对于列表中的每个趋势，使用 python-twitter（和 remove/exclude 转推）提取 1000 条最新的推文

Question

使用 python-twitter 库 (https://github.com/bear/python-twitter) 我正在尝试使用雅虎 Where on earth ID 检索某个位置的前 10 大趋势的 1000 条最新推文，但无法检索似乎弄清楚如何从列表中的趋势中检索推文。

我不知道我是否遗漏了文档中的某些内容，并且在网上找不到任何有关如何从返回的列表中获取特定趋势的推文以及如何删除转推的示例。

import twitter
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer


ACCESS_TOKEN = 'XXXX'
ACCESS_TOKEN_SECRET = 'XXXX'
CONSUMER_KEY = 'XXXX'
CONSUMER_SECRET = 'XXXX'

# Define the location id for the UK
WOEID = 23424975
# Define language of tweets
LANG = "en"
# Define type of tweets we are after
TWEETS_TYPE = "recent"
# Define max number of tweets per trend
MAX_STATUSES = 1000

# API config
# API with request rate limited
api = twitter.Api(CONSUMER_KEY,
                  CONSUMER_SECRET,
                  ACCESS_TOKEN,
                  ACCESS_TOKEN_SECRET,
                  sleep_on_rate_limit=True)

print(api.VerifyCredentials())

# Query the Twitter API for the current top 10 trends in the UK.
uk_trends = api.GetTrendsWoeid(WOEID)
print(uk_trends)


# Return the 1000 most recent tweets for each trend
# This is where I want to retrieve the tweets per trend
for trend in uk_trends:
    count = MAX_STATUSES
    trend = trend
    search_results = api.GetSearch(term=trend, count=count)
    print(search_results)

我应该使用 Twitter API 本身吗？

Answer 1

我能够通过访问 Trend() 对象的名称属性、将其解析为字符串并遍历代码中返回的结果来解决问题，如下所示：

```

import os
import json
import csv

import twitter
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
import pandas as pd
import matplotlib.pyplot as plt

ACCESS_TOKEN = 'XXXX'
ACCESS_TOKEN_SECRET = 'XXXX'
CONSUMER_KEY = 'XXXX'
CONSUMER_SECRET = 'XXXX'

# Define the location id for the UK
# With Yahoo Where on Earth ID
WOEID = 23424975
# Define language of tweets
LANG = "en"
# Define type of tweets we are after
TWEETS_TYPE = "recent"
# Define max number of tweets per trend
MAX_STATUSES = 10

# API configuration
# API with request rate limited
api = twitter.Api(CONSUMER_KEY,
                  CONSUMER_SECRET,
                  ACCESS_TOKEN,
                  ACCESS_TOKEN_SECRET,
                  sleep_on_rate_limit=True)

# Check twitter account api details are correct
# print(api.VerifyCredentials())

# Query the Twitter API for the current top 10 trends in the UK.
uk_trends = api.GetTrendsWoeid(WOEID)

print(uk_trends)


# Return the 1000 most recent tweets for each trend
for trend in uk_trends:
    '''
    Extract name of each trend returned by Trend model
    and search required count value of recent tweets per trend
    '''
    trend = str(trend.name)
    count = MAX_STATUSES
    search_results = api.GetSearch(term=trend, count=count)
    print(search_results)

```

对于列表中的每个趋势，使用 python-twitter（和 remove/exclude 转推）提取 1000 条最新的推文

For each trend in list, pull the 1000 most recent tweets using python-twitter (And remove/exclude retweets)

python

twitter

python-twitter

tweets