jbnicolai
Joined 13 years ago
Joined 13 years ago
This is where the axiom of choice is interesting; many people feel that it seems intuitively reasonable, but the implications are counterintuitive (e.g. banach-tarski)
"Extraordinary claims require extraordinary evidence"
Always resonated with me as a good summary.Where a (naive) frequentist might assume, for instance, that after a 90% accurate test comes back positive the hypothesis is likely to be true, a Bayesianist would ask how likely it was to be true in the first place; all the test did was make it ten times more likely, which may or may not make it probable.
You may enjoy https://www.lesswrong.com/posts/XTXWPQSEgoMkAupKt/an-intuiti...
> A{2,4} -> AA(A|AA)
Library looks fantastic!
It concerns a large multinational in the transport sector. While we have built up a strong digital department, there's a lot of catching up to do, so the more 'batteries included' any given solution has the better.
On the other hand, it's crucial that we can extend any given tool as there will undoubtedly be unforeseen or non-default scenarios. For example: we'd love to perform some analytics on not just what customers are calling the APIs, but perform more detailed queries based on e.q. request parameters, geoIP, or perhaps even User Agent headers. It is absultely no problem to have to do this ourselves by performing raw queries on the database, and perhaps built our own dashboard around it, but again; if there's something that already covers a lot of these cases that'd be ideal.
The minimum required functionality is that the tool can operate as an authenticating proxy, only passing on requests when the e.g. OAuth2 headers are verified. Other security aspects, such as throttling and rate limiting are a requirement as we're dealing with systems that must be protected from unforeseen load.
Nice to haves are features such as autogenerated documentation pages, where clients can test the APIs from within their browser. On the other hand: rolling this ourselves using Swagger wouldn't be a problem either.
Research so far has included looking at some open source tools, e.g. Kong[1] from Mashable, apigee[2], reading up on Gartner's magic quadrant re. API management, and demos from IBM and CA. Costs of these vendor tools aren't a major concern, lack of modifiability absolutely is. I'm currently leaning towards Kong, but am wondering if others have interesting experiences to share.
[1]: https://getkong.org/ [2]: https://apigee.com/ [3]: https://www.gartner.com/doc/reprints?id=1-2DC669J&ct=150409&...
To make the comparison more fair you'd store the python program and time starting and running both from a shell.
So close to haiku,
only one more syllable,
great embarrassment.Small plug, but I suppose the only people reading these comments are interested in tmux: https://github.com/tmux-plugins