WatsonApiException: Error: invalid-api-key, Code: 401

Question

我在 IBM Watson 中找不到 Alchemy Language API。

我可以使用自然语言理解服务来做到这一点吗？

当我添加

from watson_developer_cloud import NaturalLanguageUnderstandingV1
from watson_developer_cloud.natural_language_understanding_v1 
  import Features, EntitiesOptions, KeywordsOptions

它显示组合关键字的一些错误

# In[]:
import tweepy
import re
import time
import math
import pandas as pd
from watson_developer_cloud import AlchemyLanguageV1

def initAlchemy():
    al = AlchemyLanguageV1(api_key='GRYVUMdBbOtJXxNOIs1aopjjaiyOmLG7xJBzkAnvvwLh')
    return al

def initTwitterApi():
    consumer_key = 'OmK1RrZCVJSRmKxIuQqkBExvw'
    consumer_secret = 'VWn6OR4rRgSi7qGnZHCblJMhrSvj1QbJmf0f62uX6ZQWZUUx5q'
    access_token = '4852231552-adGooMpTB3EJYPHvs6oGZ40qlo3d2JbVjqUUWkJ'
    access_token_secret = 'm9hgeM9p0r1nn8IoQWJYBs5qUQu56XmrAhsDSYKjuiVA4'
    auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
    auth.set_access_token(access_token, access_token_secret)
    api = tweepy.API(auth)
    return api
'''This function is implemented to handle tweepy exception errors
because search is rate limited at 180 queries per 15 minute window by twitter'''
def limit(cursor):
    while True:
        try:
            yield cursor.next()
        except tweepy.TweepError as error:
            print(repr(error))
            print("Twitter Request limit error reached sleeping for 15 minutes")
            time.sleep(16*60)
        except tweepy.RateLimitError:
            print("Rate Limit Error occurred Sleeping for 16 minutes")
            time.sleep(16*60)
def retrieveTweets(api, search, lim):
    if(lim == ""):
        lim = math.inf
    else:
        lim = int(lim)
    text = []
    for tweet in limit(tweepy.Cursor(api.search, q=search).items(limit = lim)):
        t = re.sub('s+', ' ', tweet.text)
        text.append(t)
    data = {"Tweet":text,
            "Sentiment":"",
            "Score":""}
    dataFrame = pd.DataFrame(data, columns=["Tweet","Sentiment","Score"])
    return dataFrame
def analyze(al,dataFrame):
    sentiment = []
    score = []
    for i in range(0, dataFrame["Tweet"].__len__()):
        res = al.combined(text=dataFrame["Tweet"][i],
                          extract="doc-sentiment",
                          sentiment=1)
        sentiment.append(res["docSentiment"]["type"])
        if(res["docSentiment"]["type"] == "neutral"):
            score.append(0)
        else:
            score.append(res["docSentiment"]["score"])
    dataFrame["Sentiment"] = sentiment
    dataFrame["Score"] = score
    return dataFrame

def main():
    #Initialse Twitter Api
    api = initTwitterApi()
    #Retrieve tweets
    dataFrame = retrieveTweets(api,input("Enter the search query (e.g. #hillaryclinton ) : "), input("Enter limit for number of tweets to be searched or else just hit enter : "))
    #Initialise IBM Watson Alchemy Language Api
    al = initAlchemy()
    #Do Document Sentiment analysis
    dataFrame = analyze(al, dataFrame)
    #Save tweets, sentiment, and score data frame in csv file
    dataFrame.to_csv(input("Enter the name of the file (with .csv extension) : "))
if __name__ == '__main__':
    main()# -*- coding: utf-8 -*-

Answer 1

Watson Natural Language Understanding只有一个组合调用，但由于它是唯一的调用，所以它不被称为组合，它实际上是analyze。了解详细信息的最佳位置是 API 文档 - https://www.ibm.com/watson/developercloud/natural-language-understanding/api/v1/?python#post-analyze