def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# get screen_name's tweets
tweets = helper.get_user_timeline(screen_name)
# TODO
analyzer = Analyzer(positives, negatives)
s = tweets
s = str(s)
# analyze word
tw = TweetTokenizer()
#print(tw.tokenize(s))
p = tw.tokenize(s)
score = analyzer.analyze2(p)
positive = float(score[0])
if score[1] < 0:
score[1] = -score[1]
negative = float(score[1])
else:
negative = float(score[1])
neutral = score[2]
# generate chart
chart = helper.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search2():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
if not tweets:
return redirect(url_for("index"))
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
classics = os.path.join(sys.path[0], "classics-words.txt")
arthistory = os.path.join(sys.path[0], "arthistory-words.txt")
tech = os.path.join(sys.path[0], "tech-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives, classics, arthistory, tech)
# initialise classics, arthistory, tech, neutral counters
classics, arthistory, tech, neutral = 0.0, 0.0, 0.0, 0.0
# loop through tweets list to analyse it, adding to counter
for tweet in tweets:
interest = analyzer.analyze2(tweet)
if interest == 'classics':
classics += 1
elif interest == 'arthistory':
arthistory += 1
elif interest == 'tech':
tech += 1
else:
neutral += 1
# generate chart
chart = helpers.chart2(classics, arthistory, tech, neutral)
# render results
return render_template("search2.html", chart=chart, screen_name=screen_name)
