I have a python script which is processing a large amount of data from compressed ASCII. After a short period, it runs out of memory. I am not constructing large lists or dicts. The following code illustrates the issue:
import struct
import zlib
import binascii
import numpy as np
import psutil
import os
import gc
process = psutil.Process(os.getpid())
n = 1000000
compressed_data = binascii.b2a_base64(bytearray(zlib.compress(struct.pack('%dB' % n, *np.random.random(n))))).rstrip()
print 'Memory before entering the loop is %d MB' % (process.get_memory_info()[0] / float(2 ** 20))
for i in xrange(2):
print 'Memory before iteration %d is %d MB' % (i, process.get_memory_info()[0] / float(2 ** 20))
byte_array = zlib.decompress(binascii.a2b_base64(compressed_data))
a = np.array(struct.unpack('%dB' % (len(byte_array)), byte_array))
gc.collect()
gc.collect()
print 'Memory after last iteration is %d MB' % (process.get_memory_info()[0] / float(2 ** 20))
It prints:
Memory before entering the loop is 45 MB
Memory before iteration 0 is 45 MB
Memory before iteration 1 is 51 MB
Memory after last iteration is 51 MB
Between the first and second iteration, 6 MB of memory get created. If i run the loop more than two times, the memory usage stays at 51 MB. If I put the code to decompress into its own function and feed it the actual compressed data, the memory usage will continue to grow. I am using Python 2.7. Why is the memory increasing and how can it be corrected? Thank you.