I am not testing this use-case. But a related
use-case might highlight why speed did never
hurt anybody.
Lets say you program a flying drone with Python,
and the measurement is from the drone sensor
and communication systems.
Lets say you are using the idle time between
measurements for some complex planning. It
is then not true that you have anyway
to wait for the measurement.
Hope this helps!
BTW: If somebody knows another Python implementation
I am happy to test this implementation as well.
I am assuming that the standard Python python.exe
I tested amounts to CPython? Not sure. And the
GraalVM is practically the same as JPython? Not
sure either.
Opinion: Anyone who is counting on Python
for truly fast compute speed is probably using
Python for the wrong purpose.
Here, we use Python to control Test Equipment,
to set up the equipment and ask for a measurement,
get it, and proceed to the next measurement; and
at the end produce a nice formatted report.
If we wrote the test script in C or Rust or
whatever it could not run substantially faster
because it is communicating with the test equipment,
setting it up and waiting for responses, and
that is where the vast majority of the time goes.
Especially if the measurement result requires
averaging it can take a while. In my opinion
this is an ideal use for Python, not just because
the speed of Python is not important, but also
because we can easily find people who know Python,
who like coding in Python, and will join the
company to program in Python ... and stay with us.
--- Joseph S.
--
https://mail.python.org/mailman/listinfo/python-list
