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Scraper.py
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Scraper.py
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# -*- coding: utf-8 -*-
"""
Created on Tue Sep 20 14:20:53 2022
@author: florent, mathias
Exorde Labs
"""
CLEANR = re.compile('<.*?>|&([a-z0-9]+|#[0-9]{1,6}|#x[0-9a-f]{1,6});')
netConfig = requests.get("https://raw.githubusercontent.com/MathiasExorde/TestnetProtocol-staging/main/NetworkConfig.txt").json()
w3 = Web3(Web3.HTTPProvider(netConfig["_urlSkale"]))
def cleanhtml(raw_html):
cleantext = re.sub(CLEANR, '', raw_html)
return cleantext
def preprocess(text):
new_text = [
]
for t in text.split(" "):
t = '@user' if t.startswith('@') and len(t) > 1 else t
t = 'http' if t.startswith('http') else t
new_text.append(t)
return " ".join(new_text)
def generateFileName():
random.seed(random.random())
baseSeed = ''.join(random.choices(string.ascii_uppercase + string.digits, k=256))
fileName = baseSeed + '.txt'
return fileName
def filebase_upload(content: str, bucket_name: str):
# this is not AWS credentials. These are just an open public API endpoint to pin IPFS file, temporarily.
s3 = boto3.resource(
's3',
endpoint_url = 'https://s3.filebase.com',
region_name='us-east-1',
aws_access_key_id='24C83682E3758DA63DD9',
aws_secret_access_key='B149EQGd1WwGLpuWHgPGT5wQ5OqgXPq3AOQtTeBr'
)
response = s3.Object(bucket_name, generateFileName()).put(Body=content)
return response["ResponseMetadata"]["HTTPHeaders"]['x-amz-meta-cid']
def gen_chan(r):
for idx, page in enumerate(r):
for thread in r[idx]['threads']:
yield thread
def get_threads(threads, key: str, default='NaN'):
return threads.get(key, default)
def downloadFile(hashname: str, name: str):
headers = {
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/88.0.4324.146 Safari/537.36',
}
url = "https://ipfs.filebase.io/ipfs/" + hashname
r = requests.get(url, headers=headers, allow_redirects=True,
stream=True, timeout=1200)
try:
os.mkdir("ExordeWD")
except:
pass
open('ExordeWD\\'+name, 'wb').write(r.content)
def downloadFile2Data2(hashname: str):
headers = {
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/88.0.4324.146 Safari/537.36',
}
url = "https://w3s.link/ipfs/" + hashname
trials = 0
while trials < 5:
try:
r = requests.get(url, timeout=(0.5,3))
#print(r)
if (r.status_code == 200):
try:
return r.json()
except Exception as e:
pass
#print(e)
else:
pass
except requests.exceptions.Timeout:
trials += 1
# Maybe set up for a retry, or continue in a retry loop
except requests.exceptions.TooManyRedirects:
trials += 1
# Tell the user their URL was bad and try a different one
except requests.exceptions.RequestException as e:
trials += 1
# catastrophic error. bail.
except Exception as e:
trials += 1
pass
if (trials >= 5):
return None
class Scraper():
def __init__(self, app):
r = requests.get("https://raw.githubusercontent.com/lukes/ISO-3166-Countries-with-Regional-Codes/master/all/all.csv").text.split("\n")
names = r[0]
data = r[1:]
self.app = app
self.langcodes = pd.DataFrame(data)
self.langcodes = pd.DataFrame(self.langcodes[0].str.split(",").values.tolist()).reset_index(drop=True)
self.langcodes = self.langcodes[self.langcodes.columns[:-1]]
self.langcodes.columns=names.split(",")
self.stopWords = dict()
self.stopWords["en"] = requests.get("https://raw.githubusercontent.com/LIAAD/yake/master/yake/StopwordsList/stopwords_{}.txt".format("en"), allow_redirects=True, stream=True, timeout=(1,5)).text.replace("\r","").split("\n")
self.models = dict()
self.languages = dict()
self.threads = list()
self.pendingBlocks = list()
