Which company? Octobus? As per their website, there are only 2 people, and Pierre-Yves David (“marmoute”) is a well know core Mercurial contributor. The company itself is about providing commercial support for Mercurial, along with other stuff like Python contracting.

I use Mercurial at work. My company uses Git, but I use Mercurial and clone, push, and pull transparently thanks to hg-git. I’ve noticed I am generally more aware than my Git-using colleagues of recent changes to the repo, because I’ve got a pre-pull hook set up to run hg incoming (with a tweak to avoid double network talk).

Yes indeed. For those unfamiliar, here are (from the link) examples of the two docstring styles that Napoleon (a Sphinx extension) parses and renders. PyCharm, too, parses Numpy and Google docstrings and uses the information for tooltips, static analysis, etc.

Google style:

    """Summary line.

    Extended description of function.

    Args:
        arg1 (int): Description of arg1
        arg2 (str): Description of arg2

    Returns:
        bool: Description of return value

    """
    return True

NumPy style:

    """Summary line.

    Extended description of function.

    Parameters
    ----------
    arg1 : int
        Description of arg1
    arg2 : str
        Description of arg2

    Returns
    -------
    bool
        Description of return value

    """
    return True

buried in there are a couple of good reflections on the role of toolmakers in the pursuit of independence.

We cannot be free until we control the means of production? That sounds like a good reflection, all right :-)

(Note: this may sound like I’m trying to rile you. I’m not, I am genuinely amused to see Marx echoed in this unexpected context.)

Come and Take It: The Gun Printer’s Guide to Thinking Free, by Cody Wilson of Defense Distributed fame. I finished this probably a week before the current kerfluffle started. There’s a whoooole lot of self-congratulatory bullshit and bluster in this, as Wilson is first and foremost (in my opinion) an attention whore, but buried in there are a couple of good reflections on the role of toolmakers in the pursuit of independence.

This was on my reading list; but, after I did the ’ol Amazon “Look Inside,” I took it off because it looked like the signal/noise would be unacceptable. Please give a shout if it ends up being worthwhile. I watched a few of his pre-DD/early-DD lectures on philosopy, and the guy gave me stuff to chew on.

Mods, can I merge this (‘my’) submission with/into the submission that contains the official announcement? (I couldn’t find an official way to propose a merge, hence this comment.)

I agree. Finding good feeds is difficult indeed, but I believe that good content does spread by word at some point (it may even be word in social media, actually). Feeds that post too much are definitely a problem. Following RSS/Atom feeds of newspapers specifically defeats the purpose. Nobody can manage this hilarious amount of posts, often barely categorised. I don’t have a solution for these at hand; this article suggests that the standard should be improved on this. It might be a good idea to do so.

Excerpt feeds I don’t like, because they are hard to search using the feed reader’s search facilities. I however still prefer an excerpt feed over no feed at all, which is why the article mentions this as a possible compromise. The main reason for excerpt feeds appears to be to draw people into the site owner’s Google Analytics.

the main problem I had was discovering good feeds

This is why my killer feature (originally of GOOG Reader and now of NewsBlur) is a friends/sharing system. The value of shared content is deeply rooted in discovery of new feeds.

feeds only contain the first few lines of a article

Modern feed readers generally support making it easy to get full articles / stories without a context switch.

feeds that just post too much, making it impossible to keep up

Powerful filtration is also another place where modern readers have innovated. Would definitely check them out, because these are solved problems.

Would like to hear your thoughts here after you try it for a couple of days.

but the result isn’t surprising from a geometric point of view.

In this case I myself would go for the ‘did I see it coming’ definition of surprise, rather than ‘is it unlikely to occur’. Otherwise, no maths could ever be surprising, could it? I’m personally fond of the phrase ‘surprising yet inevitable’ – I got it from Howard Tayler talking about fiction writing, and apparently it was first said by Aristoteles, but it’s neat for this sort of thing, too.

Also, thanks for the n!-based explanation, that was new (and surprising!) to me.

So this is a really late reply, but you sparked a thought: this is exactly what is currently happening in R, with the recent Hadley-inspired flood of packages that use non-standard evaluation to deliver interfaces that are super nice for interactive use (because the function takes care of evaluating your arguments in the context of the dataset argument).

Hey. I understand the reasons behind the downvote and that also helps me understand better what I should or shouldn’t post. I’ll take this feedback into account for future submissions.

This is not about Android, but about the Google Search monopoly. If you feel like it, read the announcement: it’s amazingly clear writing, a joy to read.

Excerpt, emphasis added:

The Commission decision concerns three specific types of contractual restrictions that Google has imposed on device manufacturers and mobile network operators. These have enabled Google to use Android as a vehicle to cement the dominance of its search engine. In other words, the Commission decision does not question the open source model or the Android operating system as such.

There are a couple of obvious things:

• the abuse in question is to do with Google search, Android is just a tool in this case
• Apple has a relatively small market share, so presumably consumers have a choice of buying one of the many android phones.

Aside from that, I suppose platform restrictions don’t get classified as monopolistic behaviour.

Ahhhhh no “class” meaning year. We are recent college graduates!

You’re right, that’s an odd choice by the 6(!) flaggers. The article seems fine to me, too. Unless I, too, am missing something.

Too late to edit, so here’s a reply, instead. Re: the cheat gem:

• it turns out that Chris Wanstrath’s (cheat)[http://errtheblog.com/posts/21-cheat] from 2006 still works! gem install --user cheat; cheat cheat, and away you go. Some features don’t work, though: cheat sheets and cheat recent to show all (recent) sheets both get 404 errors.
• cheat --edit sadly does not currently work. The --edit option was the best thing about the cheat gem: it was a command-line wiki, not a lookup tool.

Re: cheat.sh:

• cheat.sh isn’t wiki-like, but serves content from various cheat sheet repositories, instead. Some repos get special URLs: /:learn returns the relevant https://learnxinyminutes.com lesson, for example.
• cheat.sh does let you edit sheets in the browser, though, and will auto-submit merge requests.
• Nifty syntax highlighting, too.
• Also, does cheat.sh have hierarchical namespaces? Running cht.sh python/:list returned a short list of entries, including doc, that suggested that, but the servers overloaded before I could check cht.sh python/doc/:list. My experience with wikis both flat and nested has led me to strongly prefer flat namespaces over nested ones for general reference works, but good search covers a multitude of sins.

That was also my number one takeaway from the article. I knew about compiling to WASM targets but had no idea the front end story included full frameworks like Yew.

You don’t need ML/AI. You need data queries and business logic.

I think that hits on an important point that the article misses (or sidesteps): business logic. SQL is only helpful if you can describe what you’re looking for, and doing that requires knowledge and skill.

When you lack the ability to describe what you’re looking for, then SQL seems useless, and ML seems magically useful. Of course, you’ll still end up doing that work if you opt for an ML approach, it will just be less obvious.

(digression: this parallels the problem of not being able to describe what you’re storing, which leads to poor usage of NoSQL databases)

Now, if you have a broad notion of what you’re looking for, and a willingness to experiment, then ML (well, analysis of any kind) can help. What about the contents of a basket can be a predictor for returning after a reminder email? What is the right size of a coupon to entice people back while minimizing cost? What is the right period of time to contact someone after an absence? More customers/transactions/views/baskets means more leeway to experiment, which means more data, which means more use cases for an ML-style approach.

But, yes, absolutely, simple querying will be a better ROI until you get hyuuge.

I only did that because medum’s support for inline code is awful. (It stripped newlines and replaced them with 80 spaces, for some reason…) I’m glad it worked out, though :)