Django creates a much simpler project structure. On the other hand, the centerpiece of Rails’s philosophy is called convention over configuration. Rails provides you with more defaults.

m/ Popularity
Python is generally more widely used than Ruby, according to most measures, but in the wake of the rising popularity of the Ruby on Rails Web application development framework Ruby’s popularity too has seen rapid growth.
Python is more mature general purpose nature vs Ruby’s more niche (Rails) usage. Python is stronger and sees use in automating system administration and software development, web application development, data manipulation, analyzing scientific data (with help of numpy, scipy, and matplotlib modules), biostatistics, and teaching introductory computer science and programming. Ruby+Rails holds a slight edge over Python+Django for web development and sees use in general programming, and has more mindshare.
In terms of cloud deployment, Python can run on Google-Cloud (Google-App engine). Though Ruby has very strong cloud deployment options in the shape of Heroku and Engine Yard.

Would you prefer Python or Ruby over PHP for implementation of your web project? And is it indeed a philosophy that you chose while selecting between Python and Ruby? Interested to hear your thoughts.

Helen Boyarchuk

Helen Boyarchuk
Helen.Boyarchuk@altabel.com
Skype ID: helen_boyarchuk
Business Development Manager (LI page)
Altabel Group – Professional Software Development

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Some people will argue that it’s not worthy comparing Tomcat and JBoss, because one of them is a superset of the other. In fact JBoss is bundled with a forked version of Tomcat. So JBoss is Tomcat plus:

* JMS messaging provider
* Web Services engine (JAX-WS and/or JAX-RS)
* Management capabilities like JMX and a scripted administration interface
* A powerful data grid solution (Infinispan)
* Advanced security, e.g. out-of-the-box integration with 3rd party directories
* A dynamic and powerful clustering engine
* Transaction management service

Still many decision makers have to choose between these two, so lets’ take a deeper look at them.

The JBoss AS is an application server based on Java. It is an open source server and is usable in any operating system supported by Java.

Apache Tomcat, or its more widely known name Tomcat, is a servlet container (meaning it is a Java class that operates under the strictures of the Java Servlet API – a protocol by which a Java class responds to an http request). This is an open source server, providing a ‘pure Java’ HTTP web server environment in which code written in Java is capable of running.

Tomcat is only a servlet engine and JBoss offers many more functionalities out of the box. Still JBoss is no longer a heavyweight monolithic container, but a modular application server featuring true classloading isolation, modules loaded on demand, domain management and exceptionally lightweight container. It has a pluggable architecture and if required, you can unplug features from JBoss to make it essentially a Tomcat servlet container.

At the same time the plus going in favour of Tomcat is that it is fairly lightweight, and it means less memory requirement and a faster response. At the same time if you need certain JEE features beyond the Servlet API, you can easily enhance Tomcat. For example, if you need JPA features you can include Hibernate or OpenEJB and JPA works nearly out of the box.

Tomcat is hassle free and might be the right choice when you are not using much of Java features. It is a very good fit if it comes to web centric, user facing applications.

In case backend integration comes into play, a JEE application server should be considered. Last but not least, migrating a WAR developed for Tomcat to JBoss should be a 1 day exercise.

Some people still argue that instead of using application servers, one can still deliver a full stack application using Tomcat + Spring adding the right frameworks and writing the Spring integration layer with these frameworks. That’s for sure true. Still the logical question is what price you will have to pay for that. The JBoss project can be focused around average – to junior developers. Mastering the same complex stack of technologies with Tomcat and Spring requires skilled and well paid developers.

To make it short, Tomcat is merely an HTTP server and Java servlet container. JBoss is a full-blown JEE application servers, including an EJB container and all the other features of that stack. On the other hand, Tomcat has a lighter memory footprint (~60-70 MB), while JBoss weigh in at hundreds of megs. Tomcat is very popular for simple web applications, or applications using frameworks such as Spring that do not require a full JEE server. Administration of a Tomcat server is arguably easier, as there are fewer moving parts.
However, for applications that do require a full JEE stack (or at least more pieces that could easily be bolted-on to Tomcat) JBoss is one of the most popular open source offerings. JBoss has a larger and deeper user community, and a more mature codebase.