self.lastBatchSize = 100
self.nbItems = 0
self.keywords = list()
goingOn = True
try:
os.mkdir("ExordeWD")
except:
pass
trial = 0
while (os.path.exists('ExordeWD\\lang.json') == False and trial < 3):
downloadFile("QmQK6M7pum6W2ZRLdhgzEw7vH8GYMmvwR3aX3hFkMXWrus", "lang.json")
with open('ExordeWD\\lang.json', "r") as file:
self.lang_table = json.load(file)["langlist"]
if (os.path.exists('ExordeWD\\lang.json') == False):
goingOn = False
self.listlang = self.lang_table
def manage_scraping(self):
sender = threading.Thread(target=self.manage_sending)
sender.daemon = True
sender.start()
try:
while True:
try:
threads= list()
removal = list()
for i in range(len(self.threads)):
if(self.threads[i].is_alive() == True):
#threads.append(self.threads[i])
removal.append(self.threads[i])
else:
removal.append(self.threads[i])
self.threads = threads
while(len(removal) > 0):
del removal[0]
keywords = [x.replace(" ","%20") for x in self.keywords]
for target in ["4chan", "twitter", "reddit"]:
# if(target == "4chan"):
# x = threading.Thread(target=self.scrape, args=(target, keywords))
# x.start()
# self.threads.append(x)
if(target == "twitter"):
x = threading.Thread(target=self.scrape, args=("twitter1", keywords))
x.daemon = True
x.start()
self.threads.append(x)
y = threading.Thread(target=self.scrape, args=("twitter2", keywords))
y.daemon = True
y.start()
self.threads.append(x)
if(target == "reddit"):
x = threading.Thread(target=self.scrape, args=("reddit1", keywords))
x.daemon = True
x.start()
self.threads.append(x)
y = threading.Thread(target=self.scrape, args=("reddit2", keywords))
y.daemon = True
y.start()
self.threads.append(y)
z = threading.Thread(target=self.scrape, args=("reddit3", keywords))
z.daemon = True
z.start()
self.threads.append(z)
a = threading.Thread(target=self.scrape, args=("reddit4", keywords))
a.daemon = True
a.start()
self.threads.append(a)
if(len(self.keywords) > 0):
try:
delay = int(_contract.functions.get("autoScrapingFrequency").call())
time.sleep(delay)
except:
time.sleep(20*60)
else:
try:
delay = int(_contract.functions.get("autoScrapingFrequency").call())
time.sleep(delay)
except:
time.sleep(20*60)
except Exception as e:
pass
except Exception as e:
pass
def scrape(self, target: str, keywords: list):
try:
results = dict()
try:
exd_token = random.choice(list(pd.DataFrame([x.strip().lower() for x in requests.get("https://raw.githubusercontent.com/exorde-labs/TestnetProtocol/main/targets/keywords.txt").text.replace("\n","").split(",") if x != ""])[0]))
except:
exd_token = "bitcoin"
if scrape_printing_enabled:
print("[{}]\t{}\t{}\t\t{}".format(dt.datetime.now(),"COLLECT DATA", "scrape", "KEYWORDS SELECTED = [{}]".format(exd_token)))
if(exd_token not in keywords):
keywords.append(exd_token)
if(target == "4chan"):
try:
for p in range(1, 10):
#print(p)
for endpoint in [f"https://a.4cdn.org/biz/{p}.json", f"https://a.4cdn.org/news/{p}.json"]:
r = requests.get(endpoint)
r = json.loads(r.text)
for post in gen_chan(r):
for key in post:
threads = post[key][0]
no = get_threads(threads,'no')
time = get_threads(threads,'time')
com = cleanhtml(html.unescape(get_threads(threads,'com')))
name = get_threads(threads,'name')
ids = get_threads(threads,'id')
filename = html.unescape(get_threads(threads,'filename')) + html.unescape(get_threads(threads,'ext'))
replies = get_threads(threads,'replies')
images = get_threads(threads,'images')
url = re.search("(?P<url>https?://[^\s]+)", get_threads(threads,'com')).group("url") if re.search("(?P<url>https?://[^\s]+)", get_threads(threads,'com')) != None else None
tr_post = dict()
tr_post["internal_id"] = str(no)
