global df

global author1

global author2

global author1_name

global author2_name

global startDate

global endDate

with open(textFile, encoding ="utf8") as data_file:

data = json.load(data_file)

df = json_normalize(data, 'messages', record_prefix='message_')

df = df[df['message_text'].apply(type) == str]

df = df[df['message_type']== 'message']

df = df[['message_date', 'message_from','message_text']]

df[['Date','Time']] = df.message_date.str.split("T",expand=True,)

df.drop(columns=['message_date'],inplace=True)

df.columns = ['Author','Message','Date','Time']

df = df[['Date','Time','Author','Message']]

df['Hour'] = df['Time']

def getHour(time):

return time.split(':')[0]

df['Hour'] = df['Hour'].map(getHour)

authors = df['Author'].unique()

author1 = authors[0]

author2 = authors[1]

try:

uchr = unichr # Python 2

if sys.maxunicode == 0xffff:

# narrow build, define alternative unichr encoding to surrogate pairs

# as unichr(sys.maxunicode + 1) fails.

def uchr(codepoint):

return (unichr(codepoint) if codepoint <= sys.maxunicode\

else unichr(codepoint - 0x010000 >> 10 | 0xD800) + unichr(codepoint & 0x3FF | 0xDC00))

except NameError:

uchr = chr # Python 3

# Unicode 11.0 Emoji Component map (deemed safe to remove)

_removable_emoji_components = ((0x20E3, 0xFE0F), range(0x1F1E6, 0x1F1FF + 1), range(0x1F3FB, 0x1F3FF + 1), range(0x1F9B0, 0x1F9B3 + 1), range(0xE0020, 0xE007F + 1),)

emoji_components = re.compile(u'({})'.format(u'|'.join([re.escape(uchr(c)) for r in _removable_emoji_components for c in r])), flags=re.UNICODE)

def remove_emoji(text, remove_components=False):

cleaned = emoji.get_emoji_regexp().sub(u'', text)

if remove_components:

cleaned = emoji_components.sub(u'', cleaned)

return cleaned

author1_name = remove_emoji(authors[0])

author1_name = author1_name.strip()

if author1_name == '':

author1_name = 'Author 1'

author2_name = remove_emoji(authors[1])

author2_name = author2_name.strip()

if author2_name == '':

author2_name = 'Author 2'

media_messages_df = df[df['Message'] == '<Media omitted>']

df= df.drop(media_messages_df.index) #to drop the media files

df = df.loc[(df['Author'] == author1)|(df['Author'] == author2)]

df['Date'] = pd.to_datetime(df['Date'])

df['Day_of_week'] = df['Date'].dt.day_name()

global df

global author1

global author2

global author1_name

global author2_name

global startDate

global endDate

def isNewMessage(line):

result = False

NewLinePattern = ["(\d+\/\d+\/\d+)(,)(\s)(\d+(:)\d+)(\s)(\w+)(\s)(-)(\s)(\w+)",\

"(\d+\/\d+\/\d+)(,)(\s)(\d+(:)\d+)(\s)(-)(\s)(\w+)"]

for x in NewLinePattern:

if re.match(x,line):

result = True

return result

def standardizeDate(str):

return str.split('/')[2] + "-" + str.split('/')[1] + "-" + str.split('/')[0]

def standardizeTime(time):

time = time.strip()

if "pm" or "am" in time:

if "am" in time:

time = time.split(' ')[0]

if len(time) == 4:

time = "0" + time

return time

if "pm" in time:

time = time.split(' ')[0]

time = str(int(time.split(':')[0]) + 12) + ":" + time.split(':')[1]

return time

return time

def splitData(line):

if isNewMessage(line):

date = line.split(',')[0]

date = standardizeDate(date)

time = line.split(',')[1].split('-')[0]

time = standardizeTime(time)

author = line.split('-')[1].split(':')[0]

author = author.strip()

message = line.split(':')[2:]

message = ''.join(map(str,message))

message = message.strip()

return date, time, author, message

else:

message = line

return message

parsedData= []

with open(textFile, encoding ="utf-8") as fp:

