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For those newly moving into the realm of programming, the important question to mull over is what programming language or technology to specialize in. On the other hand, those who are already working as a software developer, the constant worry remains whether their current technology would become obsolete very soon.

Both these concerns could be easily addressed by checking the list of programming languages that are highly in demand and formulating the career by modifying your specialization accordingly. The supply for the developers have not met with the demand in these programming languages yet, making them most viable options for career.

Popular Programming Languages Based on TIOBE Index

The top 10 list of programming languages which are highly in demand in 2014 is listed below in the order of popularity. These languages are identified from the TIOBE Programming Community index which consists of 20 top programming languages. TIOBE index is an indicator of the popularity of programming languages and is updated once in every month. This index is calculated using multiple search engines, and the ratings are based on the number of skilled engineers world-wide, courses and third party vendors.

Automating The Boring Stuff With Python

[Aug, 12, 2019] |
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Python is a powerful tool that can be used for many automation tasks in the workplace. It’s notorious for being one of the most simple and versatile options available in the world of programming languages. For this reason, many people choose to automate an enormous amount of their workflow with Python. We’ve compiled a few ideas for automating the boring stuff using Python. Let’s take a look.

Managing Emails

Most businesses rely on emails being sent out regularly in order to ensure everything runs smoothly. Doing this by hand can be boring and time-consuming. To alleviate this, there are packages written with and for Python that enable you to automate certain aspects of this process. Adding and removing individuals from mailing lists can be automated as well, especially if your business has a policy to automatically add and remove people from certain mailing lists when certain conditions are met. For example, after a customer of yours doesn’t interact with your company after an extended period of time, it may be prudent to remove them from your mailing list, or you can send them a premade email reminding them of your services. This is just one way that you can save your company time and money using automation with Python.

Repetitive File System Operations

Even for personal tasks, Python excels at performing repetitive file system operations. For example, it can convert files, rename, move, delete, and sort files as much as you need it to. This can be useful in many ways. If you have a folder of mp3 files that you need to compress, this can be sped up using Python. Additionally, you can create a set of criteria that need to be met in order for a given file to be considered useless, and then delete it. As a side note, be extremely careful when automating any sort of file deletion or altering, because a bug in your program can cause severe damage to your data and even to your computer. Still, these tools are extremely powerful and can be life-saving when used properly.

Start-up Tasks

Whether you’re running a server or just using your own personal computer, there are always tasks that need to be done when your computer starts up, or you’re beginning a certain process. For example, you can automate the task of backing up your email inbox. This can ensure your files are being kept safe, and it can be triggered whenever your start up your computer. Additionally, if you need to collect or create any sort of logging data in order to document daily operations, you can use Python to alleviate some of these time-consuming processes.

Web Scraping

And finally, we have Web Scraping. This process may be slightly more advanced for a beginner Python user, but it doesn’t take a terribly long time to learn, and it opens up a whole new world of opportunity in terms of data collection and management. Web scraping is extremely important because it not only allows you to automatically search for certain pieces of content on the internet, but it can also alert you to changes and updates to existing websites. If your business relies on certain trends on social media, you can scrape sites while searching for the presence of certain keywords, and if you’re a stock trader or bitcoin guru, you can automate some of your price-checking and set custom alerts for price changes. The field of web scraping is enormous, and there is a practically infinite amount of content written on this particular subject. If you’re interested in learning more, there are vast amounts of free resources on the internet that can help you get started. Web scraping is certainly one of the most important skills to have in almost any line of work.

Get Creative!

At this point, we’d like to advise you to get more familiar with the libraries and APIs that are available to you. Each individual workflow is different and requires familiarity with different technologies. Because of this, you will know better than anybody else which items are worth automating and which aren’t. Some people try to automate everything, and some people prefer to do certain tasks manually, but sometimes spending a few hours automating a job that takes one minute will end up being a time-saver after only a few months.

We’ve gone over quite a few options in this article, but no single human alive is familiar with absolutely everything Python can do. Hopefully, you’re now more familiar with the options available to you, and you should now be better equipped to search for further information that is more relevant to your specific use case. Have fun digging into the many nuances and functionalities that the Python language has to offer!

