def findRelavantArticles():
es = Elasticsearch()
comparetweet = TwitterSearchV2.userSearchbyName("drubix_cube")
comparetweet1 = comparetweet.split()
ct1 = ""
for wc in range(500):
ct1 = ct1 + " " + comparetweet1[wc]
q2= {
"size": 8,
"query": {
"match": {"text": ct1}
}}
resA = es.search(index='twf-index',body = q2)
urlList = []
for hit in resA['hits']['hits']:
urlList.append("%(url)s" % hit["_source"])
return urlList
def personewspage():
if request.method == "POST":
twitter_handle = request.form['text']
listOfTextFiles = ["BodyTexts.json"]
es = Elasticsearch()
es.indices.create(index='twf-index', ignore=400)
i = 0
for fileName in listOfTextFiles:
with open(fileName) as bodytx:
tweets = {}
tweets = json.load(bodytx)
for key in tweets.keys():
doc = {
'url' : key,
'text' : tweets[key]
}
es.index(index = 'twf-index' , doc_type='tweet',id = i, body = doc)
i = i+1
es.indices.refresh(index='twf-index')
comparetweet = TwitterSearchV2.userSearchbyName(twitter_handle)
comparetweet1 = comparetweet.split()
ct1 = ""
for wc in range(500):
ct1 = ct1 + " " + comparetweet1[wc]
q2= {
"size": 8,
"query": {
"match": {"text": ct1}
}}
resA = es.search(index='twf-index',body = q2)
urlList = []
for hit in resA['hits']['hits']:
urlList.append("%(url)s" % hit["_source"])
return render_template('persoNews.html', urlList=urlList)