fp.readline() #skips first line which contains end-end encryption info

date, time, author, message, hour = None, None, None, None, None # initialise variables

while True:

line = fp.readline()

if not line: #if the end of the file has been reached

parsedData.append([date, time, author, message, hour])

break

line = line.strip() #removes leading and trailing whitespace

if isNewMessage(line):

if message:

message = str(message)

parsedData.append([date, time, author, message, hour])

date, time, author, message = splitData(line)

hour = time.split(':')[0]

else:

message += " "

message += splitData(line)

df = pd.DataFrame(parsedData, columns = ['Date', 'Time', 'Author', 'Message', 'Hour'])

df = df.drop(df.index[0])

authors = df['Author'].unique()

author1 = authors[0]

author2 = authors[1]

try:

uchr = unichr # Python 2

if sys.maxunicode == 0xffff:

# narrow build, define alternative unichr encoding to surrogate pairs

# as unichr(sys.maxunicode + 1) fails.

def uchr(codepoint):

return (unichr(codepoint) if codepoint <= sys.maxunicode\

else unichr(codepoint - 0x010000 >> 10 | 0xD800) + unichr(codepoint & 0x3FF | 0xDC00))

except NameError:

uchr = chr # Python 3

# Unicode 11.0 Emoji Component map (deemed safe to remove)

_removable_emoji_components = ((0x20E3, 0xFE0F), range(0x1F1E6, 0x1F1FF + 1), range(0x1F3FB, 0x1F3FF + 1), range(0x1F9B0, 0x1F9B3 + 1), range(0xE0020, 0xE007F + 1),)

emoji_components = re.compile(u'({})'.format(u'|'.join([re.escape(uchr(c)) for r in _removable_emoji_components for c in r])), flags=re.UNICODE)

def remove_emoji(text, remove_components=False):

cleaned = emoji.get_emoji_regexp().sub(u'', text)

if remove_components:

cleaned = emoji_components.sub(u'', cleaned)

return cleaned

author1_name = remove_emoji(authors[0])

author1_name = author1_name.strip()

author2_name = remove_emoji(authors[1])

author2_name = author2_name.strip()

#separate df for media only

media_messages_df = df[df['Message'] == '<Media omitted>']

#to drop the media files

df= df.drop(media_messages_df.index)

df = df.loc[(df['Author'] == author1)|(df['Author'] == author2)]

df['Date'] = pd.to_datetime(df['Date'])

df['Day_of_week'] = df['Date'].dt.day_name()

global df

global author1

global author2

global startDate

global endDate

global author1_wpm

global author2_wpm

global more_words

global author1_messages

global author2_messages

global more_messages

#restricting range of data

mask = (df['Date'] >= startDate) & (df['Date']<= endDate)

df = df.loc[mask]

author1_df = df.loc[(df['Author'] == author1)]

author2_df = df.loc[(df['Author'] == author2)]

author1_hour = author1_df['Hour'].value_counts()

author2_hour = author2_df['Hour'].value_counts()

def time_of_day_data():

hours_dictionary = {}

hours_dictionary['hourlist'] = ['Author 1', 'Author 2']

for i in range(0,24):

t_list = [0,0]

j = str(i)

if i<10:

j = '0' + j

if i == 0:

j = '00'

if j in author1_hour.index.tolist():

t_list[0] = author1_hour.loc[j].item()

if j in author2_hour.index.tolist():

t_list[1] = author2_hour.loc[j].item()

hours_dictionary[j] = t_list

for x in hours_dictionary:

if x =='hourlist':

counter = 0

elif int(hours_dictionary[x][0])> counter:

counter = int(hours_dictionary[x][0])

elif int(hours_dictionary[x][1])> counter:

counter = int(hours_dictionary[x][1])

return hours_dictionary, counter

def roundup(x):

return int(x) if x % 100 == 0 else int(x + 100 - x % 100)

### start of FIRST: time of day ###

def plot_time_of_day():

plt.style.use('fivethirtyeight')

plt.style.use('bmh')

plt.rcParams["font.family"] = "Gabriola"

plt.rcParams.update({'font.size': 16})

tod_data,maxcount = time_of_day_data()

time_of_day_df = pd.DataFrame(tod_data)

maxcount = roundup(maxcount) + 200

a = roundup(maxcount/4)

b = roundup(maxcount/2)

c = roundup(3* maxcount/4)