So, we should not really care anymore about which is better, but focus on the application requirements. However, you can still use the best of these two worlds in your enterprise applications.

It would be great if your could share your opinions on this topic :) Thanks in advance for your comments!

Aliona Kavalevich

Aliona Kavalevich
Aliona.Kavalevich@altabel.com
Skype ID: aliona_kavalevich
Business Development Manager (LI page)
Altabel Group – Professional Software Development

Scala is a statically typed and multi-paradigm programming language that runs on Java virtual machine and provides Java like syntax with a few improvements.

Being a multi-paradigm programming language, Scala allows for mixing multiple programming styles such as object oriented, imperative and functional programming. Whether it’s good or not, it is not a question that could be answered with a yes or no. Supporters would say that programmers can choose from a variety of styles and stick to the best depending on their needs. The others would argue that putting together some features found in many other programming languages can’t work well, mostly by increasing complexity and making a programming language obscure.

Scala code compiles to a byte code and runs on Java virtual machine, thus it is compatible with other Java applications. If most of your code and libraries are from Java world, this can be nothing but a good thing. At the same time some additional complexity in Scala is dictated by assuring compatibility with Java.

For some developers the Scala code is obscure, for others could be a nice and neat form of solving some specific problems.

One more positive aspect of Scala is its conciseness. We all know how Java verbose is and how many boiler code developers write everyday including constructors, getters, variable initialisation (type and generics), semicolons and many others.

Now let’s see some other aspects of working with Scala:

Performance
At first sight the performance in Scala is very good, comparable to Java. Scala code compiles to the same byte code as Java does and runs on the same Java virtual machine. Still how fast Scala code is may vary from case to case and usually it’s up to the way how the code is written. The awareness of how to write a high performance Scala code is especially important for Java developers who are not very experienced in both Scala and functional programming.

Tools
There are not too many development tools created specifically to serve Scala, but fortunately, thanks to compatibility with Java it doesn’t look so bad. One family of tools hardly usable in Scala are those, which do some sort of code analysis, for instance code coverage and static code analysis. Static code analysis tools are even less usable.

Language extensions
The two worth to mention native Scala extensions are Lift web framework and Akka actors platform.
The majority of libraries and frameworks from a Java world, should be possible to use quite smoothly, which among other things, is thanks to implicit conversions in Scala.

Interoperability
Interoperability between Scala and other programming languages, including Java/C/C++, is very good, mostly because of running on Java virtual machine. What Java may talk to, Scala can do as well. Taking into account support for implicit conversions described above, I would state that Scala is one of the leaders of interoperability among all programming languages.

Testing
Developers are provided with all they need to test Scala applications efficiently. To follow a Test Driven Development methodology, they can use popular in Java world Junit tool. If someone is more keen on Behaviour Driven Development then ScalaTest is a way to go.

Monitoring and maintenance
One of the main monitoring tools to analyze production Scala applications is JMX (Java Management Extensions). This tool does its job well when we want to analyse some predefined statistics, but sometimes we need to investigate some aspects of a production application while it’s running and JMX can’t provide all required data. To deal with such scenarios, Java provides Java Virtual Machine Tool Interface (JVM TI) that allows for inspecting running Java applications but it can be used for Scala too.

Support
Scala community, including forum, mailing list and blogs, is not the biggest in the world, but it’s very energetic. Most people who are part of a Scala community are very passionate developers, which are always happy to help others to solve their problems. Books are also great: Programming in Scala book by Marting Oderski, Lex Spoon and Bill Venners.

Scala skills
No one will argue that it is far behind other programming languages such as Java or C/C++. Still while looking for Scala developers we could search for Java developers with Scala interests as well. The learning curve is not massive as Scala follows Java syntax. In such case, at least on experienced Scala developer would help the team adopting new programming language.

Have you moved from Java to Scala? How do you find this language?

Thanks for sharing your opinion!

Aliona Kavalevich

Aliona Kavalevich
Aliona.Kavalevich@altabel.com
Skype ID: aliona_kavalevich
Business Development Manager (LI page)
Altabel Group – Professional Software Development


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