heltonbiker heltonbiker - 6 months ago 14x
Python Question

Improve speed of reading and converting from binary file with python

I know there have been some questions regarding file reading, binary data handling and integer conversion using struct() before, so I come here to ask about a piece of code I have that I think is taking too much time to run. The file being read is a multichannel datasample recording (short integers), with intercalated intervals of data (hence the nested

statements). The code is as follows:

# channel_content is a dictionary, channel_content[channel]['nsamples'] is a string
for rec in xrange(number_of_intervals)):
for channel in channel_names:
[struct.unpack( "h", f.read(2))[0]
for iteration in xrange(int(channel_content[channel]['nsamples']))])

With this code, I get 2.2 seconds per megabyte read with a dual-core with 2Mb RAM, and my files typically have 20+ Mb, which gives some very annoying delay (specially considering another benchmark shareware program I am trying to mirror loads the file WAY faster).

What I would like to know:

  1. If there is some violation of "good practice": bad-arranged loops, repetitive operations that take longer than necessary, use of inefficient container types (dictionaries?), etc.

  2. If this reading speed is normal, or normal to Python, and if reading speed

  3. If creating a C++ compiled extension would be likely to improve performance, and if it would be a recommended approach.

  4. (of course) If anyone suggests some modification to this code, preferrably based on previous experience with similar operations.

Thanks for reading

(I have already posted a few questions about this job of mine, I hope they are all conceptually unrelated, and I also hope not being too repetitive.)

is a list, so I made the correction suggested by @eumiro (remove typoed brackets)

EDIT: I am currently going with Sebastian's suggestion of using
method, and will soon put the final code here. Besides, every contibution has been very useful to me, and I very gladly thank everyone who kindly answered.

Final Form after going with
once, and then alternately extending one array for each channel via slicing the big array:

fullsamples = array('h')
fullsamples.fromfile(f, os.path.getsize(f.filename)/fullsamples.itemsize - f.tell())
position = 0
for rec in xrange(int(self.header['nrecs'])):
for channel in self.channel_labels:
samples = int(self.channel_content[channel]['nsamples'])
position += samples

The speed improvement was VERY impressive over reading the file a bit at a time, or using struct() in any form.


You could use array to read your data:

import array
import os

fn = 'data.bin'
a = array.array('h')
a.fromfile(open(fn, 'rb'), os.path.getsize(fn)/a.itemsize)

It is 40x times faster than struct.unpack from @samplebias's answer.