# No. of variable

categories=list(time_of_day_df)[1:]

N = len(categories)

# What will be the angle of each axis in the plot? (we divide the plot / number of variable)

angles = [n / float(N) * 2 * pi for n in range(N)]

angles += angles[:1]

# Initialise the spider plot

ax = plt.subplot(111, polar=True, label='time of day')

# If you want the first axis to be on top:

ax.set_theta_offset(pi / 2)

ax.set_theta_direction(-1)

# Draw one axe per variable + add labels labels yet

plt.xticks(angles[:-1], categories, fontsize=16)

# Draw ylabels

ax.set_rlabel_position(0)

plt.yticks([a,b,c], [str(a),str(b),str(c)], color="grey", size=12)

plt.ylim(0,maxcount)

# Ind1

values=time_of_day_df.loc[0].drop('hourlist').values.flatten().tolist()

values += values[:1]

ax.plot(angles, values, linewidth=1, linestyle='solid', label=author1_name, color=author1_colour)

ax.fill(angles, values, author1_colour, alpha=0.1)

# Ind2

values=time_of_day_df.loc[1].drop('hourlist').values.flatten().tolist()

values += values[:1]

ax.plot(angles, values, linewidth=1, linestyle='solid', label=author2_name, color=author2_colour)

ax.fill(angles, values, author2_colour, alpha=0.1)

# Add legend

plt.legend(loc='upper right', bbox_to_anchor=(0.1, 0.1))

plt.savefig(os.path.join("uploads", 'timeofday.png'), bbox_inches = 'tight')

plot_time_of_day()

### end of FIRST: time of day ###

author1_day = author1_df['Day_of_week'].value_counts()

author2_day = author2_df['Day_of_week'].value_counts()

days_in_order = [ 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']

def day_of_week_data():

day_dictionary = {}

day_dictionary['Day'] = ['Author 1', 'Author 2']

for dayname in days_in_order:

t_list = [0,0]

if dayname in author1_day.index.tolist():

t_list[0] = author1_day.loc[dayname].item()

if dayname in author2_day.index.tolist():

t_list[1] = author2_day.loc[dayname].item()

day_dictionary[dayname] = t_list

for x in day_dictionary:

if x =='Day':

counter = 0

else:

temp = max(int(day_dictionary[x][0]),int(day_dictionary[x][1]))

if temp > counter:

counter = temp

return day_dictionary, counter

### start of SECOND: Day of week ###

def plot_day_of_week():

plt.style.use('fivethirtyeight')

plt.style.use('bmh')

plt.rcParams["font.family"] = "Gabriola"

plt.rcParams.update({'font.size': 16})

dow_data,maxcount = day_of_week_data()

day_of_week_df = pd.DataFrame(dow_data)

maxcount = roundup(maxcount) + 200

a = roundup(maxcount/4)

b = roundup(maxcount/2)

c = roundup(3* maxcount/4)

# number of variable

categories=list(day_of_week_df)[1:]

N = len(categories)

# What will be the angle of each axis in the plot? (we divide the plot / number of variable)

angles = [n / float(N) * 2 * pi for n in range(N)]

angles += angles[:1]

# Initialise the spider plot

ax = plt.subplot(111, polar=True, label='day of week')

# If you want the first axis to be on top:

ax.set_theta_offset(pi / 2)

ax.set_theta_direction(-1)

# Draw one axe per variable + add labels labels yet

plt.xticks(angles[:-1], categories, fontsize=16)

for label,i in zip(ax.get_xticklabels(),range(0,len(angles))):

angle_rad=angles[i]

if angle_rad == 0:

ha = 'center'

elif angle_rad <= pi/2:

ha= 'left'

elif pi/2 < angle_rad <= pi:

ha= 'left'

elif pi < angle_rad <= (3*pi/2):

ha= 'right'

else:

ha= 'right'

label.set_horizontalalignment(ha)

