Summon: A Short Essay on Making Music

Making music is, in one sense at least, really hard. I mean that it’s elusive. You can play an instrument by yourself for thousands of hours, as I have, often in a not very productive way, and you can play with others for hundreds of hours, and get hardly any music out of it. Even if you know the chords and you know the lyrics and you know the song form and the audience is clapping and you have the technique, usually something hasn’t quite happened. What isn’t happening all that time? What is music that is so elusive? 

There’s a trend now in discussions of “practice”, both in the strictly musical sense, like how to make your half-hour piano practice more efficient, what techniques to practice. But also in the more general and maybe more Eastern sense of “your practice”, the set of activities you do routinely and with intention to improve your skills and your self. (And by the way I think the conflation of these two different senses of “practice” for people who selling books about these topics.) In both these senses I myself am deficient, and am most often noodling mindlessly on my guitar or not being intentional enough about my actions in any sphere, let alone the musical one. 

On those rare moments when music happens, however, you really feel it. You can be playing something solo or, even better, suddenly find that you and the rest of the band are making something, holy shit!, making music! It’s there!

The way I think of it is like a seance. Playing summons music, though not often. The deepest feeling I have about music is that it’s its own thing, a rare presence in the room, a creation that sits apart from its participants. And isn’t this what art is, after all, what creation is: You made it and now it’s there.

As at a seance (I imagine), you can be “doing” the seance and not quite feeling it. Maybe the table shakes a little bit, maybe someone thinks the air has gotten colder in the corner. But then: the seance works and there is a real manifestation. And everybody knows it. A being has been summoned into this room with us. This is music. We are a string quartet—two violins, a viola, and a cello—but there are five…entities in this room.

Time is one for the main mediums (ha) of this summoning, too: The music has its tempo, and when it’s there you don’t feel like you’re having to keep time for the music. You just feel the music’s time, just as you feel the harmonies. They are there. Present. When the bridge of the jazz standard comes you all drop into it, relaxed in spacious time divisions and fooling with them because the music is with you, non-contingent, not fragile, it’s keeping things going, at the tempo, in that key.

And to summon music, you must of course listen. Even as you are playing. To listen and perform at the same time, even just by yourself, is rare! As rare as music is.

But Show Me *How* Jupyter is the New Excel

These are the slides, notes, and the resulting video from a presentation I gave at TekMountain on Tuesday, September 17th, inspired by the article mentioned below

I read this great article just a few weeks ago called “Jupyter is the New Excel“. I loved it, and was provoked by its premise, and wrote to the author to tell her so. This dominant and for many users intimidating part of the data science toolchain, called a Jupyter notebook, could be used for more everyday tasks. You didn’t have to do data science per se with notebooks, didn’t have to, like, crunch big data, worry about data storage, care what generalized least squares were. Jupyter was easy and useful enough to use for front office tasks, for fantasy football, dinner party invites, what have you. You could fool around with it!

I work at IBM, where I fool around with data science as a rank amateur, and I took the article as a jumping off point: Yes, how? How would Jupyter replace Excel exactly? How could you use Jupyter for your email marketing and fantasy football, for your real estate office spreadsheets?

So I thought I’d create this tech talk, a presentation where we can step through examples of everyday data crunching, the things that many of do now in Excel, see if the article’s premise checks out.

My goal is to introduce Jupyter notebooks very, very briefly, get right into just a few super-practical, everyday tasks, to not talk about data science, to welcome and un-intimidate. If I’m successful, I’ll persuade you that Jupyter notebooks are no more complicated to use than Excel, might work better for some things, can be the kind of ready-to-hand tool that spreadsheets are for many now. This might even be a gateway drug to do some better integrations of your data, which is where Jupyter starts to really outpace all these separate, versioned, weirdo macro-laden spreadsheets, or even be a useful starting point for some data-sciencing on your own :-)

Resources for learning more

Jupyter and Python and a lot of the premier data science tools are open source, which means there are a TON of resources out there for learning, trying. Here are a few good ones, focusing again not on the ocean of data science but on Jupyter notebooks:

Brython, browser-based Python

And if like a new lover or a Taylor Swiftie or a vegan you need your favorite programming language to really be everywhere, there’s Brython, which allows you to put Python code in <script> tags, where it talks to the DOM in a mostly Pythonic way, and have that code translated on the fly into JavaScript and sent to the browser.

Awkward in conception, probably pointless in production, it’s straight forward in execution. Import brython.js, call brython() on load, and you can do stuff like this

from browser import document, alert
def echo(ev):
    alert("Hello {} !".format(document["zone"].value))

document["test"].bind("click", echo)

The gallery shows some more useful things, like doing Ajax requests in Brython, sorting tabular data

But then I don’t know,…In the richer examples, like ones with decorators binding Brython functions to events, it starts to look a little more like a framework, like Flask or something. 

@bind("#get_test", "click")
def get(ev):
             data={"foo": 34})

Since Taylor Swift does country tunes, pop, politics, and emo, maybe it is time to throw out all my other music :-)