def post_list(request):
posts = Post.objects.filter(
published_date__lte=timezone.now()).order_by('published_date')
for post in posts:
posting = post.text
translation = language_translator.translate(
text=post.text, model_id='en-es').get_result()
obj = (json.dumps(translation, indent=2, ensure_ascii=False))
print(obj)
obj2 = json.loads(obj)
post.obj2 = obj2['translations'][0]['translation']
post.w_count = obj2['word_count']
post.c_count = obj2['character_count']
tone_input = ToneInput(post.text)
tone = service.tone(tone_input=tone_input,
content_type="application/json")
tone2 = str(tone)
print(tone2)
post.tone3 = ""
#print(post.tone3)
temp = json.loads(tone2)
if (len(temp['result']['document_tone']['tones']) > 0):
temp2 = temp['result']['document_tone']['tones']
for x in temp2:
post.tone3 += 'Tone name: ' + x[
'tone_name'] + '\t' + '|\tScore: ' + str(x['score']) + '\r'
else:
post.tone3 = 'Tone name: n/a\t|\tScore: n/a'
return render(request, 'blog/post_list.html', {'posts': posts})
def post_list(request):
posts = Post.objects.filter(published_date__lte=timezone.now()).order_by('published_date')
for post in posts:
posting = post.text
translation = language_translator.translate(
text= post.text, model_id='en-es').get_result()
obj = (json.dumps(translation, indent=2, ensure_ascii=False))
# print(obj)
obj2 = json.loads(obj)
post.obj2 = obj2['translations'][0]['translation']
post.w_count = obj2['word_count']
post.c_count = obj2['character_count']
tone_input = ToneInput(post.text)
try:
tone = tone_analyzer.tone(tone_input=tone_input, content_type="application/json").get_result()
jsonText = (json.dumps(tone, indent=2, ensure_ascii=False))
jsonParse = json.loads(jsonText)
post.Score1 = jsonParse['document_tone']['tones'][0]['score']
post.ToneName1 = jsonParse['document_tone']['tones'][0]['tone_name']
except:
pass
post.Score1 = "Missing data in response"
post.ToneName1 ="no response from API"
print("Encountered an issue please hold tight! We are working on it ")
return render(request, 'blog/post_list.html', {'posts': posts})
def post_list(request):
posts = Post.objects.filter(
published_date__lte=timezone.now()).order_by('published_date')
for post in posts:
posting = post.text
translation = language_translator.translate(
text=post.text, model_id='en-es').get_result()
obj = (json.dumps(translation, indent=2, ensure_ascii=False))
print(obj)
obj2 = json.loads(obj)
post.obj2 = obj2['translations'][0]['translation']
post.w_count = obj2['word_count']
post.c_count = obj2['character_count']
tone_input = ToneInput(post.text)
tone = tone_analyzer.tone(tone_input=tone_input,
content_type="application/json")
tone2 = str(tone)
json_data = json.loads(tone2)
post.json_score1 = json_data['result']['document_tone']['tones'][0][
'score']
post.json_score2 = json_data['result']['document_tone']['tones'][1][
'score']
post.json_name1 = json_data['result']['document_tone']['tones'][0][
'tone_name']
post.json_name2 = json_data['result']['document_tone']['tones'][1][
'tone_name']
post.tone3 = (tone2[1:500])
print(post.tone3)
return render(request, 'blog/post_list.html', {'posts': posts})
def get_essay_emotion(path):
"""
Identifies the user's mood based on a piece of writing authored by them
Args:
path: path to the file with text written by the user
Returns:
The user's emotion as identified
"""
file = open(path, "r")
text = file.read()
print()
print('Identifying mood...')