# Draw ylabels

ax.set_rlabel_position(0)

plt.yticks([a,b,c], [str(a),str(b),str(c)], color="grey", size=12)

plt.ylim(0,maxcount)

# Ind1

values=day_of_week_df.loc[0].drop('Day').values.flatten().tolist()

values += values[:1]

ax.plot(angles, values, linewidth=1, linestyle='solid', label=author1_name, color=author1_colour)

ax.fill(angles, values, author1_colour, alpha=0.1)

# Ind2

values=day_of_week_df.loc[1].drop('Day').values.flatten().tolist()

values += values[:1]

ax.plot(angles, values, linewidth=1, linestyle='solid', label=author2_name, color=author2_colour)

ax.fill(angles, values, author2_colour, alpha=0.1)

# Add legend

plt.legend(loc='upper right', bbox_to_anchor=(0.1, 0.1))

plt.savefig(os.path.join("uploads", 'dayofweek.png'), bbox_inches = 'tight')

plot_day_of_week()

### end of SECOND: Day of week ###

def timeline_data():

timeline_dictionary = {}

timeline_dictionary['date'] = ['Author1', 'Author2']

for i in range(len(df)):

t_list = [0,0]

day,author = df.iloc[i,0], df.iloc[i,2]

if day not in timeline_dictionary:

timeline_dictionary[day] = t_list

t_list = timeline_dictionary[day]

if author == author1:

t_list[0] += 1

if author == author2:

t_list[1] += 1

timeline_dictionary[day] = t_list

return timeline_dictionary

timeline_df = pd.DataFrame(timeline_data())

timeline_df = timeline_df.T

new_header = timeline_df.iloc[0]

timeline_df = timeline_df[1:]

timeline_df.columns = new_header

### start of THIRD: timeline ###

def plot_timeline():

plt.style.use('fivethirtyeight')

plt.rcParams["font.family"] = "Gabriola"

plt.rcParams.update({'font.size': 24})

plt.figure(figsize = (20,8))

plt.xlabel('Timeline', fontsize=30)

ax1 = timeline_df.Author1.plot(color=author1_colour)

ax2 = timeline_df.Author2.plot(color=author2_colour)

ax1.xaxis.set_label_position('top')

ax1.legend([author1_name,author2_name],loc='upper right')

plt.savefig(os.path.join("uploads", 'timeline.png'), bbox_inches = 'tight')

plot_timeline()

### end of THIRD: timeline ###

def top_words(df):

top_N = 40

stopwords = nltk.corpus.stopwords.words('english')

# RegEx for stopwords

RE_stopwords = r'\b(?:{})\b'.format('|'.join(stopwords))

#RE_stopwords.extend(['from', 'subject', 're', 'edu', 'use'])

# replace '|'-->' ' and drop all stopwords

words = (df.Message\

.str.lower()\

.replace([RE_stopwords], [''], regex=True)\

.str.cat(sep=' ')\

.split())

words = [word for word in words if len(word) > 3]

# generate DF out of Counter

rslt = pd.DataFrame(Counter(words).most_common(top_N),

columns=['Word', 'Frequency']).set_index('Word')

return rslt

def hex_to_rgb(hex):

hex = hex.lstrip('#')

hlen = len(hex)

return tuple(int(hex[i:i + hlen // 3], 16) for i in range(0, hlen, hlen // 3))

def rgb_to_hsl(r, g, b):

r = float(r)

g = float(g)

b = float(b)

high = max(r, g, b)

low = min(r, g, b)

h, s, l = ((high + low) / 2,)*3

if high == low:

h = 0.0

s = 0.0

else:

d = high - low

s = d / (2 - high - low) if l > 0.5 else d / (high + low)

h = {

r: (g - b) / d + (6 if g < b else 0),

g: (b - r) / d + 2,

b: (r - g) / d + 4,

}[high]

h /= 6

return h, s, l

a1_rgb = hex_to_rgb(author1_colour)

a2_rgb = hex_to_rgb(author2_colour)

a1_hlsva = rgb_to_hsl(a1_rgb[0]/255,a1_rgb[1]/255,a1_rgb[2]/255)

a2_hlsva = rgb_to_hsl(a2_rgb[0]/255,a2_rgb[1]/255,a2_rgb[2]/255)

a1_hlsva0 = round(a1_hlsva[0]*355)

a1_hlsva1 = round(a1_hlsva[1]*100)

a1_hlsva2 = round(a1_hlsva[2]*100)

a2_hlsva0 = round(a2_hlsva[0]*355)

a2_hlsva1 = round(a2_hlsva[1]*100)

a2_hlsva2 = round(a2_hlsva[2]*100)

