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Python is ideally suited for data science and machine learning because 80% of the work tends to be data exploration, transformations and feature engineering and
by sfifs 8y ago
Python is ideally suited for data science and machine learning because 80% of the work tends to be data exploration, transformations and feature engineering and 19% of the work is iterative development of models. In such workflows the lack of type checking & simple REPL is a huge feature. Most of the underlying code for ML is anyway written in Fortran or C and Python becomes a very convenient front end glue
For the 1% work that is actually engineering the model's deployment in production, it's not uncommon to use faster languages with the exported model.
If what you're doing is writing a vanilla CRUD server that gets thousands or hundreds of thousands of hits a second, Python is probably a bad choice.
- makapuf 8y agoUh why ? Thousands of hits per second will generally be IO or DB bound and will be done using clear code and a minimum of boilerplate.
- vonseel 8y agoI’m not sure how many people will ever even work on CRUD apps of that scale. Even a mere 1,000 req/sec adds up to 86.4M per day. That sounds like something at least as popular as Stack Overflow, for example. How many web apps are there, really, that have millions of users?
- pimeys 8y agoOr almost any advertisement tracker server.
- vonseel 8y agoIsn't that market dominated by a few, or at the max, no more than 10-15 companies? My point is just that are there really more than a few dozen or maybe a hundred companies that see more than 1000 req/sec (on web apps)?
- tdfx 8y agoDepends if you're talking maximum or average. Getting to the front page of HN could easily give you a burst of 1000 req/sec. I would agree there's very few CRUD apps that deal with 1000 req/sec on average. On the other hands, there's various APIs and tracking type of services that probably do handle well in excess of that, being run by not-large companies none of us have ever heard of.