tr_post["internal_parent_id"] = None
tr_post["keyword"] = ""
tr_post["mediaType"] = "Social_Networks"
tr_post["domainName"] = "4channel.org"
tr_post["url"] = "https://boards.4channel.org/biz/thread/" + str(no)
tr_post["author"] = name
tr_post["authorLocation"] = ""
tr_post["creationDateTime"] = dt.datetime.fromtimestamp(time,pytz.timezone('UTC'))
if(tr_post["creationDateTime"] >= (dt.datetime.now(pytz.timezone('UTC')) - dt.timedelta(minutes=5))):
tr_post["lang"] = detect(text=com.replace("\n",""), low_memory=False)["lang"]
if(tr_post["lang"] in self.languages):
self.languages[tr_post["lang"]] += 1
else:
self.languages[tr_post["lang"]] = 1
tr_post["title"] = ''
tr_post["description"] = ''
tr_post["content"] = com.replace("\n","").replace("'","''")
if(tr_post["content"] in ("","[removed]") and tr_post["title"] not in ("","[deleted]")):
tr_post["content"] = tr_post["title"]
tr_post["controversial"] = False
tr_post["tokenOfInterest"] = list()
max_ngram_size = 1
deduplication_thresold = 0.9
deduplication_algo = 'seqm'
windowSize = 1
numOfKeywords = 20
kw_extractor = yake.KeywordExtractor(lan=tr_post["lang"], n=max_ngram_size, dedupLim=deduplication_thresold, dedupFunc=deduplication_algo, windowsSize=windowSize, top=numOfKeywords, features=None)
kx = kw_extractor.extract_keywords(tr_post["content"])
for kw in kx:
if(kw[0] not in tr_post["tokenOfInterest"]):
tr_post["tokenOfInterest"].append(kw[0])
tr_post["reference"] = endpoint.split("/")[3]
tr_post["link"] = None
tr_post["is_video"] = None
tr_post["nb_comments"] = replies
tr_post["nb_shared"] = 0
tr_post["nb_liked"] = 0
tr_post["topics"] = list()
tr_post["entities"] = list()
tr_post["medias"] = list()
tr_post["links"] = list()
if(tr_post["url"] not in results and tr_post["content"] != 'NaN'):
self.send_doc(tr_post)
if 'last_replies' in threads:
for comment in threads['last_replies']:
com_com = cleanhtml(comment.get('com', 'NaN'))
time_com = comment.get('time', 'NaN')
fname_com = comment.get('filename', 'NaN')
tr_post = dict()
tr_post["internal_id"] = str(comment["no"])
tr_post["internal_parent_id"] = str(no)
tr_post["keyword"] = ""
tr_post["mediaType"] = "Social_Networks"
tr_post["domainName"] = "4channel.org"
tr_post["url"] = "https://boards.4channel.org/biz/thread/" + str(no) + "/" + str(comment["no"])
#print(tr_post["url"])
tr_post["author"] = name
tr_post["authorLocation"] = ""
tr_post["creationDateTime"] = dt.datetime.fromtimestamp(time_com,pytz.timezone('UTC'))
tr_post["lang"] = detect(text=com_com.replace("\n",""), low_memory=False)["lang"]
if(tr_post["lang"] in self.languages):
self.languages[tr_post["lang"]] += 1
else:
self.languages[tr_post["lang"]] = 1
tr_post["title"] = ''
tr_post["description"] = ''
tr_post["content"] = com_com.replace("\n","").replace("'","''")
if(tr_post["content"] in ("","[removed]") and tr_post["title"] != ""):
tr_post["content"] = tr_post["title"]
tr_post["controversial"] = False
tr_post["tokenOfInterest"] = list()
max_ngram_size = 1
deduplication_thresold = 0.9
deduplication_algo = 'seqm'
windowSize = 1
numOfKeywords = 20
kw_extractor = yake.KeywordExtractor(lan=tr_post["lang"], n=max_ngram_size, dedupLim=deduplication_thresold, dedupFunc=deduplication_algo, windowsSize=windowSize, top=numOfKeywords, features=None)
kx = kw_extractor.extract_keywords(tr_post["content"])
for kw in kx:
if(kw[0] not in tr_post["tokenOfInterest"]):
tr_post["tokenOfInterest"].append(kw[0])
tr_post["reference"] = endpoint.split("/")[3]
tr_post["link"] = None
tr_post["is_video"] = None
tr_post["nb_comments"] = 0
tr_post["nb_shared"] = 0
tr_post["nb_liked"] = 0
tr_post["topics"] = list()
