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pwordfreq.py
90 lines | 2.5 KiB | text/x-python | PythonLexer
#!/usr/bin/env python
"""Parallel word frequency counter.
This only works for a local cluster, because the filenames are local paths.
"""
import os
import time
import urllib
from itertools import repeat
from wordfreq import print_wordfreq, wordfreq
from IPython.parallel import Client, Reference
from __future__ import division
try: #python2
from urllib import urlretrieve
except ImportError: #python3
from urllib.request import urlretrieve
davinci_url = "http://www.gutenberg.org/cache/epub/5000/pg5000.txt"
def pwordfreq(view, fnames):
"""Parallel word frequency counter.
view - An IPython DirectView
fnames - The filenames containing the split data.
"""
assert len(fnames) == len(view.targets)
view.scatter('fname', fnames, flatten=True)
ar = view.apply(wordfreq, Reference('fname'))
freqs_list = ar.get()
word_set = set()
for f in freqs_list:
word_set.update(f.keys())
freqs = dict(zip(word_set, repeat(0)))
for f in freqs_list:
for word, count in f.items():
freqs[word] += count
return freqs
if __name__ == '__main__':
# Create a Client and View
rc = Client()
view = rc[:]
if not os.path.exists('davinci.txt'):
# download from project gutenberg
print("Downloading Da Vinci's notebooks from Project Gutenberg")
urlretrieve(davinci_url, 'davinci.txt')
# Run the serial version
print("Serial word frequency count:")
text = open('davinci.txt').read()
tic = time.time()
freqs = wordfreq(text)
toc = time.time()
print_wordfreq(freqs, 10)
print("Took %.3f s to calculate"%(toc-tic))
# The parallel version
print("\nParallel word frequency count:")
# split the davinci.txt into one file per engine:
lines = text.splitlines()
nlines = len(lines)
n = len(rc)
block = nlines//n
for i in range(n):
chunk = lines[i*block:i*(block+1)]
with open('davinci%i.txt'%i, 'w') as f:
f.write('\n'.join(chunk))
try: #python2
cwd = os.path.abspath(os.getcwdu())
except AttributeError: #python3
cwd = os.path.abspath(os.getcwd())
fnames = [ os.path.join(cwd, 'davinci%i.txt'%i) for i in range(n)]
tic = time.time()
pfreqs = pwordfreq(view,fnames)
toc = time.time()
print_wordfreq(freqs)
print("Took %.3f s to calculate on %i engines"%(toc-tic, len(view.targets)))
# cleanup split files
map(os.remove, fnames)