Time and memory efficient processing of many intervals for a bigWig file
Assuming you can make a BED file of introns, you can then use the pyBigWig module in python:

import pyBigWig
import numpy

bw = pyBigWig.open("some file.bw")
bed = open("introns.bed")
for line in bed:
    cols = line.strip().split("\t")
    vals = bw.values(cols[0], int(cols[1]), int(cols[2]), numpy=True)
    effLen = cols[2] - cols[1] - (vals &lt; 1.0).sum()
    # Do something with this.


One can make that parallel (with the deeptools API) should it prove too slow. This will only use an appreciable amount of memory for very large introns, since there you need to store the value at each base. One could make this much more memory efficient by using bw.intervals() instead, but that'd require quite a bit more code (you'd need to determine the number of bases overlap per interval and then assume that either each base you want to query has an overlapping interval or, if not, keep track of that fact).