Simple and Universal: A History of Plain Text, and Why It Matters

My first computer did not have a web browser. But I remember using my first web browser (Mosaic) with some awe. It was the late 90’s and though the web was not nearly as beautiful or functional as it is now, it worked. It was clear — even to my young self — that there was something very special about it. The web had separated text from paper.

Mosaic wasn’t much to look at, but its potential was inspiring nonetheless.

You see, before the web, we were already exploring alternative forms of text, in the context of the “desktop publishing” revolution, whose killer app — especially in media circles — was QuarkXPress. However, even desktop publishing still had a conceptual model of printed pages of text. The “output” of desktop publishing tools was almost always a paper printer. The “publishing” part of “desktop publishing” was “printing”. QuarkXpress and Adobe InDesign fought an epic battle to determine who could generate the best-looking paper, most efficiently.
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You won’t know it when you don’t see it

The NYTimes wrote about a study on how the Chinese government mass fabricates posts on social networks to control public opinion. The studied group is the famed “50 Cent Party” (aka 50c).

Contrary to prior findings, these researchers reveal that these posts are not meant to confront or defend the government, but instead to distract attention away from timely political issues that could result in collective social action. Specifically:

… the 50c party engages in almost no argument of any kind and is instead devoted primarily to cheerleading for the state, symbols of the regime, or the revolutionary history of the Communist Party.

I’ve always thought the best propaganda blends in so well to its surroundings as to not draw any attention. For example, we all see political campaign slogans as discrete pieces of propaganda in the wild, and we can recognize them for what they are.

When we know somewhat was made to support a political campaign, it’s easy to put on one’s own “analysis cap” and cut it down from that perspective. We can detach ourselves from the message, and thus choose not to be influenced by it.
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What is a muckhacker?

Historical Context: back in 2013, I registered a domain and hired a designer to work on a logo for something called MuckHacker.com. I also registered a short domain to go along with it, https://muck.cc. The main goal was to launch my own group writer blog as a way to put myself into the same mindset as the publishers we were serving as customers at Parse.ly. The topical focus was going to be media criticism. This post laid out why I picked the name “MuckHacker”. Eventually, this project became a “Custom Domain” at Medium.com. But, over time, I relocated the “MuckHacker content” that was published over the years back to this blog. All the posts from the MuckHacker group blog, which operated from 2014-2017, can be found via this post listing with the “muckhacker” tag.

Some definitions of related terms may be helpful:

  • muck, n: something sordid or corrupt
  • hack, n: a colloquial term for a writer or journalist
  • hacker, n: an enthusiastic or skillful computer programmer, often associated with the Free Software movement
  • hacker, n: someone who seeks and exploits weaknesses in a computer system or computer network
  • muck, v: to mishandle or spoil something
  • hack, v: to cut with rough or heavy blows
  • muckraker, n: a writer who investigates and publishes truthful reports to perform an auditing or watchdog function

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The media and “objectivity”

Chomsky — the same one behind “Manufacturing Consent”, an excellent analysis of newspaper and TV journalism in the pre-Internet era — walks us through a structural analysis of modern media here:

There is a concept of “objectivity” to which journalists are supposed to adhere: report honestly what is “within the Beltway” — that is, what is considered acceptable by major power centers, state and private. Departing from that framework is “biased.” There are to be sure exceptions, but there extensive documentation showing that this framework is upheld with quite impressive consistency. It can be changed in so many ways.


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An async kind of pair programming

Can pair programming be done in a way that is compatible with async communication?

async_jam

Pair programming is described by the original c2 wiki as a process in which “two engineers participate in one development effort at one workstation”. It would seem the process is inherently synchronous, at least as originally described and practiced.

I experimented with pair programming at my first industrial programming job at Morgan Stanley. It was 2006-2008 and two fads were happening in parallel: “agile” software management techniques and “extreme programming”, with a particular emphasis on test-driven development with Java.

I occasionally found pair programming to be effective, but noticed my results varied wildly depending on the engineer I paired with and the problem we worked on. Some people really enjoyed the “brain swarming” of having two heads attack a problem. Other people found it cumbersome and interruptive. Some problems seemed so indivisible that it always ended up that one person drove, and the other person merely watched. In the end, I couldn’t really say whether I benefited from it, despite many hours of experimentation.

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Simple Lego Blocks for Big Data

Data engineers should abstract their code in the most lightweight way possible to facilitate downstream integration in a large-scale data system.

You want lego blocks, not puzzle pieces.

lego_blocks

The creators of the C programming language once famously said, “first make it work, then make it right, and, finally, make it fast.” This adage still applies today.

The difference is, we have tools to take working code and validate that it is right against reams of data. Many of these tools can also be used to make the working, right code run really fast across a cluster of machines, possibly even in real-time, as the data comes in.

But, making code work, then right, then fast, requires some discipline.

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Idiomatic Python Resources

Let’s say you’ve just joined my team and want to become an idiomatic Python programmer. Where do you begin?

Well, you can move up the learning curve quickly using resources from this blog:

I also have some good resources on web development with Python:

And on more advanced Python concepts, like dunders and functional programming:

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Programming: it’s weird

I read the Bloomberg piece, What Is Code?, an explanation of code artistry and programmer/hacker culture in 2015. I love this paragraph about “languages as liquid infrastructure”:

The point is that things are fluid in the world of programming, fluid in a way that other industries don’t seem to be. Languages are liquid infrastructure. You download a few programs and, whoa, suddenly you have a working Clojure environment. Which is actually the Java Runtime Environment. You grab an old PC that’s outlived its usefulness, put Linux on it, and suddenly you have a powerful Web server. Now you can participate in whole new cultures. There are meetups, gatherings, conferences, blogs, and people chatting on Twitter. And you are welcomed. They are glad for the new blood.

Java was supposed to supplant C and run on smart jewelry. Now it runs application servers, hosts Lisplike languages, and is the core language of the Android operating system. It runs on billions of things. It won. C and C++, which it was designed to supplant, also won. A lot of things keep winning because computers keep getting more plentiful. It’s weird.


Worse is better, is worse, is better, is worse, is better…

The 3 Best Python Books for Your Team

Python was the core programming language used at Parse.ly. It is a widely-used language with huge adoption among open source projects. It’s no wonder it’s one of the leading languages for software teams.

I’ve written a couple of blog posts with original material for learning Python, including “import this: learning the Zen of Python with code and slides” and “Build a web app fast”.

Newcomers to Python are often overwhelmed by the wealth of information, available online and in print, for the language. I am often asked by others, “What are the best books for my Python team?” I plan to answer that question with this post, by highlighting what I consider to be the three best Python books on the market today.

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Picking tech stacks

I realize now that one of the hardest parts of running a successful startup is “betting” on tech stacks that, 3 years out, will have a groundswell of community support around them.

It’s still shocking to me that when I chose each of the following technologies as a central part of Parse.ly, they were so new/immature as to not even show up on a Google search trends box, but are now very popular technologies.

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