What it means to “go pro” in data science

A look at what it takes to be a professional data science programmer.

Noahs_Ark_Paul_K_FlickrMy experience of being a data scientist is not at all like what I’ve read in books and blogs. I’ve read about data scientists working for digital superstar companies. They sound like heroes writing automated (near sentient) algorithms constantly churning out insights. I’ve read about MacGyver-like data scientist hackers who save the day by cobbling together data products from whatever raw material they have around.

The data products my team creates are not important enough to justify huge enterprise-wide infrastructures. It’s just not worth it to invest in hyper-efficient automation and production control. On the other hand, our data products influence important decisions in the enterprise, and it’s important that our efforts scale. We can’t afford to do things manually all the time, and we need efficient ways of sharing results with tens of thousands of people.

There are a lot of us out there — the “regular” data scientists; we’re more organized than hackers but with no need for a superhero-style data science lair. A group of us met and held a speed ideation event, where we brainstormed on the best practices we need to write solid code. This article is a summary of the conversation and an attempt to collect our knowledge, distill it, and present it in one place. Read more…

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Building C# objects dynamically

Using ExpandoObject to create objects that you can add properties, methods, and events to.

Buy “C# 6.0 Cookbook” in early release.
Editor’s note: This is an excerpt from “C# 6.0 Cookbook,” by Jay Hilyard and Stephen Teilhet. It offers more than 150 code recipes to common and not-so-common problems that C# programmers face every day. In it, you’ll find recipes on asynchronous methods, dynamic objects, enhanced error handling, the Rosyln compiler, and more.


You want to be able to build up an object to work with on the fly at runtime.


Use ExpandoObject to create an object that you can add properties, methods, and events to and be able to data bind to in a user interface.

We can use ExpandoObject to create an initial object to hold the Name and current Country of a person.


Once we have added properties directly, we can also add properties to our object in a more dynamic fashion using the AddProperty method we have provided for you. One example of why you might do this is to add properties to your object from another source of data. We will add the Language property.

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Get started with functional programming in Python

Start writing shorter and less bug-prone Python code.

It is hard to get a consistent opinion on just what functional programming is, even from functional programmers themselves. A story about elephants and blind men seems apropos here. Usually we can contrast functional programming with “imperative programming” (what you do in languages like C, Pascal, C++, Java, Perl, Awk, TCL, and most others, at least for the most part). Functional programming is not object-oriented programming (OOP), although some languages are both. And it is not Logic Programming (e.g., Prolog).

I would roughly characterize functional programming as having at least several of the following characteristics:

  • Functions are first class (objects). That is, everything you can do with “data” can be done with functions themselves (such as passing a function to another function). Moreover, much functional programming utilizes “higher order” functions (in other words, functions that operate on functions that operate on functions).
  • Functional languages eschew side effects. This excludes the almost ubiquitous pattern in imperative languages of assigning first one, then another value to the same variable to track the program state.
  • In functional programming we focus not on constructing a data collection but rather on describing “what” that data collection consists of. When one simply thinks, “Here’s some data, what do I need to do with it?” rather than the mechanism of constructing the data, more direct reasoning is often possible.

Functional programming often makes for more rapidly developed, shorter, and less bug-prone code. Moreover, high theorists of computer science, logic, and math find it a lot easier to prove formal properties of functional languages and programs than of imperative languages and programs.

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How reactive applications adapt

The principles of reactive applications facilitate adaptation.


One of the fascinating things found in nature is the ability of a species to adapt to its changing environment. The canonical example of this is Britain’s Peppered Moth. When newly industrialized Great Britain became polluted in the nineteenth century, slow-growing, light-colored lichens that covered trees died and resulted in a blackening of the trees bark. The impact of this was quite profound: lightly-colored peppered moths, which historically had been well camouflaged and the majority, now found themselves the obvious target of many a hungry bird. Their rare, dark-colored sibling, who had been conspicuous before, now blended into their recently polluted ecosystem. As the birds, changed from eating dark-colored to light-colored moths, the previously common light-colored moth became the minority, and the dynamics of Britain’s moth population changed.

So what do moths have to do with programming? Read more…

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4 ways the Raspberry Pi is being used in education

Get inspired to create, teach, and learn with the Raspberry Pi.


The Raspberry Pi is a small computer that can be used for a variety of projects, and has been heralded as a great boon to education due to its flexibility and simplicity. While PcPro magazine noted in January of 2014 that Pi’s were “gathering dust” in classrooms, production has not ceased. The usage map is pretty impressive and the Raspberry Pi 2 was recently released.

In February of this year, the Raspberry Pi Foundation announced that they’re starting a mentoring program for people 16-21 years old. Here are four other ways that the Pi is being used in education and growing the tech community.

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Learn a C-style language

Improve your odds with the lingua franca of computing.

You have a lot of choices when you’re picking a programming language to learn. If you look around the web development world, you’ll see a lot of JavaScript. At universities and high schools, you’ll often find Python used as a teaching language. If you go to conferences with language theorists, like Strange Loop, you’ll hear a lot about functional languages, such as Haskell, Scala, and Erlang. This level of choice is good: many languages mean that the overall state of the field is continually evolving, and coming up with new solutions. That choice also leads to a certain amount of confusion regarding what you should learn. It’s not possible to learn every language out there, even if you wanted to. Depending on the area you’re in, the choice of language may be made for you. For the overall health of your career, and to provide you the widest range of future opportunities, the single most useful language-related thing you can do is learn a C-style language.

A boring old C-style language just like millions of developers learned before you, going back to the 1980s and earlier. It’s not flashy, it’s usually not cutting edge, but it is smart. Even if you don’t stick with it, or program in it on a daily basis, having a C-style language in your repertoire is a no-brainer if you want to be taken seriously as a developer.
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