############################

df_1 = top_words(author1_df)

df_1.columns

d = dict(zip(df_1.index, df_1.Frequency))

plt.style.use('fivethirtyeight')

plt.rcParams["font.family"] = "Gabriola"

plt.rcParams.update({'font.size': 16})

fileloc = os.path.join("static", shape + '.jpg')

mask = np.array(Image.open(fileloc))

wordcloud = WordCloud(background_color = '#F0F0F0', mask=mask, width = mask.shape[1], height = mask.shape[0])

wordcloud.generate_from_frequencies(frequencies=d)

plt.figure()

def a1_color_func(word, font_size, position, orientation, random_state=None,**kwargs):

return "hsl({0}, {1}%%, %d%%)".format(str(a1_hlsva0),str(a1_hlsva1)) % random.randint(60, 90)

plt.imshow(wordcloud.recolor(color_func = a1_color_func), interpolation="bilinear")

plt.axis("off")

wordcloud.to_file(os.path.join("uploads", 'author1cloud.png'))

df_2 = top_words(author2_df)

df_2.columns

d = dict(zip(df_2.index, df_2.Frequency))

plt.style.use('fivethirtyeight')

plt.rcParams["font.family"] = "Gabriola"

plt.rcParams.update({'font.size': 16})

wordcloud = WordCloud(background_color = '#F0F0F0',mask=mask,width = mask.shape[1],height = mask.shape[0])

wordcloud.generate_from_frequencies(frequencies=d)

plt.figure()

def a2_color_func(word, font_size, position, orientation, random_state=None,**kwargs):

return "hsl({0}, {1}%%, %d%%)".format(str(a2_hlsva0),str(a2_hlsva1)) % random.randint(60, 90)

plt.imshow(wordcloud.recolor(color_func = a2_color_func), interpolation="bilinear")

plt.axis("off")

wordcloud.to_file(os.path.join("uploads", 'author2cloud.png'))

n_instances = 100

subj_docs = [(sent, 'subj') for sent in subjectivity.sents(categories='subj')[:n_instances]]

obj_docs = [(sent, 'obj') for sent in subjectivity.sents(categories='obj')[:n_instances]]

train_subj_docs = subj_docs[:80]

test_subj_docs = subj_docs[80:100]

train_obj_docs = obj_docs[:80]

test_obj_docs = obj_docs[80:100]

training_docs = train_subj_docs+train_obj_docs

testing_docs = test_subj_docs+test_obj_docs

sentim_analyzer = SentimentAnalyzer()

all_words_neg = sentim_analyzer.all_words([mark_negation(doc) for doc in training_docs])

unigram_feats = sentim_analyzer.unigram_word_feats(all_words_neg, min_freq=4)

len(unigram_feats)

sentim_analyzer.add_feat_extractor(extract_unigram_feats, unigrams=unigram_feats)

training_set = sentim_analyzer.apply_features(training_docs)

test_set = sentim_analyzer.apply_features(testing_docs)

trainer = NaiveBayesClassifier.train

classifier = sentim_analyzer.train(trainer, training_set)

'''

for key,value in sorted(sentim_analyzer.evaluate(test_set).items()):

print('{0}: {1}'.format(key, value))

