If you are a software developer looking for a slight change, then you have several options available. The process of software development requires multiple types of resources. A software developer performs the construction and delivery of software programs. An experienced software developer gains business knowledge, analytical skills, team management skills and communication skills. All of these skills can be used to divert your development career into a related and slightly varied role in software development.

Production Support Engineer
A developer can easily switch to the role of a Production Support Engineer. This role entails working with customers and technical teams to report, track and resolve production issues. For some, this might be an exciting opportunity to see the software application from a user’s point of view.

Engineering Manager
If you have experience in leading a team of developers, you could take the role of an Engineering Manager. This role requires managing a bigger team of developers. The Engineering Manager is also responsible for ensuring the delivery of software products and meeting the deadlines set by Product Management. You will get the opportunity to develop software, if you are inclined to do so. However, you will also take new responsibilities such as performance management, infrastructure management and vendor management.

Partner Engineer
This role requires some amount development as well as coordination with partners such as vendors and customers. The job of a Partner Engineer is to act as a middleman to help the integration of services with partners via application programming interfaces (APIs). For example, companies such as Twitter and Facebook employ Partner Engineers to integrate their services with customer websites.

Systems Analyst
Many companies offer developers with an opportunity to switch to Analyst roles. This role involves analyzing system requirements by working with business and technical teams. Many Systems Analysts also work on reviewing, developing and testing application code. This role is suitable for developers with strong analytical skills.

QA Automation Engineer
This role is responsible for automating test cases with the help of tools such as Java, Ruby and Selenium. This role is ideal for people with prior development experience. QA Automation Engineers work with developers and product managers to define test cases, and to automate and run the test cases. In this role, you will get the opportunity to work on back-end as well as front-end automation tasks. You will remain in touch with programming languages as well as database technologies.

Database Analyst
Most people gain significant amount of knowledge on databases while working as a software developer. This will help you to switch your role into a Database Analyst. A Database Analyst analyzes database issues, reviews performance problems, writes database scripts and runs queries. This role also provides a path to become a Database Administrator, if you are interested.

Deployment Engineer
This role is responsible for deploying the code developed by software engineers. You may not be developing application programs in this role. However, you will be responsible for code deployments, pushing the code into test and production environments.

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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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Python, a Zen Poem

Technology has continued to evolve in ways that few would have been able to imagine. This has allowed electronics to become smarter, more connected and far more useful.

With the Internet of Things (IoT), they're allowing more than just computers to become connected to the Internet. This aims to make the life of the average person easier, better and more care-free.

Let's examine why the Internet of Things has become such a powerful idea that an estimated one out of every five developers currently works on an IoT project.


What is the Internet of Things?

The Internet of Things hinges on one seemingly simple concept: electronics can be embedded in machines, clothing, animals and even people to provide a networked world where the whole is more than just the sum of its parts.

For example, consider how the Internet of Things can influence things like refrigerators. They can be networked directly to the manufacturer for readings that can warn if the refrigerator is about to malfunction. They can even be connected to a grocery shopping service to allow someone to restock them automatically or to notify the owner that the refrigerator is almost out of an item.

The most interesting notion about the Internet of Things is that it's not just a situation where one “thing” connects with a party. They typically communicate with other things, which in turn allows for a network of automated processes to occur.

These processes can simplify and expedite tedious tasks to make everyday life for everyone easier, which is why projects involving the Internet of Things are so popular.


How Prevalent is IoT Development?

An estimated one in five developers are currently developing projects for the Internet of Things. Their chosen languages vary widely because of the flexibility that IoT enjoys.

For example, IoT projects that hinge on interacting with mobile phones tend to have apps written in JavaScript or Java. The back-end code that runs the IoT functionality for machines tends to be written in Assembly, C++,Java,Perl,Pythonor another compiled language for efficiency.

To put the growth of IoT work into perspective, Evans Data Corp. performed research to create predictions about IoT projects in 2014. They stated that 17% of companies would be developing IoT projects.

In this year, that figure's risen to a solid 19%. Given the fact that 44% of developers have stated that they will enter into the IoT scene this year or next, this means that development will only grow in the coming future.


The Future Involving the Internet of Things

Development of IoT-related projects will likely explode in the next few years. The advantages it brings, such as more efficient work in manufacturing environments and the projected 15% savings to the restaurant industry over the next five years, will make it one of the most valuable technological changes in the near future.

Without a comprehensive understanding of the Internet of Things and the skills to lead IoT projects, businesses and developers may find themselves falling behind. Don't let the Internet of Things pass you by.

Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”