Python Programming for Cisco Networking Engineers

[Jun, 25, 2018] |
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Wondering why Cisco is teaching network engineers Python in addition to their core expertise?

Yes, arguably there are many other tools available to use to automate the network without writing any code. It is also true that when code is absolutely necessary, in most companies software developers will write the code for the network engineers. However, networks are getting progressively more sophisticated and the ability for network engineers to keep up with the rate of change, scale of networks, and processing of requirements is becoming more of a challenge with traditional methodologies.

Does that mean that all network engineers have to become programmers in the future? Not completely, but having certain tools in your tool belt may be the deciding factor in new or greater career opportunities. The fact is that current changes in the industry will require Cisco engineers to become proficient in programming, and the most common programming language for this new environment is the Python programming language. Already there are more opportunities for those who can understand programming and can also apply it to traditional networking practices.

Cisco’s current job boards include a search for a Sr. Network Test Engineer and for several Network Consulting Engineers, each with "competitive knowledge" desired Python and Perl skills. Without a doubt, the most efficient network engineers in the future will be the ones who will be able to script their automated network-related tasks, create their own services directly in the network, and continuously modify their scripts.

Whether you are forced to attend or are genuinely interested in workshops or courses that cover the importance of learning topics related to programmable networks such as Python, the learning curve at the very least will provide you with an understanding of Python scripts and the ability to be able to use them instead of the CLI commands and the copy and paste options commonly used. Those that plan to cling to their CLI will soon find themselves obsolete.

As with anything new, learning a programming language and using new APIs for automation will require engineers to learn and master the skills before deploying widely across their network. The burning question is where to start and which steps to take next?

In How Do I Get Started Learning Network Programmability? Hank Preston – on the Cisco blog page suggest a three phase approach to diving into network programmability.

“Phase 1: Programming Basics

In this first phase you need to build a basic foundation in the programmability skills, topics, and technologies that will be instrumental in being successful in this journey. This includes learning basic programming skills like variables, operations, conditionals, loops, etc. And there really is no better language for network engineers to leverage today than Python. Along with Python, you should explore APIs (particularly REST APIs), data formats like JSON, XML, and YAML. And if you don’t have one already, sign up for a GitHub account and learn how to clone, pull, and push to repos.

Phase 2: Platform Topics

Once you have the programming fundamentals squared away (or at least working on squaring them away) the time comes to explore the new platforms of Linux, Docker, and “the Cloud.” As applications are moving from x86 virtualization to micro services, and now serverless, the networks you build will be extending into these new areas and outside of traditional physical network boxes. And before you can intelligently design or engineer the networks for those environments, you need to understand how they basically work. The goal isn’t to become a big bushy beard wearing Unix admin, but rather to become comfortable working in these areas.

Phase 3: Networking for Today and Tomorrow

Now you are ready to explore the details of networking in these new environments. In phase three you will dive deep into Linux, container/Docker, cloud, and micro service networking. You have built the foundation of knowledge needed to take a hard look at how networking works inside these new environments. Explore all the new technologies, software, and strategies for implementing and segmenting critical applications in the “cloud native” age and add value to the application projects.”

Community resources:

GitHub’s, PYPL Popularity of Programming Language lists Python as having grown 13.2% in demand in the last 5 years.

Python in the June 2018 TIOBE Index ranks as the fourth most popular language behind Java, C and C++.

Despite the learning curve, having Python in your tool belt is without a question a must have tool.

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A successful career as a software developer or other IT professional requires a solid understanding of software development processes, design patterns, enterprise application architectures, web services, security, networking and much more. The progression from novice to expert can be a daunting endeavor; this is especially true when traversing the learning curve without expert guidance. A common experience is that too much time and money is wasted on a career plan or application due to misinformation.

The Hartmann Software Group understands these issues and addresses them and others during any training engagement. Although no IT educational institution can guarantee career or application development success, HSG can get you closer to your goals at a far faster rate than self paced learning and, arguably, than the competition. Here are the reasons why we are so successful at teaching:

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