tr_post["entities"] = list()
tr_post["medias"] = list()
tr_post["links"] = list()
if(tr_post["url"] not in results):
self.send_doc(tr_post)
#results[tr_post["url"]] = tr_post
#self.send_item(tr_post)
except Exception as e:
# print()
# print(target, e)
# print()
pass
if(target == "reddit1"):
try:
r = requests.get("https://api.pushshift.io/reddit/search/comment/?q="+"|".join(keywords)+"&after=5m").json()
#r = requests.get("https://api.pushshift.io/reddit/search/comment/?q="+keyword+"&after=5m").json()
posts = r["data"]
for post in posts:
break
#try:
tr_post = dict()
tr_post["internal_id"] = post["id"]
tr_post["internal_parent_id"] = post["parent_id"] if post["parent_id"] != None else 0
tr_post["domainName"] = "reddit.com"
tr_post["mediaType"] = "Social_Networks"
tr_post["url"] = "https://www.reddit.com" + post["permalink"]
tr_post["author"] = post["author"]
tr_post["authorLocation"] = ""
tr_post["creationDateTime"] = dt.datetime.fromtimestamp(post["created_utc"],pytz.timezone('UTC'))
tr_post["lang"] = detect(text=post["body"].replace("\n",""), low_memory=False)["lang"]
if(tr_post["lang"] in self.languages):
self.languages[tr_post["lang"]] += 1
else:
self.languages[tr_post["lang"]] = 1
tr_post["title"] = ''
tr_post["description"] = ''
tr_post["content"] = cleanhtml(post["body"].replace("\n","").replace("'","''"))
if(tr_post["content"] in ("","[removed]") and tr_post["title"] != ""):
tr_post["content"] = tr_post["title"]
subkeywords = [x for x in keywords if x in tr_post["content"]]
tr_post["keyword"] = subkeywords[0] if len(subkeywords) != 0 else keywords[0]
# tokens = cat_tokenizer(tr_post["content"][:500], return_tensors='pt')
# output = cat_model(**tokens)
# scores = output[0][0].detach().numpy()
# scores = expit(scores)
# predictions = (scores >= 0.5) * 1
# cat_results = list()
# for i in range(len(predictions)):
# if predictions[i]:
# try:
# cat_results.append(cat_class_mapping[i])
# except:
# pass
# tr_post["categories"] = cat_results
# try:
# text = preprocess(tr_post["content"])
# encoded_input = ironizer(text, return_tensors='pt')
# output = mdl_ironizer(**encoded_input)
# scores = output[0][0].detach().numpy()
# scores = softmax(scores)
# if(scores[0] < scores[1]):
# isIrony = True
# else:
# isIrony = False
# tr_post["isIrony"] = isIrony
# except:
# text = preprocess(tr_post["content"][:500])
# encoded_input = ironizer(text, return_tensors='pt')
# output = mdl_ironizer(**encoded_input)
# scores = output[0][0].detach().numpy()
# scores = softmax(scores)
# if(scores[0] < scores[1]):
# isIrony = True
# else:
# isIrony = False
# tr_post["isIrony"] = isIrony
# try:
# tr_post["emotions"] = self.calc_emotions(tr_post["content"])
# except:
# tr_post["emotions"] = self.calc_emotions(tr_post["content"][:500])
# if(len(tr_post["content"]) < 50):
# tr_post["emotions"] = tr_post["emotions"].loc[:2]
# try:
# tr_post["sentiment"] = tr_post["emotions"].loc[0, "label"]
# except:
# tr_post["sentiment"] = tr_post["emotions"].loc[0, "label"]
tr_post["controversial"] = False
# tr_post["toxic"] = self.models["toxicity"][0].predict(self.models["toxicity"][1].transform([tr_post["content"]]))[0]
# tr_post["censored"] = (self.models["censoring"][0].predict(self.models["censoring"][1].transform([tr_post["content"]]))[0] or self.models["censoring"][0].predict(self.models["censoring"][1].transform([tr_post["url"]]))[0])
tr_post["tokenOfInterest"] = list()
max_ngram_size = 1
deduplication_thresold = 0.9
deduplication_algo = 'seqm'
windowSize = 1
numOfKeywords = 20
