def get(self, request, *args, **kwargs):
user_id = request.GET.get('user_id', None)
# tweet_list, df = twitter_user(user_id)
return Response(
data={
"cold": cold_def(twitter_user(user_id)),
"normal": normal_def(twitter_user(user_id)),
"warm": warm_def(twitter_user(user_id))
},
status=status.HTTP_201_CREATED,
# headers=headers,
)
def tweet_sentiment(name):
client = language_v1.LanguageServiceClient()
tweet_list, df = twitter_user(name)
score_list = ['\0' for i in range(len(tweet_list))]
for i in range(len(tweet_list)):
sentence_str = str(tweet_list[i])
document = language_v1.Document(
content=sentence_str, type_=language_v1.Document.Type.PLAIN_TEXT)
sentiment = client.analyze_sentiment(request={
'document': document
}).document_sentiment
score_list[i] = format(
(sentiment.score + 1) * 25 + sentiment_predict(sentence_str) * 50,
".1f")
# print("Text: {}".format(sentence_str.strip("['']")))
# print("Sentiment: (score) {} (magnitude) {}".format(sentiment.score, sentiment.magnitude))
# return sentiment.score, sentence_str.strip("['']")
# return score_list, sentiment.magnitude
return score_list
def model_sentiment(name):
new_list, df1 = twitter_user(name)
model_score_list = ['\0' for i in range(len(new_list))]
for i in range(len(new_list)):
sentence_str = str(new_list[i])
model_score_list[i] = sentiment_predict(sentence_str)
return model_score_list
def get(self, request, *args, **kwargs):
user_id = request.GET.get('user_id', None)
tweet_list, df = twitter_user(user_id)
score = tweet_sentiment(user_id)
ss = []
for i in range(len(df)):
st = (df['Tweets'][i], df['Dates'][i])
ss.append(st)
for i in range(len(df)):
Sentence.objects.get_or_create(user_id=user_id,
sentence=ss[i][0],
date=ss[i][1],
title=score[i],
date_m=(ss[i][1]).strftime('%Y-%m'))
queryset = self.get_queryset().filter(
user_id=user_id) # 필터 추가, 이름만 가져온다. sql where userid = name
serializer_class = self.get_serializer_class()
serializer = serializer_class(queryset, many=True)
# headers = self.get_success_headers(serializer.data)
#format(('date', "%Y-%m-%d"), "%Y-%m")
total_sen = self.get_queryset().filter(user_id=user_id).count()
avg_sen = self.get_queryset().filter(user_id=user_id).aggregate(
Avg('title'))
avg_sen['total_sen'] = total_sen
avg_month = self.get_queryset().filter(
user_id=user_id).values('date_m').annotate(Avg('title'))
page = self.paginate_queryset(queryset)
if page is not None:
serializer = self.get_serializer(page, many=True)
return self.get_paginated_response(serializer.data)
return Response(
data={
# "status": 201, {"total_sen": total_sen})
# "total": {"total_sen": total_sen},
"avg": avg_sen,
"m_avg": avg_month,
"data": serializer.data,
# "data": score,
# "user_id": user_id,
},
status=status.HTTP_201_CREATED,
# headers=headers,
)
def get(self, request, *args, **kwargs):
user_id = request.GET.get('user_id', None)
queryset = self.get_queryset().filter(
word_user_id=user_id) # 필터 추가, 이름만 가져온다. sql where userid = name
tweet_list, df = twitter_user(user_id)
words_dic, noun_adj_adv_list = count_word(df)
# words, noun_adj_adv_list = count_word(twitter_date(user_id, '2020-12'))
# wdf = twitter_date("SANDEUL920320", '2020-12')
# for i in range(len(words.keys())):
# wt = (wdf['Tweets'][i], wdf['Dates'][i])
# ww.append(wt)
for key, value in words_dic.items():
Word.objects.create(word_user_id=user_id, text=key, value=value)
# ww = Word.objects.values('text', 'value') #sql select word, word_count
# wdf = noun_adj_adv_list
# for i in range(len(noun_adj_adv_list)):
# Word.objects.create(sen_id=i, word_date='2020-12', word=noun_adj_adv_list[i][0], word_count=words[i][1])
serializer_class = self.get_serializer_class()
serializer = serializer_class(queryset, many=True)
# headers = self.get_success_headers(serializer.data)
page = self.paginate_queryset(queryset)
if page is not None:
serializer = self.get_serializer(page, many=True)
return self.get_paginated_response(serializer.data)
return Response(
data={
# "word_index": 201,
# "message": twitter_date("SANDEUL920320", '2020-12'),
# "message": twitter_date(user_id, '2020-12'),
# "sen_id": twitter_date("SANDEUL920320", '2020-12'),
# "word_date": 2020-12,
# "word": noun_adj_adv_list,
# "word_count": words
"data": serializer.data,
## "data": ww
},
status=status.HTTP_201_CREATED,
# headers=headers,
)