2019#27 Readings of the Week

October 12, 2019 4 minutes read | 730 words by Ruben Berenguel

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Some data engineering, a bit of Haskell, programming music, Python and random bits and bobs. I recommend you play with the third. Several good books this week, as I have ramped up my reading: current goal would be 52 this year.

NOTE: The themes are varied, and some links below are affiliate links. Some data engineering, a bit of Haskell, programming music, Python. Expect a similar wide range in the future as well. You can check all my weekly readings by checking the tag here . You can also get these as a weekly newsletter by subscribing here.

Whither Literate Programming — What went wrong?

I tried literate programming for a personal project many years ago (with emacs, it was Javascript), and the main problem is when you are not sure how you will implement something and need to repeatedly refactor: you also need to refactor your explanation, which is painful.

You are already smart enough to write Haskell

I’m inching closer to writing some Haskell code for realz…

That Music You’re Dancing To? It’s Code

I met Sam Aaron (and Sonic Pi) at Scala World, I was at his Sonic Pi workshop as well. On my task manager, I have specifically “play with Sonic Pi”. I love making sounds, and Sonic Pi is awesome. I’d recommend Sam’s Scala World presentation.

PEP 603 – Adding a frozenmap type to collections

We are inching closer to Python 4 = Scala 3.

Data Lake at Robinhood

I like their write up and engine choices.

Interview with Weld’s main contributor: accelerating numpy, scikit and pandas as much as 100x with Rust and LLVM

Rust was not the first language in which Weld was implemented; the first implementation was in Scala, which was chosen because of its algebraic data types and powerful pattern matching. This made writing the optimizer, which is the core part of the compiler, very easy. Our original optimizer was based on the design of Catalyst, which is Spark SQL’s extensible optimizer. We moved away from Scala because it was too difficult to embed a JVM-based language into other runtimes and languages.

Pipenv: A Guide to the New Python Packaging Tool

Handling deployable dependencies with pipenv is pretty easy. For managing my local environments I still prefer pyenv (with pyenv-virtualenv) but I could see pipenv superseding it.

Venture Capital Is Putting Its Money Into Astrology

I see less money in your future.

If someone told you they know Python, what would you expect them to know?

A reddit thread I found interesting

Python Negatypes

Hillel Wayne always writes interesting stuff. Also he just created a newsletter. Join it.

The Right Answer? 8,186,699,633,530,061 (An Abacus Makes It Look Almost Easy)

What can I say? I’m a sucker for mechanical computers.

📚 Skunk Works: A Personal Memoir of My Years of Lockheed

This was an excellent read. Covering the history of some of the more iconic airplanes of the 20th century (U-2, F-117A, SR-71), how they came to be and also comes with some lessons which, in hindsight, can be applied to Agile if you want.

🔊 Blitzscaling: The Lightning-Fast Path to Building Massively Valuable Companies

I may be unfair to it, but it was a downer. Based on Reid Hoffman’s podcast Masters of Scale, it lacks the punch and edition the podcast enjoy. It may be excellent if you haven’t heard his podcast, but the podcast is 10x better, and free.

📚 Doorways in the sand

I’m a big Roger Zelazny fan (I’m slowly working to have all his books in paperback or hardcover) and this is quite fun. Bringing some reminisces of the Hammett’s flair in the first Amber book and the absurd of Slaughterhouse-5. I may be biased, I really like his writing.

📚 The Productivity Project: Accomplishing More by Managing Your Time, Attention, and Energy

I found this book way better than his newest Hyperfocus , but the latter gets more coverage these days (in any case, if you feel like reading some productivity pr0n and have already read Getting Things Done, go for Atomic Habits).

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