Invoking an external command in Python is a two step process:

from subprocess import call
call(["ls","-1"])

Python and Ruby, each with roots going back into the 1990s, are two of the most popular interpreted programming languages today. Ruby is most widely known as the language in which the ubiquitous Ruby on Rails web application framework is written, but it also has legions of fans that use it for things that have nothing to do with the web. Python is a big hit in the numerical and scientific computing communities at the present time, rapidly displacing such longtime stalwarts as R when it comes to these applications. It too, however, is also put to a myriad of other uses, and the two languages probably vie for the title when it comes to how flexible their users find them.

A Matter of Personality...

That isn't to say that there aren't some major, immediately noticeable, differences between the two programming tongues. Ruby is famous for its flexibility and eagerness to please; it is seen by many as a cleaned-up continuation of Perl's "Do What I Mean" philosophy, whereby the interpreter does its best to figure out the meaning of evening non-canonical syntactic constructs. In fact, the language's creator, Yukihiro Matsumoto, chose his brainchild's name in homage to that earlier language's gemstone-inspired moniker.

Python, on the other hand, takes a very different tact. In a famous Python Enhancement Proposal called "The Zen of Python," longtime Pythonista Tim Peters declared it to be preferable that there should only be a single obvious way to do anything. Python enthusiasts and programmers, then, generally prize unanimity of style over syntactic flexibility compared to those who choose Ruby, and this shows in the code they create. Even Python's whitespace-sensitive parsing has a feel of lending clarity through syntactical enforcement that is very much at odds with the much fuzzier style of typical Ruby code.

For example, Python's much-admired list comprehension feature serves as the most obvious way to build up certain kinds of lists according to initial conditions:

a = [x**3 for x in range(10,20)]
b = [y for y in a if y % 2 == 0]

first builds up a list of the cubes of all of the numbers between 10 and 19 (yes, 19), assigning the result to 'a'. A second list of those elements in 'a' which are even is then stored in 'b'. One natural way to do this in Ruby is probably:

a = (10..19).map {|x| x ** 3}
b = a.select {|y| y.even?}

but there are a number of obvious alternatives, such as:

a = (10..19).collect do |x|
x ** 3
end

b = a.find_all do |y|
y % 2 == 0
end

It tends to be a little easier to come up with equally viable, but syntactically distinct, solutions in Ruby compared to Python, even for relatively simple tasks like the above. That is not to say that Ruby is a messy language, either; it is merely that it is somewhat freer and more forgiving than Python is, and many consider Python's relative purity in this regard a real advantage when it comes to writing clear, easily understandable code.

And Somewhat One of Performance

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.”

A project manager acts as the primary link between business and technical teams. A project manager is responsible for maintaining the project schedule, developing project estimates, working with external teams and tracking project issues. The project manager belongs to either the technical team or the project management office (PMO). The project manager works with business teams, technical teams, business counterparts, testing resources, vendors and infrastructure teams.

A project manager is often challenged with diagonally opposite views from the business side and technical side. A project manager’s success depends on balancing the needs and emotions of both sides.

Understanding the Requirements
A project manager must familiarize with the project’s requirements as defined by the business or product managers. This will help you understand the business vision behind the project. You will need this knowledge while negotiating with the technical teams.

Understanding the Technical Landscape
A project manager must also understand the technical systems, resource skills and infrastructure capabilities available for the project. Business teams come up with expectations that are sometimes beyond the capabilities of the technology team. It is the responsibility of the project manager to understand the technical capabilities available to the project.

Walkthrough of Business Requirements
This is a critical step in the project delivery process. The project manager must invite members from the business team, technical team, testing team, infrastructure team and vendors. The project manager must encourage the various stakeholders to ask questions about the requirements. Any prototypes available must be demonstrated in this meeting. The project manager must find answers to all questions resulting from the requirements walkthrough. The project manager must get the final version of the requirements approved by all stakeholders.

Managing Conflicts in Timelines and Budgets
All project managers will face the conflicts arising from shortened timelines and limited budgets. Business teams typically demand many features that are nearly impossible to deliver within short timeframes. The project manager must work with business and technical teams to prioritize the requirements. If the project is executed in a product development organization, then the project manager could utilize agile methodologies to deliver projects incrementally. In this case, the project manager may be required to act as a scrum master to facilitate scrum meetings between various stakeholders.

The Art of Saying “No”
As a project manager, you may be forced to say “no” to demands from both business and technology teams. However, it is important to create a win-win situation for all parties when you are faced with conflicting demands. You can work with the stakeholders individually before bringing all parties together. Most stakeholders prefer to work together. The success of a project manager depends on how effectively he or she can bring out the best in everyone, driving everyone towards a common goal.

Finally, the job of a project manager is not to satisfy the demands from all corners. The project manager must identify the essential deliverables that will meet the business needs, with a solid understanding of what is possible within the limits of technology.

Related:

Smart Project Management: Best Practices of Good Managers

Is Agism an Issue in IT?