kw_extractor = yake.KeywordExtractor(lan=tr_post["lang"], n=max_ngram_size, dedupLim=deduplication_thresold, dedupFunc=deduplication_algo, windowsSize=windowSize, top=numOfKeywords, features=None)
kx = kw_extractor.extract_keywords(tr_post["content"])
for kw in kx:
if(kw[0] not in tr_post["tokenOfInterest"]):
tr_post["tokenOfInterest"].append(kw[0])
tr_post["reference"] = post["subreddit"]
tr_post["link"] = None
tr_post["is_video"] = None
tr_post["nb_comments"] = 0
tr_post["nb_shared"] = 0
tr_post["nb_liked"] = 0
tr_post["topics"] = list()
tr_post["entities"] = list()
tr_post["medias"] = list()
tr_post["links"] = list()
if(tr_post["url"] not in results):
#results[tr_post["url"]] = tr_post
self.send_doc(tr_post)
#self.send_item(tr_post)
except Exception as e:
# print()
# print(target, e)
# print()
pass
if(target == "reddit2"):
r = requests.get("https://api.pushshift.io/reddit/search/submission/?q="+"|".join(keywords)+"&after=5m").json()
posts = r["data"]
for post in posts:
try:
tr_post = dict()
tr_post["internal_id"] = post["id"]
tr_post["internal_parent_id"] = 0
tr_post["domainName"] = "reddit.com"
tr_post["mediaType"] = "Social_Networks"
tr_post["url"] = post["full_link"]
tr_post["author"] = post["author"]
tr_post["authorLocation"] = ""
tr_post["creationDateTime"] = dt.datetime.fromtimestamp(post["created_utc"],pytz.timezone('UTC'))
tr_post["lang"] = detect(text=post["selftext"].replace("\n",""), low_memory=False)["lang"] if "selftext" in post else detect(text=post["titile"].replace("\n",""), low_memory=False)["lang"]
if(tr_post["lang"] in self.languages):
self.languages[tr_post["lang"]] += 1
else:
self.languages[tr_post["lang"]] = 1
tr_post["title"] = post["title"]
tr_post["description"] = ''
tr_post["content"] = cleanhtml(post["selftext"].replace("\n","").replace("'","''")) if "selftext" in post else cleanhtml(post["title"].replace("\n","").replace("'","''"))
if(tr_post["content"] in ("","[removed]") and tr_post["title"] != ""):
tr_post["content"] = tr_post["title"]
subkeywords = [x for x in keywords if x in tr_post["content"]]
tr_post["keyword"] = subkeywords[0] if len(subkeywords) != 0 else keywords[0]
tr_post["controversial"] = False
tr_post["tokenOfInterest"] = list()
max_ngram_size = 1
deduplication_thresold = 0.9
deduplication_algo = 'seqm'
windowSize = 1
numOfKeywords = 20
kw_extractor = yake.KeywordExtractor(lan=tr_post["lang"], n=max_ngram_size, dedupLim=deduplication_thresold, dedupFunc=deduplication_algo, windowsSize=windowSize, top=numOfKeywords, features=None)
kx = kw_extractor.extract_keywords(tr_post["content"])
for kw in kx:
if(kw[0] not in tr_post["tokenOfInterest"]):
tr_post["tokenOfInterest"].append(kw[0])
tr_post["reference"] = post["subreddit"]
tr_post["link"] = post["url"]
tr_post["is_video"] = post["is_video"]
tr_post["nb_comments"] = 0
tr_post["nb_shared"] = 0
tr_post["nb_liked"] = 0
tr_post["topics"] = list()
tr_post["entities"] = list()
tr_post["medias"] = list()
tr_post["links"] = list()
if(tr_post["url"] not in results):
self.send_doc(tr_post)
except Exception as e:
pass
if(target == "reddit3"):
r = requests.get("https://api.pushshift.io/reddit/search/comment/?subreddit="+"|".join(keywords)+"&after=5m").json()
#r = requests.get(f'https://api.pushshift.io/reddit/search/comment/?subreddit='+keyword+"&after=5m").json()
posts = r["data"]
for post in posts:
try:
tr_post = dict()
tr_post["internal_id"] = post["id"]
tr_post["internal_parent_id"] = post["parent_id"] if post["parent_id"] != None else 0
tr_post["domainName"] = "reddit.com"
tr_post["mediaType"] = "Social_Networks"
tr_post["url"] = "https://www.reddit.com" + post["permalink"]
tr_post["author"] = post["author"]
tr_post["authorLocation"] = ""
