Jeff Nelson, a former Googler and inventor of Chromebook says on Quora, “One habit I've clung to is writing small prototypes when I'm trying to learn new concepts.
For example, I'll sit down with a book or a web page, and over the course of a few hours, write 30 or 40 programs all of them only a few dozen lines long.  Each program intended to demonstrate some simple concept. This prototyping makes it very easy to try out many concepts in a short period of time.”

Miguel Paraz, Software Engineering Student habit is to “keep a log in a text file or document on my work computer. Before trying to solve a problem, I write it down first. And then I describe the details as they happen.”

One of the biggest challenges faced by senior IT professionals in organizations is the choice of the right software vendor. In the highly competitive enterprise software industry, there are lot of vendors who claim to offer the best software for the problem and it can be really daunting to narrow down the best choice. Additionally, enterprise software costs can often run into millions of dollars thereby leaving very little margin of error. The real cost of choosing a wrong software can often result into losses much more than the cost of the software itself as highlighted by software disasters experienced by leading companies like HP, Nike etc. In such a scenario, senior IT professionals despite years of expertise can find it very difficult to choose the right business software vendor for their organization.

Here are some of the proven ways of short-listing and selecting the right business software vendor for your organization,

·         Understand and Define The Exact Need First: Before embarking on a journey to select the software vendor, it is critical to understand and define the exact problem you want the software to solve. The paramount question to be asked is what business objective does the software need to solve. Is the software required to “reduce costs” or is it to “improve productivity”? Extracting and defining this fundamental question is the bare minimum but necessary step to go searching for the right vendor. It will then form the basis of comparing multiple vendors on this very need that your organization has and will help drive the selection process going forward. The detailed approach involves creating a set of parameters that the software needs to meet in order to be considered. In fact, consider categorizing these parameters further in “must-haves”, “good to have” etc. which will help you assign relevant weights to these parameter and how the software’s fare on each of these parameters

·         Building The List of Vendors Who Meet The Need: Once you have defined your need and distilled that need into various parameters, it’s time to built the list of vendors who you think will meet the need. This is akin to a lead generation model wherein you want to identify a large enough pool and then filters your list down to the best ones. There are multiple ways of building a list of vendors and more often than not, you must use a combination of these methods to build a good enough list.

o   Use Industry Reports: We discussed the IT intelligence offered by leading industry firms Gartner and Forrester in How To Keep On Top Of Latest Trends In Information Technology. These firms based on their access to leading software vendors and CIO network publish vendor comparison research reports across specific verticals as well as specific technologies. Gartner’s Magic Quadrant and Forrester’s Wave are a very good starting point to get an insight into the best software vendors. For example, if you were looking for a CRM solution, you could look for Gartner’s Magic Quadrant for CRM and look at the vendors that make the list. These reports can be pricey but well worth the money if you are going to invest hundreds of thousands in the software. Having said that, you don’t have to trust these report blindly because how these firms define the best software may not match how you define the best software for your organization

o   Competitive Intelligence: If you are a smart professional, you are already keeping tabs of your competition. Chances are that if you are a big organization, you might see a Press Release either from your competitor or their vendor announcing the implementation of new software. Extrapolate that across 5-10 key competitors of yours and you might discover the vendors that your competitors are choosing. This gives you a good indicator that the vendors used by your competitors must be offering something right.

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

The mainstay of a corporation is the data that it possesses. By data, I mean its customer base, information about the use of its products, employee roles and responsibilities, the development and maintenance of its product lines, demographics of supporters and naysayers, financial records, projected sales ... It is in the organization of this data that advancements to the bottom line are often realized i.e. the nuggets of gold are found. Defining what is important, properly cataloging the information, developing a comprehensive protocol to access and update this information and discerning how this data fits into the corporate venacular is basis of this data organization and may be the difference between moving ahead of the competition or being the one to fall behind.

Whenever we attempt to develop an Enterprise Rule Application, we must begin by harvesting the data upon which those rules are built. This is by no means an easy feat as it requires a thorough understanding of the business, industry, the players and their respective roles and the intent of the application. Depending upon the scope of this undertaking, it is almost always safe to say that no one individual is completely knowledgeable to all facets needed to comprise the entire application.

The intial stage of this endeavor is, obviously, to decide upon the intent of the application. This requires knowledge of what is essential, what is an add-on and which of all these requirements/options can be successfully implemented in the allotted period of time. The importance of this stage cannot be stressed enough; if the vision/goal cannot be articulated in a manner that all can understand, the knowledge tap will be opened to become the money drain. Different departments may compete for the same financial resources; management may be jockeying for their day in the sun; consulting corporations, eager to win the bid, may exaggerate their level of competency. These types of endeavors require those special skills of an individual or a team of very competent members to be/have a software architect, subject matter expert and business analyst.

Once the decision has been made and the application development stages have been defined, the next step is to determine which software development tools to employ. For the sake of this article, we will assume that the team has chosen an object oriented language such as Java and a variety of J EE components, a relationsional database and a vendor specific BRMS such as Blaze Advisor. Now, onto the point of this article.