'''

df['Message'].unique()[10:20]

def sentiment(message):

sid = SentimentIntensityAnalyzer()

ss = sid.polarity_scores(message)

return ss['compound']

df["Sentiment"] = df.apply(lambda row : sentiment(row['Message']),axis = 1)

def sentiment_data():

sentiment_dictionary = {}

sentiment_dictionary['date'] = ['Author1', 'Author2']

for i in range(len(df)):

t_list = [[0,0.0],[0,0.0]]

month,author,sentiment = str(df.iloc[i,0]), df.iloc[i,2], df.iloc[i,6]

if sentiment != 0.0:

month = month.split('-')[0] + '-' + month.split('-')[1]

if month not in sentiment_dictionary:

sentiment_dictionary[month] = t_list

t_list = sentiment_dictionary[month]

if author == author1:

t_list[0][0] += 1

t_list[0][1] += sentiment

if author == author2:

t_list[1][0] += 1

t_list[1][1] +=sentiment

sentiment_dictionary[month] = t_list

for x in sentiment_dictionary:

if x != 'date':

t_list = sentiment_dictionary[x]

if t_list[0][0] != 0:

t_list[0] = float(t_list[0][1])/float(t_list[0][0])

else:

t_list[0] = 0

if t_list[1][0] != 0:

t_list[1] = float(t_list[1][1])/float(t_list[1][0])

else:

t_list[1] = 0

sentiment_dictionary[x] = t_list

return sentiment_dictionary

sentiment_df = pd.DataFrame(sentiment_data())

sentiment_df = sentiment_df.T

new_header = sentiment_df.iloc[0]

sentiment_df = sentiment_df[1:]

sentiment_df.columns = new_header

def plot_sentiment():

plt.style.use('fivethirtyeight')

plt.rcParams["font.family"] = "Gabriola"

plt.rcParams.update({'font.size': 24})

plt.figure(figsize = (20,8))

plt.xlabel('Sentiment Analysis',fontsize =30)

ax1 = sentiment_df.Author1.plot(color=author1_colour)

ax2 = sentiment_df.Author2.plot(color=author2_colour)

ax1.xaxis.set_label_position('top')

h1, l1 = ax1.get_legend_handles_labels()

ax1.legend([author1_name,author2_name],loc='upper right')

plt.savefig(os.path.join("uploads", 'sentiment.png'), bbox_inches = 'tight')

plot_sentiment()

#number of words

def no_of_words(message):

return len(message.split())

df["WordCount"] = df.apply(lambda row : no_of_words(row['Message']),axis = 1)

author1_df = df.loc[(df['Author'] == author1)]

author2_df = df.loc[(df['Author'] == author2)]

author1_wpm = author1_name + "'s average word per message is {:0.2f}".format(author1_df["WordCount"].mean())

author2_wpm = author2_name + "'s average word per message is {:0.2f}".format(author2_df["WordCount"].mean())

def who_sent_more_words():

if author1_df["WordCount"].sum()> author2_df["WordCount"].sum():

num = author1_df["WordCount"].sum()/author2_df["WordCount"].sum()

num = num*100 -100

return (author1_name + " sent {:0.0f}% more words than ".format(num)+ author2_name)

elif author2_df["WordCount"].sum()> author1_df["WordCount"].sum():

num = author2_df["WordCount"].sum()/author1_df["WordCount"].sum()

num = num*100 -100

return (author2_name + " sent {:0.0f}% more words than ".format(num)+ author1_name)

else:

return ("You both sent the same number of words somehow!")

more_words = who_sent_more_words()

days = "Number of days of texting: " + str(len(df["Date"].unique()))

author1_messages = author1_name + " sent " + str(len(author1_df.index)) + " messages"

author2_messages = author2_name + " sent " + str(len(author2_df.index)) + " messages"

def who_sent_more():

if len(author1_df.index)> len(author2_df.index):

num = len(author1_df.index)/len(author2_df.index)

return (author1_name + " sent {:0.2f} times more messages than ".format(num)+ author2_name)

elif len(author2_df.index)> len(author1_df.index):

num = len(author2_df.index)/len(author1_df.index)

return (author2_name + " sent {:0.2f} times more messages than ".format(num)+ author1_name)

else:

return ("You both sent the same number of messages somehow!")

