import time
import text_utils as txu
import twitter_utils as twu
'''
Implementing the second feature which would produce the median for tweets in a file ft2.txt
'''
# Calculate the time when the processing starts
start = time.clock()
# The mode of input can be a text file or twitter api json
inp, outp = txu.extract_arguments()
tweets = twu.get_input(inp)
#initialize the median dictionary
median_dict = {'median': 0.0,
'length': 0}
outfile = open(outp, 'w')
for tweet in tweets:
median_dict = txu.get_median_iterative(tweet, median_dict)
outfile.write("{0:.2f}".format(round(median_dict['median'],2))+"\n")
outfile.close()
# Calculate the time processing ends
end = time.clock()
# Print total time taken
print "Total time taken in processing median: ", end - start
- extracting all URLs in the tweets
- extracting all hashtags in the tweets
- extracting all replyats in the tweets
- get sentiment for each tweet
- get worldwide trending hashtags
'''
def write_csv(data, filename):
with open(filename, 'wb') as csvfile:
writer = csv.writer(csvfile)
writer.writerows(data)
if __name__ == '__main__':
# get path for all outputs
inp, urls, tags, replyats, sentiment, trends = txu.extract_arguments(n=7)
tweets = twu.get_input(inp)
tweets_text = "\n".join(tweets)
# extract all URLs in the tweets and write in a file
start = time.clock()
txu.write_file('\n'.join(txu.get_urls(tweets_text)), urls)
print "Time taken in extracting URLs: ", time.clock() - start
# extract all hashtags in the tweets and write in a file
start = time.clock()
txu.write_file('\n'.join(txu.extract_hashtags(tweets_text)), tags)
print "Time taken in extracting hashtags: ", time.clock() - start
# extract all replyats in the tweets and write in a file
start = time.clock()
import time
import text_utils as txu
import twitter_utils as twu
'''
Implementing the second feature which would produce the median for tweets in a file ft2.txt
'''
# Calculate the time when the processing starts
start = time.clock()
# The mode of input can be a text file or twitter api json
inp, outp = txu.extract_arguments()
tweets = twu.get_input(inp)
#initialize the median dictionary
median_dict = {'median': 0.0, 'length': 0}
outfile = open(outp, 'w')
for tweet in tweets:
median_dict = txu.get_median_iterative(tweet, median_dict)
outfile.write("{0:.2f}".format(round(median_dict['median'], 2)) + "\n")
outfile.close()
# Calculate the time processing ends
end = time.clock()
# Print total time taken
print "Total time taken in processing median: ", end - start
- extracting all replyats in the tweets
- get sentiment for each tweet
- get worldwide trending hashtags
'''
def write_csv(data, filename):
with open(filename, 'wb') as csvfile:
writer = csv.writer(csvfile)
writer.writerows(data)
if __name__ == '__main__':
# get path for all outputs
inp, urls, tags, replyats, sentiment, trends = txu.extract_arguments(n=7)
tweets = twu.get_input(inp)
tweets_text = "\n".join(tweets)
# extract all URLs in the tweets and write in a file
start = time.clock()
txu.write_file('\n'.join(txu.get_urls(tweets_text)), urls)
print "Time taken in extracting URLs: ", time.clock() - start
# extract all hashtags in the tweets and write in a file
start = time.clock()
txu.write_file('\n'.join(txu.extract_hashtags(tweets_text)), tags)
print "Time taken in extracting hashtags: ", time.clock() - start
# extract all replyats in the tweets and write in a file
start = time.clock()