service = ToneAnalyzerV3(username=const.watson_username,
password=const.watson_password,
version='2017-09-21')
service.set_detailed_response(True)
tone_input = ToneInput(text)
tone = service.tone(tone_input=tone_input, content_type="application/json")
emo_score = []
for emotion in tone.result["document_tone"]["tones"]:
print(emotion["score"])
print(emotion["tone_id"])
emo_score.append(emotion["score"])
print(tone.result["document_tone"]["tones"][emo_score.index(
max(emo_score))]["tone_id"])
return (tone.result["document_tone"]["tones"][emo_score.index(
max(emo_score))]["tone_id"])
def post_list(request):
posts = Post.objects.filter(published_date__lte=timezone.now()).order_by('published_date')
for post in posts:
posting = post.text
translation = language_translator.translate(
text= post.text, model_id='en-es').get_result()
obj = (json.dumps(translation, indent=2, ensure_ascii=False))
print(obj)
obj2 = json.loads(obj)
post.obj2 = obj2['translations'][0]['translation']
post.w_count = obj2['word_count']
post.c_count = obj2['character_count']
tone_input = ToneInput(post.text)
tone = service.tone(tone_input=tone_input, content_type="application/json")
tone2 = str(tone)
post.tone3 = (tone2[1:500])
print(post.tone3)
toneObject = json.dumps(service.tone(tone_input=posting, content_type="text/plain").get_result(), indent=2)
post.obj3 = json.loads(toneObject)
print(toneObject)
try:
post.firstTone = post.obj3['document_tone']['tones'][0]['tone_name']
post.firstScore = post.obj3['document_tone']['tones'][0]['score']
post.secondTone = post.obj3['document_tone']['tones'][1]['tone_name']
post.secondScore = post.obj3['document_tone']['tones'][1]['score']
except:
pass
return render(request, 'blog/post_list.html', {'posts': posts})
def ProcessImage(image_path):
"""
Identifies the emotion of an image, using the Watson Visual Recognition API
Args:
image_path: the path to the image file
Returns:
The emotion of the image
"""
service = VisualRecognitionV3(
'2018-03-19',
url='https://gateway.watsonplatform.net/visual-recognition/api',
iam_apikey='dnckUYEa5ip8jnJvWFdeFA7aMsRCXx9agFgEiGO3NBpu')
path = abspath(image_path)
text = " "
try:
with open(path, 'rb') as images_file:
results = service.classify(images_file=images_file,
threshold='0.1',
classifier_ids=['default'
]).get_result()
#print()
for value in results["images"][0]["classifiers"][0]["classes"]:
text = text + " " + value["class"]
print(text)
text += "."
puncs1 = [
'@', '#', '$', '%', '^', '&', '*', '(', ')', '-', '_', '+',
'=', '{', '}', '[', ']', '|', '\\', '"', "'", ';', ':', '<',
'>', '/'
]
for punc in puncs1:
text = text.replace(punc, '')
except WatsonApiException as ex:
print(ex)
service = ToneAnalyzerV3(username='******',
password='******',
version='2017-09-21')
service.set_detailed_response(True)
tone_input = ToneInput(text)
tone = service.tone(tone_input=tone_input, content_type="application/json")
emo_score = []
for emotion in tone.result["document_tone"]["tones"]:
print(emotion["score"])
print(emotion["tone_name"])
emo_score.append(emotion["score"])
if not emo_score:
return 'Neutral'
else:
return (tone.result["document_tone"]["tones"][emo_score.index(
max(emo_score))]["tone_name"])
def analyze_tone(tone_analyzer: T, text: str) -> dict:
"""Analyzes text input with tone analyzer object"""
try:
tone_input = ToneInput(text)
return tone_analyzer.tone(
tone_input,
'application/json'
).get_result()
except WatsonApiException:
traceback.print_exc(limit=1)
def analyze(message):
service = ToneAnalyzerV3(
## url is optional, and defaults to the URL below. Use the correct URL for your region.
# url='https://gateway.watsonplatform.net/tone-analyzer/api',
username='******',
password='******',
version='2017-09-21')
tone_input = ToneInput(message)
result = service.tone(tone_input=tone_input,
content_type="application/json").get_result()
return result
def post_list(request):
posts = Post.objects.filter(
published_date__lte=timezone.now()).order_by('published_date')
for post in posts:
posting = post.text
translation = language_translator.translate(
text=post.text, model_id='en-es').get_result()
obj = (json.dumps(translation, indent=2, ensure_ascii=False))
# print(obj)
obj2 = json.loads(obj)
post.obj2 = obj2['translations'][0]['translation']
post.w_count = obj2['word_count']
post.c_count = obj2['character_count']
tone_input = ToneInput(post.text)
