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Simple Python command to extract aggregated keywords from a list of texts in a CSV file column.
# -*- coding: utf-8 -*-
import csv
import codecs, cStringIO
from argparse import ArgumentParser
from monkeylearn import MonkeyLearn
class UTF8Recoder:
"""
Iterator that reads an encoded stream and reencodes the input to UTF-8
"""
def __init__(self, f, encoding):
self.reader = codecs.getreader(encoding)(f)
def __iter__(self):
return self
def next(self):
return self.reader.next().encode("utf-8")
class UnicodeReader:
"""
A CSV reader which will iterate over lines in the CSV file "f",
which is encoded in the given encoding.
"""
def __init__(self, f, dialect=csv.excel, encoding="utf-8", **kwds):
f = UTF8Recoder(f, encoding)
self.reader = csv.reader(f, dialect=dialect, **kwds)
def next(self):
row = self.reader.next()
return [unicode(s, "utf-8") for s in row]
def __iter__(self):
return self
class UnicodeWriter:
"""
A CSV writer which will write rows to CSV file "f",
which is encoded in the given encoding.
"""
def __init__(self, f, dialect=csv.excel, encoding="utf-8", **kwds):
# Redirect output to a queue
self.queue = cStringIO.StringIO()
self.writer = csv.writer(self.queue, dialect=dialect, **kwds)
self.stream = f
self.encoder = codecs.getincrementalencoder(encoding)()
def writerow(self, row):
self.writer.writerow([s.encode("utf-8") for s in row])
# Fetch UTF-8 output from the queue ...
data = self.queue.getvalue()
data = data.decode("utf-8")
# ... and reencode it into the target encoding
data = self.encoder.encode(data)
# write to the target stream
self.stream.write(data)
# empty queue
self.queue.truncate(0)
def writerows(self, rows):
for row in rows:
self.writerow(row)
def parse_args():
parser = ArgumentParser()
parser.add_argument(
'-s',
'--samples',
help='Number of samples to keep.',
type=int,
metavar='samples'
)
parser.add_argument(
'-c',
'--col',
help='Column to use',
type=int,
default=0,
metavar='col'
)
parser.add_argument(
'-k',
'--keywords',
help='Number of keywords to extract.',
type=int,
default=10,
metavar='keywords'
)
parser.add_argument(
'-t',
'--token',
help='Your MonkeyLearn API token.',
type=str,
metavar='token'
)
parser.add_argument(
'file_path',
help='Input csv file to process.',
metavar='path'
)
return parser.parse_args()
if __name__ == "__main__":
args = parse_args()
f = open(args.file_path)
reader = UnicodeReader(f)
MAX_SAMPLES = args.samples
COL = args.col
MAX_KEYWORDS = args.keywords
API_TOKEN = args.token
text = ''
print "Reading data..."
for i, row in enumerate(reader):
text += row[COL]
if i + 1 == MAX_SAMPLES:
break
print "Extracting keywords..."
ml = MonkeyLearn(API_TOKEN)
res = ml.extractors.extract('ex_y7BPYzNG', [text], max_keywords=MAX_KEYWORDS)
for item in res.result[0]:
print item['keyword']
f.close()
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