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Unlike Java, Python does not have a string contains method. Instead, use the in operator or the find method. The in operator finds treats the string as a word list whereas the find method looks for substrings. In the example shown below, 'is' is a substring of this but not a word by itself. Therefore, find recoginizes 'is' in this while the in operator does not.

s = "This be a string"
if s.find("is") == -1:
    print "No 'is' here!"
else:
    print "Found 'is' in the string."
    
if "is" in s:
    print "No 'is' here!"
else:
    print "Found 'is' in the string."

#prints out the following:
Found 'is' in the string
No 'is' here!

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.

Finding the Right Candidate from a Recruiters Perspective

[Mar, 23, 2017] |
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I’ve been a technical recruiter for several years, let’s just say a long time. I’ll never forget how my first deal went bad and the lesson I learned from that experience. I was new to recruiting but had been a very good sales person in my previous position. I was about to place my first contractor on an assignment. I thought everything was fine. I nurtured and guided my candidate through the interview process with constant communication throughout. The candidate was very responsive throughout the process. From my initial contact with him, to the phone interview all went well and now he was completing his onsite interview with the hiring manager.

Shortly thereafter, I received the call from the hiring manager that my candidate was the chosen one for the contract position, I was thrilled. All my hard work had paid off. I was going to be a success at this new game! The entire office was thrilled for me, including my co-workers and my bosses. I made a good win-win deal. It was good pay for my candidate and a good margin for my recruiting firm. Everyone was happy.

I left a voicemail message for my candidate so I could deliver the good news. He had agreed to call me immediately after the interview so I could get his assessment of how well it went. Although, I heard from the hiring manager, there was no word from him. While waiting for his call back, I received a call from a Mercedes dealership to verify his employment for a car he was trying to lease. Technically he wasn’t working for us as he had not signed the contract yet…. nor, had he discussed this topic with me. I told the Mercedes office that I would get back to them. Still not having heard back from the candidate, I left him another message and mentioned the call I just received. Eventually he called back. He wanted more money.

I told him that would be impossible as he and I had previously agreed on his hourly rate and it was fine with him. I asked him what had changed since that agreement. He said he made had made much more money in doing the same thing when he lived in California. I reminded him this is a less costly marketplace than where he was living in California. I told him if he signed the deal I would be able to call the car dealership back and confirm that he was employed with us. He agreed to sign the deal.

How Can Business Analysts Use Python?

[Apr, 01, 2014] |
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The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.

Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.

Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.

Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.

This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.

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the hartmann software group advantage

why take Crystal Reports Training with the hartmann software group?

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:

Learn from the experts.
1. We have provided software development and other IT related training to many major corporations in Germany since 2002.
2. Our educators have years of consulting and training experience; moreover, we require each trainer to have cross-discipline expertise i.e. be Java and .NET experts so that you get a broad understanding of how industry wide experts work and think.
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