# -*- coding: utf-8 -*-
from aip import AipNlp
import csv
import pandas as pd
from pandas.core.frame import DataFrame
APP_ID = '******'
API_KEY = '888888888'
SECRET_KEY = '88888888'
client = AipNlp(APP_ID, API_KEY, SECRET_KEY)
def output():
urls = []
with open('redio11.csv', "r") as f:
reader = csv.reader(f)
for row in reader:
urls.append(row[0])
return urls
def sentimentClassify():
x = output()
i = 1
pp=[]
np=[]
con=[]
sen=[]
all={}
for i in range(10640):
text = x[i]
result = client.sentimentClassify(text);
print(result)
if "error_code" in result.keys():
pp.append(" ")
np.append(" ")
con.append(" ")
sen.append(" ")
all['positive_prob'] = pp
all['negative_prob'] = np
all['confidence'] = con
all['sentiment'] = sen
else:
data = result['items']
items = data[0]
positive_prob = items['positive_prob']
pp.append(positive_prob)
negative_prob = items['negative_prob']
np.append(negative_prob)
confidence = items['confidence']
con.append(confidence)
sentiment = items['sentiment']
sen.append(sentiment)
all['positive_prob'] = pp
all['negative_prob'] = np
all['confidence'] = con
all['sentiment'] = sen
return all
def add(ulist):
csv_input = pd.read_csv('redio11.csv', encoding='gbk')
pp = DataFrame(ulist['positive_prob'])
csv_input["positive_prob"] = pp
csv_input.to_csv('redio11.csv', index=False, encoding='gbk')
np = DataFrame(ulist['negative_prob'])
csv_input["negative_prob"] = np
csv_input.to_csv('redio11.csv', index=False, encoding='gbk')
con = DataFrame(ulist['confidence'])
csv_input["confidence"] = con
csv_input.to_csv('redio11.csv', index=False, encoding='gbk')
sen = DataFrame(ulist['sentiment'])
csv_input["sentiment"] = sen
csv_input.to_csv('redio11.csv', index=False, encoding='gbk')
if __name__ == '__main__':
ALL = sentimentClassify()
add(ALL)
调用百度API进行情感分析
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