# tone = tone_analyzer.tone(tone_input=tone_input, content_type="application/json")
# print(tone)
# print('//////////////////////////////////////////////////////')
# tone2 = str(tone)
# post.tone3 = (tone2[1:500])
# print('*********************************************************************')
# print(post.tone3)
# print('*********************************************************************')
# JsonText = json.dumps(post.tone3)
# d2=json.loads(JsonText)
# print(d2['result'][0])
# jsonText = json.dumps(tone, indent=2, ensure_ascii=False)
# tone_score = json.loads(jsonText)['results']
# print(tone_score)
try:
tone = tone_analyzer.tone(
tone_input=tone_input,
content_type="application/json").get_result()
jsonText = (json.dumps(tone, indent=2, ensure_ascii=False))
jsonParse = json.loads(jsonText)
post.Score1 = jsonParse['document_tone']['tones'][0]['score']
post.ToneName1 = jsonParse['document_tone']['tones'][0][
'tone_name']
except:
pass
post.Score1 = "no-data value for key Score from API response"
post.ToneName1 = "no-data value for key ToneName from API response"
print(
"****************************Something went wrong while rendering the Document tone json"
)
return render(request, 'blog/post_list.html', {'posts': posts})
def post_list(request):
posts = Post.objects.filter(
published_date__lte=timezone.now()).order_by('published_date')
for post in posts:
posting = post.text
translation_ch = language_translator.translate(
text=post.text, model_id='en-zh-TW').get_result()
translation_fr = language_translator.translate(
text=post.text, model_id='en-fr').get_result()
obj_ch = (json.dumps(translation_ch, indent=2, ensure_ascii=False))
print(obj_ch)
obj2_ch = json.loads(obj_ch)
post.obj2_ch = obj2_ch['translations'][0]['translation']
post.w_count_ch = obj2_ch['word_count']
post.c_count_ch = obj2_ch['character_count']
obj_fr = (json.dumps(translation_fr, indent=2, ensure_ascii=False))
print(obj_fr)
obj2_fr = json.loads(obj_fr)
post.obj2_fr = obj2_fr['translations'][0]['translation']
post.w_count_fr = obj2_fr['word_count']
post.c_count_fr = obj2_fr['character_count']
# tone_input = ToneInput(post.text)
# post.tone = service.tone(tone_input=tone_input, content_type="application/json")
# tone2 = str(tone)
# post.tone3 = (tone2[1:500])
# print(post.tone3)
tone_input = ToneInput(post.text)
tone = service.tone(tone_input=tone_input,
content_type="application/json")
tone_type = []
tone_score = []
document_tones = tone.result["document_tone"]["tones"]
i = 0
for i in range(len(document_tones)):
tone_type.append(document_tones[i]["tone_name"])
tone_score.append(document_tones[i]["score"])
return render(request, 'blog/post_list.html', {
'posts': posts,
'tone_type': tone_type,
'tone_score': tone_score
})
def post_list(request):
posts = Post.objects.filter(published_date__lte=timezone.now()).order_by('published_date')
language_translator = LanguageTranslatorV3(
version='2018-05-31',
iam_apikey='HlK2hXGChPDwRQ9J32GYzPduHQqhNTDBsvsYg4Yvtop0')
service = ToneAnalyzerV3(
version='2017-09-26',
iam_apikey='DRPM3RA0gH0UcfLkZUBwpAo91JwbgEYDgiXtjV3mZeFS')
for post in posts:
posting = post.text
translation = language_translator.translate(
text= post.text, model_id='en-es').get_result()
obj = (json.dumps(translation, indent=2, ensure_ascii=False))
# print(obj)
obj2 = json.loads(obj)
post.obj2 = obj2['translations'][0]['translation']
post.w_count = obj2['word_count']
post.c_count = obj2['character_count']
tone_input = ToneInput(post.text)
tone = service.tone(tone_input=tone_input, content_type="application/json")
tone2 = str(tone)
json_data = json.loads(tone2)
# print(json_data)
try:
post.json_score1 = json_data['result']['document_tone']['tones'][0]['score']
post.json_name1 = json_data['result']['document_tone']['tones'][0]['tone_name']
post.json_score2 = json_data['result']['document_tone']['tones'][1]['score']
post.json_name2 = json_data['result']['document_tone']['tones'][1]['tone_name']
except:
pass
post.tone3 = (tone2[1:500])
# print(post.tone3)
return render(request, 'blog/post_list.html', {'posts': posts})
def getEmotion(text):
print(text)
service = ToneAnalyzerV3(username='******',
password='******',
version='2017-09-21')
service.set_detailed_response(True)
tone_input = ToneInput(text)
tone = service.tone(tone_input=tone_input, content_type="application/json")
emo_score = []
for emotion in tone.result["document_tone"]["tones"]:
print(emotion["score"])
print(emotion["tone_name"])
emo_score.append(emotion["score"])
if not emo_score:
print('Neutral')
return 'Neutral'
else:
print(tone.result["document_tone"]["tones"][emo_score.index(
max(emo_score))]["tone_name"])
return (tone.result["document_tone"]["tones"][emo_score.index(
max(emo_score))]["tone_name"])
def analyze_sentiment(self, text):
if text == '':
return {}
tone_input = ToneInput(text)
return self.tone_analyzer.tone(tone_input, 'application/json')
