These past few days I've been experimenting with something new that I want to use by myself.

Interestingly, this thread below has been written by that.

Let me show you how it looks like. 👇🏻

A thread on HN about bad code in legacy projects both makes me think how little we've learned as a discipline over the years and, honestly, how little credit we give ourselves for some pretty major

Fun going down this list and thinking: "Hmm, plausible at a well-run modern software shop", "Hmm, possible, but requires implausible tradeoffs", "Literally disallowed by languages", and "If you were to attempt doing that our test suite wouldn't let you merge."

I think we as an industry celebrate (not quite the right word) failure too much and don't celebrate success nearly enough. There is no DailyWTF for competent execution, word of which generally stays pretty local to the source while incompetence passes into legend.

Alrighty let me try to thread the needle on being the change I want to see in the world while not giving away anything that will get me in trouble:

Ruby has wonderful developer ergonomics. Typed languages are easier for machines to guarantee the correctness of. We built a type checker for Ruby (and I believe it is slated for OSS release sometime).

c.f.

Two years ago on a weekend, I built a tool to make it easier to evaluate Twitter accounts. Since then 36590 people used it to analyze 55390 different Twitter accounts.

Over the last months @mmkaradeniz and I made a new version. We launched it last night:

@accountanalysis doesn't use machine learning or AI „magic“. Instead of telling users if an account is authentic or not, it helps them to evaluate the accounts themselves.

It visualizes the different features (date, time, type, app, etc.) of Tweets to make them interpretable. /1

@accountanalysis The core concept is still the same, but it looks much better and is easier to operate. Not only for the users, but us developers as well. Enabling us to continuously roll out new features in the future.

Side-by-side screenshots of the old and new version. /2

@accountanalysis Some people had questions what different charts displayed and how they could be interpreted. There are now explanations for all charts, that can be toggled on and off at any time. /3

@accountanalysis The selected/retrieved Tweet count moved to the top to make it clear that not all Tweets of an account are analyzed. 3200 is the API limit by Twitter. It's possible to get more through the Premium API, but I don't think people would pay $100+ for the analysis of one account. /4

Originally, tweet length was 160 minus username length. One day, I turned to Jack and pointed out that I got one more character than him. He said, "That's not fair. We should standardize." I agreed. He said, "How about 140?" I said, "Sure." And he updated the code.

Last year, we upgraded tweet length to 280 and guess what? Use of 'please' is up 54% and 'thank you' is up 22%. I love that! Also, people are asking more questions and having more conversations. All this, and the majority of tweets are still under 140. It worked.

Last up in Privacy Tech for #enigma2021, @xchatty speaking about "IMPLEMENTING DIFFERENTIAL PRIVACY FOR THE 2020

Differential privacy was invented in 2006. Seems like a long time but it's not a long time since a fundamental scientific invention. It took longer than that between the invention of public key cryptography and even the first version of SSL.

But even in 2020, we still can't meet user expectations.
* Data users expect consistent data releases
* Some people call synthetic data "fake data" like
"fake news"
* It's not clear what "quality assurance" and "data exploration" means in a DP framework

We just did the 2020 US census
* required to collect it by the constitution
* but required to maintain privacy by law

But that's hard! What if there were 10 people on the block and all the same sex and age? If you posted something like that, then you would know what everyone's sex and age was on the block.

@zkat__ I'm in the position that I actually find npm / yarn the best ecosystem. Whenever I use something else I always end up stubbing my toe into something thats missing / feels wrong.

Ex. Cargo seems to neither have a concept of devDependencies nor peerDependencies.

I also can't understand why it wouldn't have an "add" command to add a new dependency. And I'm no fan of Toml, json is greate (easy to parse and build tooling around), and the better option in my opinion would be json5.

C / C++ seems to just not have language package managers. The linux / bsd crowd seem to have decided that the system package manager also should be the language package manager. Which might have been fine if every Linux distro used the same system package manager.

Instead we end up with a N x M problem. Where we have a bunch of different operating systems and they all support multiple system package managers. So there's no easy way of distributing, referencing and updating C / C++ packages.

It is also my opinion that the compiler / runtime should be a package dependency. I don't like Rust's split between rustup and cargo (they should have been one tool). Similarly it would be better if you added Node as a dependency to package.json, that way we wouldn't need NVM.