Carefully configured Flask can get up to 1/3rd the speed of other web frameworks. But misconfigure it, use an ORM, or if you're on django, you're serving 1/10th as many requests/sec with significantly higher latency than other languages.
Template rendering takes an appreciable amount of time. I had to replace django's (slow as shit) stock templates with jinja2 on a project because it was taking tens of seconds to render a very large page. Jinja is far faster, but it's still slow enough that I had to add a caching layer to a website that shouldn't need one.
3. Numerical shit
I implemented a video processing algorithm from a paper for a computer vision class. Python's scientific and numeric libraries were sick and made prototyping delightfully easy--then the final runs on the full dataset took forever. What I re-implemented in C++ was >10x faster. Vectorization and other tweaks can make python numerics go faster, but it's a pain in the ass. One of the goals of the Julia scientific programming language is to make loops fast enough that code doesn't have to be manually vectorized.
I work on bare bones low latency systems. Read from a socket->do some basic work->send on a socket.
I prototype in python and use zeromq so i can simply insert a new piece of code in c++ when the time is right. Throughput generally increases 10x or more for the same algorithm
Yeah, there are tradeoffs. SqlAlchemy is by far the most pleasant and thorough ORM to work with, for example. For any language. Full transactional support + every other feature you can dream of.
So, is that bad? Are my systems inferior because they are not "webscale" or "computational pipelines"? I never said I did that. Python is fast enough for what we do.
