With stiff penalties for being caught and the whiff of secretive underground or even nefarious acts, computer hacking can be seen as a somewhat dubious pursuit. Not all hackers operate with the motive of emptying your Paypal account, however; there are many hackers who utilize their skills to aid companies in locating security flaws ("penetration testing") or engage in hacking with the goal of becoming cyber-freedom-fighters that champion simple human freedoms, such as the right to free speech.

Computer hacking is as much an art as it is a skill. At its simplest distillation, hacking is the systematic search for chinks in programming armor. While advanced problem-solving, intuition and sophisticated understanding of programming languages are a distinct advantage, there does exist a number of push-button programs that computing wizards have written allowing those less sophisticated in the art of hacking to break into remote computers in a variety of ways. Because of this new ubiquity, today's hackers no longer need to be a programming Wunderkind; they simply need to know where to download software and be able to turn on a computer. It really is that simple and the implications can be disturbing.

Phishing, Push-Button Programs and Brute Force Tactics

There's no need to crack a company's firewall if you have direct physical access to their computers. One aspect of hacking is the impersonation of an employee or service worker with the goal of gaining access to a company's database, where the hacker can then unleash whatever havoc he or she has planned into the system. Another is to engage in simple phishing techniques, such as impersonating an employee who forgot their password and needs help logging into the system.

Because such impersonations often fail thanks to companies becoming more security-conscious, taking over operations of a computer remotely is often the preferred method of gaining access. Such attempts can be facilitated in a variety of ways. One is the brute-force method, in which a program such as SQLmap, Nmap or Burpsuite is used; running one of these programs is analogous to trying every doorknob in a neighborhood to see which house is unlocked. Using a variety of different parameters, these programs can find access to a vulnerable computer or network in less than a minute.

Hackers can also attempt to gain access with a program like Metasploit. With literally a few clicks of a mouse, access to a remote and vulnerable computer can be achieved by a relative newbie. With a related hacking aid, called Meterpreter, a backdoor is created that allows access into an operating system. It does not install itself onto the remote computer, running instead using the computer's memory; in fact, Meterpreter can hide itself inside the operations of a perfectly valid program, so it cannot be detected even by sophisticated programmers. Once engaged, it allows a remote user carte blanche access to the system in question.

Where to Learn the Art of Hacking

Of course, for those who wish to learn the actual skills rather than download someone else's hack, there are a number of practice sites that pose an increasingly difficult set of challenges intended to train neophytes in the art of hacking. For example, Hack This Site starts beginners with the goal of cracking simple flaws in coding scripts or software such as HTML, Unix, Javascript and Apache. Their structured series of tests increase in complexity, incorporating real-word scenarios and even old-fashioned "phone phreaking" challenges that recall the bygone golden age of hacking skills displayed by Matthew Broderick in "WarGames."

Using just these simple tools and free practice sites, beginners have a powerful array of hacking resources just a simple mouse click away.

The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.

Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.

Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.

Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.

This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.

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Who Are the Main Players in Big Data?

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.

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

Python, a Zen Poem

With the skyrocketing popularity of Android and iOS operating systems, software developers got a whole new arena opened up. Many of the programmers have progressed to concentrate solely onto Mobile Technology Development. This is mainly due to the high demand as well as numerous lucrative ideas left to explore in the Mobile App world.

Exponential growth of smartphone users

As per the survey by eMarketer, the number of smartphone users across the globe crossed 1 billion almost two years ago. The expected number of smartphone users by 2014 end is 1.75 billion.

With smartphones, iPads and Tablets getting more accessible and less expensive day by day, the development potential for mobile apps is truly vast. The under-penetration in emerging markets like India and China in Asia shows that there seems to still a lot of steam left in the mobile app development industry.