Not getting any hits on your dating profile? It doesn’t mean you’re a loser. There are literally millions of computer dating profiles out there and dozens of free and paid websites to find a date. A dating profile is kind of like a resume for your personal life. To succeed, you have to learn a few tricks to stand out.

Tips to Improve Your Computer Dating Profile

1.  Make a Good First Impression

Filling out an online dating profile can be a daunting task. When you’re faced with all that blank space to write about yourself, it gets intimidating. The best way to improve your computer dating odds is to make a good first impression. Start with a good opening line such as a favorite quote or a personal motto you can easy build on.

Information Technology is one of the most dynamic industries with new technologies surfacing frequently. In such a scenario, it can get intimidating for information technology professionals at all levels to keep abreast of the latest technology innovations worth investing time and resources into.

It can therefore get daunting for entry and mid-level IT professionals to decide which technologies they should potentially be developing skills. However, the biggest challenge comes for senior information technology professionals responsible for driving the IT strategy in their organizations.

It is therefore important to keep abreast of the latest technology trends and get them from reputable sources. Here are some of the ways to keep on top of the latest trends in Information Technology.

·         Subscribe to leading Analyst Firms: If you work for a leading IT organization, chances are that you already have subscription to leading IT analyst firms notably Gartner and Forrester. These two firms are some of the most recognized analyst firms with extensive coverage on almost every enterprise technology including hardware and software. These Analyst firms frequently publish reports on global IT spending and trends that are based on primary research conducted on vendors and global CIOs & CTOs. However, subscription to these reports is very expensive and if you are a part of a small organization you may have issues securing access to these reports. One of the most important pieces of research published by these firms happens to be the Gartner Hype Cycle which plots leading technologies and their maturity curve.Even if you do not have access to Gartner research, you can hack your way by searching for “Gartner Hype Cycle” on Google Images and you will in most cases be able to see the plots similar to the one below

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

I will begin our blog on Java Tutorial with an incredibly important aspect of java development:  memory management.  The importance of this topic should not be minimized as an application's performance and footprint size are at stake.

From the outset, the Java Virtual Machine (JVM) manages memory via a mechanism known as Garbage Collection (GC).  The Garbage collector

• Manages the heap memory.   All obects are stored on the heap; therefore, all objects are managed.  The keyword, new, allocates the requisite memory to instantiate an object and places the newly allocated memory on the heap.  This object is marked as live until it is no longer being reference.
• Deallocates or reclaims those objects that are no longer being referened. 
• Traditionally, employs a Mark and Sweep algorithm.  In the mark phase, the collector identifies which objects are still alive.  The sweep phase identifies objects that are no longer alive.
• Deallocates the memory of objects that are not marked as live.
• Is automatically run by the JVM and not explicitely called by the Java developer.  Unlike languages such as C++, the Java developer has no explict control over memory management.
• Does not manage the stack.  Local primitive types and local object references are not managed by the GC.

So if the Java developer has no control over memory management, why even worry about the GC?  It turns out that memory management is an integral part of an application's performance, all things being equal.  The more memory that is required for the application to run, the greater the likelihood that computational efficiency suffers. To that end, the developer has to take into account the amount of memory being allocated when writing code.  This translates into the amount of heap memory being consumed.

Memory is split into two types:  stack and heap.  Stack memory is memory set aside for a thread of execution e.g. a function.  When a function is called, a block of memory is reserved for those variables local to the function, provided that they are either a type of Java primitive or an object reference.  Upon runtime completion of the function call, the reserved memory block is now available for the next thread of execution.  Heap memory, on the otherhand, is dynamically allocated.  That is, there is no set pattern for allocating or deallocating this memory.  Therefore, keeping track or managing this type of memory is a complicated process. In Java, such memory is allocated when instantiating an object:

String s = new String();  // new operator being employed
String m = "A String";    /* object instantiated by the JVM and then being set to a value.  The JVM
calls the new operator */