Process very large (>20GB) text file line by line
Solution 1:
It's more idiomatic to write your code like this
def ProcessLargeTextFile():
with open("filepath", "r") as r, open("outfilepath", "w") as w:
for line in r:
x, y, z = line.split(' ')[:3]
w.write(line.replace(x,x[:-3]).replace(y,y[:-3]).replace(z,z[:-3]))
The main saving here is to just do the split
once, but if the CPU is not being taxed, this is likely to make very little difference
It may help to save up a few thousand lines at a time and write them in one hit to reduce thrashing of your harddrive. A million lines is only 54MB of RAM!
def ProcessLargeTextFile():
bunchsize = 1000000 # Experiment with different sizes
bunch = []
with open("filepath", "r") as r, open("outfilepath", "w") as w:
for line in r:
x, y, z = line.split(' ')[:3]
bunch.append(line.replace(x,x[:-3]).replace(y,y[:-3]).replace(z,z[:-3]))
if len(bunch) == bunchsize:
w.writelines(bunch)
bunch = []
w.writelines(bunch)
suggested by @Janne, an alternative way to generate the lines
def ProcessLargeTextFile():
bunchsize = 1000000 # Experiment with different sizes
bunch = []
with open("filepath", "r") as r, open("outfilepath", "w") as w:
for line in r:
x, y, z, rest = line.split(' ', 3)
bunch.append(' '.join((x[:-3], y[:-3], z[:-3], rest)))
if len(bunch) == bunchsize:
w.writelines(bunch)
bunch = []
w.writelines(bunch)
Solution 2:
Measure! You got quite some useful hints how to improve your python code and I agree with them. But you should first figure out, what your real problem is. My first steps to find your bottleneck would be:
- Remove any processing from your code. Just read and write the data and measure the speed. If just reading and writing the files is too slow, it's not a problem of your code.
- If just reading and writing is already slow, try to use multiple disks. You are reading and writing at the same time. On the same disc? If yes, try to use different discs and try again.
- Some async io library (Twisted?) might help too.
If you figured out the exact problem, ask again for optimizations of that problem.