python - Most Performant Way To Do Imports -

from performance point of view (time or memory) better do:

import pandas pd 

or

from pandas import dataframe, timeseries 

does best thing depend on how many classes i'm importing package?

similarly, i've seen people things like:

def foo(bar):     numpy import array 

why ever want import inside function or method definition? wouldn't mean import being performed every time function called? or avoid namespace collisions?

this micro-optimising, , should not worry this.

modules loaded once per python process. code imports need bind name module or objects defined in module. binding extremely cheap.

moreover, top-level code in your module runs once too, binding takes place once. import in function binding each time function run, again, cheap negligible.

importing in function makes difference 2 reasons: won't put name in global namespace module (so no namespace pollution), , because name local, using name faster using global.

if want improve performance, focus on code being repeated many, many times. importing not it.