import pandas as pd
import csv
# If service instance provides API key authentication
service = ToneAnalyzerV3(
# ## url is optional, and defaults to the URL below. Use the correct URL for your region.
url='https://gateway.watsonplatform.net/tone-analyzer/api',
version='2017-09-21',
iam_apikey='H7sXUX39LzgVDqO4IcZaoX3dbsiZYn8GVo2wnZvXd6oP')
filename = raw_input()
f = []
filetext = filename + ".txt"
t = open(filetext, 'r')
text = t.read()
tone_input = ToneInput(text)
tone = service.tone(tone_input=tone_input, content_type="application/json")
#print(json.dumps(tone.get_result(), indent=2))
data = tone.get_result()
score1 = 0
score2 = 0
word_valence = []
for i in range(len(data["sentences_tone"])):
txt = data["sentences_tone"][i]["text"]
txt = txt.replace("'", "")
txt = txt.replace(",", "")
corresponding_valence = 0
max_probable_tone_id = ''
max_probablity = -1
def home():
user_id = session.get('id')
if 'logged_in' not in session:
session['logged_in']=False
return render_template('index1a.html',uname="")
elif session['logged_in'] is False:
return render_template('index1a.html',uname="")
else:
nme = session['this']
print(nme)
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
# Access to user's access key and access secret
auth.set_access_token(access_key, access_secret)
# Calling api
api = tweepy.API(auth)
# 200 tweets to be extracted
number_of_tweets=3
tweets = api.user_timeline(screen_name=nme)
results = api.get_user(nme)
url = "https://avatars.io/twitter/"+nme
# Empty Array
tmp=[]
# create array of tweet information: username,
# tweet id, date/time, text
tweets_for_csv = [tweet.text for tweet in tweets] # CSV file created
for j in tweets_for_csv:
# Appending tweets to the empty array tmp
tmp.append(j)
tlen=len(tmp)
results = api.get_user(nme)
fname=results.name
prlink = "https://twitter.com/intent/user?user_id=" + str(results.id)
moodans=[]
for item in tmp:
tone_input = ToneInput(item)
tone = service.tone(tone_input=tone_input, content_type="application/json", sentences=False).get_result()
#print(json.dumps(tone, indent=2))
parsed = json.loads(json.dumps(tone, indent=2))
i=0;
ak="Neutral"
for tones in parsed['document_tone']['tones']:
ak=tones['tone_name']
i=i+1
if(i==1):
break
moodans.append(ak)
return render_template('index1a.html',uname=nme,tmp=tmp,dictcolor=dictcolor,moodans=moodans,dict=dict,url=url,tlen=tlen,prlink=prlink,fname=fname)
'../resources/tone-example.json')) as tone_json:
tone = tone_analyzer.tone(tone_input=json.load(tone_json),
content_type='application/json')
print(json.dumps(tone, indent=2))
print("\ntone() example 5:\n")
with open(join(dirname(__file__),
'../resources/tone-example-html.json')) as tone_html:
tone = tone_analyzer.tone(json.load(tone_html)['text'],
content_type='text/html')
print(json.dumps(tone, indent=2))
print("\ntone() example 6 with GDPR support:\n")
tone_analyzer.set_detailed_response(True)
with open(join(dirname(__file__),
'../resources/tone-example-html.json')) as tone_html:
tone = tone_analyzer.tone(json.load(tone_html)['text'],
content_type='text/html',
headers={'Custom-Header': 'custom_value'})
print(tone)
print(tone.get_headers())
print(tone.get_result())
tone_analyzer.set_detailed_response(False)
print("\ntone() example 7:\n")
tone_input = ToneInput('I am very happy. It is a good day.')
tone = tone_analyzer.tone(tone_input=tone_input,
content_type="application/json")
print(json.dumps(tone, indent=2))
# with open(join(dirname(__file__),
# '../resources/tone-example-html.json')) as tone_html:
# tone = service.tone(
# json.load(tone_html)['text'], content_type='text/html').get_result()
# print(json.dumps(tone, indent=2))
# print("\ntone() example 6 with GDPR support:\n")
# service.set_detailed_response(True)
# with open(join(dirname(__file__),
# '../resources/tone-example-html.json')) as tone_html:
# tone = service.tone(
# json.load(tone_html)['text'],
# content_type='text/html',
# headers={
# 'Custom-Header': 'custom_value'
# })
# print(tone)
# print(tone.get_headers())
# print(tone.get_result())
# print(tone.get_status_code())
# service.set_detailed_response(False)
# print("\ntone() example 7:\n")
test_tone = "Hi Team, The times are difficult! Our sales have been disappointing for the past three quarters for our data analytics product suite. We have a competitive data analytics product suite in the industry. However, we are not doing a good job at selling it, and this is really frustrating.We are missing critical sales opportunities. We cannot blame the economy for our lack of execution. Our clients need analytical tools to change their current business outcomes. In fact, it is in times such as this, our clients want to get the insights they need to turn their businesses around. It is disheartening to see that we are failing at closing deals, in such a hungry market. Let's buckle up and execute.Jennifer BakerSales Leader, North-East region"
tone_input = ToneInput(test_tone)
result = service.tone(tone_input=tone_input,
content_type="application/json").get_result()
# print(type(json.dumps(tone, indent=2)))
pprint(result)