global fileWhatsapp

global filename

if request.method == "POST":

fileWhatsapp = request.files["fileWhatsapp"] #file is now the text file

if fileWhatsapp:

filename = secure_filename(fileWhatsapp.filename)

if allowed_whatsapp(filename):

fileWhatsapp.save(os.path.join("uploads", filename))

return redirect('/customize')

else:

flash("Please only select a .txt file of your Whatsapp chat")

return redirect('/start/whatsapp/')

else:

flash("No file selected for uploading")

return redirect('/start/whatsapp/')

global fileTelegram

global filename

if request.method == "POST":

fileTelegram = request.files["fileTelegram"] #file is now the text file

if fileTelegram:

filename = secure_filename(fileTelegram.filename)

if allowed_telegram(filename):

fileTelegram.save(os.path.join("uploads", filename))

return redirect('/customize')

else:

flash("Please only select a .json file of your Telegram chat")

return redirect('/start/telegram/')

else:

flash("No file selected for uploading")

return redirect('/start/telegram/')

global author1_name

global author2_name

global startDate

global endDate

global author1_colour

global author2_colour

global shape

if fileTelegram:

telegramData("uploads/" + filename)

else:

whatsappData("uploads/" + filename)

if request.method == "POST":

if request.form["contactOrNot"] == "no":

if request.form["authorOne"] and request.form["authorTwo"]:

author1_name = request.form["authorOne"]

author2_name = request.form["authorTwo"]

else:

flash("Please fill up the name fields if you want to customize them")

return redirect('/customize')

if request.form["dateRange"] == "no":

if request.form["startDate"] and request.form["endDate"]:

if request.form["startDate"] < request.form["endDate"]:

startDate = request.form["startDate"]

endDate = request.form["endDate"]

else:

flash("Please ensure that the start date is earlier than the end date")

return redirect('/customize')

else:

flash("Please fill up the date range if you want to customize them")

return redirect('/customize')

author1_colour = request.form["colour1"]

author2_colour = request.form["colour2"]

if author1_colour == author2_colour:

flash("Please choose different colours for the two authors")

return redirect('/customize')

try:

shape = request.form["shape"]

except KeyError:

flash("Please choose a shape for your wordcloud")

return redirect('/customize')

return redirect('/output')

global fileTelegram

global fileWhatsapp

plot()

'''

pdf = pdfkit.from_string(process("uploads/" + filename, author1_name, author2_name, startDate, endDate, author1_colour, author2_colour), False) #for testing

#pdf = pdfkit.from_file("templates/file.html", False) #generate pdf with a black rectangle

#pdf = pdfkit.from_string(render_template('file.html', onehtml = base64.b64encode(open("uploads/timeline.png", "rb").read())), False) #cannot find file (because it's rendered)

'''

one = base64.b64encode(open("uploads/timeofday.png", "rb").read()).decode('utf-8')

two = base64.b64encode(open("uploads/dayofweek.png", "rb").read()).decode('utf-8')

three = base64.b64encode(open("uploads/timeline.png", "rb").read()).decode('utf-8')

four = base64.b64encode(open("uploads/author1cloud.png", "rb").read()).decode('utf-8')

five = base64.b64encode(open("uploads/author2cloud.png", "rb").read()).decode('utf-8')

six = base64.b64encode(open("uploads/sentiment.png", "rb").read()).decode('utf-8')

rendered_template = render_template('file.html', author1=author1_name, author2=author2_name,\

colour1=author1_colour, colour2=author2_colour, \

wpm1=author1_wpm, wpm2=author2_wpm, morewpm=more_words,\

messages1=author1_messages, messages2=author2_messages, moremessages=more_messages,\

onehtml=one, twohtml=two, threehtml=three, fourhtml=four, fivehtml=five, sixhtml=six)

pdf = pdfkit.from_string(rendered_template, False)

response = make_response(pdf)

response.headers['Content-Type'] = 'application/pdf'

response.headers['Content-Disposition'] = 'inline; filename=inspecText.pdf'

os.remove(os.path.join("uploads", filename))

os.remove(os.path.join("uploads", 'timeline.png'))

os.remove(os.path.join("uploads", 'timeofday.png'))

os.remove(os.path.join("uploads", 'dayofweek.png'))

os.remove(os.path.join("uploads", 'author1cloud.png'))

os.remove(os.path.join("uploads", 'author2cloud.png'))

os.remove(os.path.join("uploads", 'sentiment.png'))

fileTelegram = ''

fileWhatsapp= ''