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.

When making a strategic cloud decision, organizations can follow either one of two ideologies: open or closed.

In the past, major software technologies have been widely accepted because an emerging market leader simplified the initial adoption.  After a technology comes of age, the industry spawns open alternatives that provide choice and flexibility, and the result is an open alternative that quickly gains traction and most often outstrips the capabilities of its proprietary predecessor.

After an organization invests significantly in a technology, the complexity and effort required steering a given workload onto a new system or platform is, in most cases, significant. Switching outlays, shifting to updated or new software/hardware platforms, and the accompanying risks may lead to the ubiquitousness of large, monolithic and complex ERP systems – reason not being that they offer the best value for an organization, but rather because shifting to anything else is simply – unthinkable.

There’s no denying that these are critical considerations today since a substantial number of organizations are making their first jump into the cloud and making preparations for the upsetting shift in how IT is delivered to both internal and external clientele. Early adopters are aware of the fact that the innovation brought about by open technologies can bring dramatic change, and hence are realizing how crucial it is to be able to chart their own destiny.

IT jobs are without a doubt some of the highest paying jobs with information architects, data-security analysts and UX designers taking home $100,000 or more a year. But then again, these are high demand; high expertise jobs so don’t jump with joy as yet. But like every job and IT industry to be specific, not everyone commands such higher salaries. There are a large number of IT professionals who at some point of their career feel that their salaries have hit a standstill. Even if you are an IT professional and a great one at that, your technical expertise alone may not help you exceed the IT earning barrier. To continuously exceed your salaries, you need to work hard and smart. Here is how you can exceed the earning barrier in IT.

·         Gain Business Knowledge and Move Up The Management Ladder: IT departments for the most part are considered a part of “back office” operations. What this means is that despite being a core part of the business, IT professionals do not often get enough say in revenue generating components of the business and as a result seldom have a chance to take up senior management roles.  So if you do not want to stay content with a project manager or senior project management salary, invest time and money in gaining business knowledge. It could be through a formal business degree, online training courses or just by keeping your eyes and ears open while in the organization. Having the technical experience with business knowledge will instantly make you stand apart and open the doors for you to draw senior management salaries. For example, a survey conducted highlighted that CIOs were the biggest salary winners which clearly demonstrates the value of technical and business knowledge

·         Gain expertise on the “Hot” Technologies and Keep Learning: Say you are an expert in Java and draw a respectable salary in the industry. However, someone with less years of experience than you joins the organization and draws a higher salary than you! Why you ask. It could very well be because he/she is an expert in say big data technology such as Hadoop. Information Technology is one of the most dynamic industries with new technologies and languages coming up every now and then. When a new technology comes to the foray and gains traction, there is an instant demand-supply gap created which means that those with the specific skill sets are in a position to demand high salaries. If you have to break the IT earning barrier, always be ready to reinvent yourself by learning new technologies and this way you will be well positioned to jump on the high paying opportunities in the IT industry

·         Work On Your Own Side Projects: This one might seem controversial but let me clarify that I do not mean doing freelance work because even though your organization may never find out, it is ethically in breach of contract with your contract. If you have been lucky enough to be trained in some web based technologies such as Java, .NET or even HTML etc. spare sometime after office to build your own side projects. They could be very small projects tackling some problem that only you might have but there are multiple benefits of developing side projects. Worst case scenario, you will improve your technical skills. On the up side, you might end up creating your own business. A lot of technology start-ups were actually side projects the founders tinkered on with while they were employed full-time. You may not always succeed but there is no downside to the same

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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