tr_post["creationDateTime"] = dt.datetime.fromtimestamp(post["created_utc"],pytz.timezone('UTC'))
tr_post["lang"] = detect(text=post["body"].replace("\n",""), low_memory=False)["lang"]
if(tr_post["lang"] in self.languages):
self.languages[tr_post["lang"]] += 1
else:
self.languages[tr_post["lang"]] = 1
tr_post["title"] = ''
tr_post["description"] = ''
tr_post["content"] = cleanhtml(post["body"].replace("\n","").replace("'","''"))
if(tr_post["content"] in ("","[removed]") and tr_post["title"] != ""):
tr_post["content"] = tr_post["title"]
subkeywords = [x for x in keywords if x in tr_post["content"]]
tr_post["keyword"] = subkeywords[0] if len(subkeywords) != 0 else keywords[0]
tr_post["controversial"] = False
tr_post["tokenOfInterest"] = list()
max_ngram_size = 1
deduplication_thresold = 0.9
deduplication_algo = 'seqm'
windowSize = 1
numOfKeywords = 20
kw_extractor = yake.KeywordExtractor(lan=tr_post["lang"], n=max_ngram_size, dedupLim=deduplication_thresold, dedupFunc=deduplication_algo, windowsSize=windowSize, top=numOfKeywords, features=None)
kx = kw_extractor.extract_keywords(tr_post["content"])
for kw in kx:
if(kw[0] not in tr_post["tokenOfInterest"]):
tr_post["tokenOfInterest"].append(kw[0])
tr_post["reference"] = post["subreddit"]
tr_post["link"] = "https://www.reddit.com" + post["permalink"]
tr_post["is_video"] = post["is_video"] if "is_video" in post else None
tr_post["nb_comments"] = 0
tr_post["nb_shared"] = 0
tr_post["nb_liked"] = 0
tr_post["topics"] = list()
tr_post["entities"] = list()
tr_post["medias"] = list()
tr_post["links"] = list()
if(tr_post["url"] not in results):
self.send_doc(tr_post)
#Save to DB
except Exception as e:
pass
if(target == "reddit4"):
r = requests.get("https://api.pushshift.io/reddit/search/submission/?subreddit="+"|".join(keywords)+"&after=5m").json()
posts = r["data"]
for post in posts:
try:
tr_post = dict()
tr_post["internal_id"] = post["id"]
tr_post["internal_parent_id"] = post["parent_id"] if post["parent_id"] != None else 0
tr_post["domainName"] = "reddit.com"
tr_post["mediaType"] = "Social_Networks"
tr_post["keyword"] = ",".join(self.keywords)
tr_post["url"] = "https://www.reddit.com" + post["permalink"]
tr_post["author"] = post["author"]
tr_post["authorLocation"] = ""
tr_post["creationDateTime"] = dt.datetime.fromtimestamp(post["created_utc"],pytz.timezone('UTC'))
tr_post["lang"] = detect(text=post["body"].replace("\n",""), low_memory=False)["lang"]
if(tr_post["lang"] in self.languages):
self.languages[tr_post["lang"]] += 1
else:
self.languages[tr_post["lang"]] = 1
tr_post["title"] = ''
tr_post["description"] = ''
tr_post["content"] = cleanhtml(post["body"].replace("\n","").replace("'","''"))
if(tr_post["content"] in ("","[removed]") and tr_post["title"] != ""):
tr_post["content"] = tr_post["title"]
subkeywords = [x for x in keywords if x in tr_post["content"]]
tr_post["keyword"] = subkeywords[0] if len(subkeywords) != 0 else keywords[0]
tr_post["controversial"] = False
tr_post["tokenOfInterest"] = list()
max_ngram_size = 1
deduplication_thresold = 0.9
deduplication_algo = 'seqm'
windowSize = 1
numOfKeywords = 20
kw_extractor = yake.KeywordExtractor(lan=tr_post["lang"], n=max_ngram_size, dedupLim=deduplication_thresold, dedupFunc=deduplication_algo, windowsSize=windowSize, top=numOfKeywords, features=None)
kx = kw_extractor.extract_keywords(tr_post["content"])
for kw in kx:
if(kw[0] not in tr_post["tokenOfInterest"]):
tr_post["tokenOfInterest"].append(kw[0])
tr_post["reference"] = post["subreddit"]
tr_post["link"] = "https://www.reddit.com" + post["permalink"]
tr_post["is_video"] = post["is_video"] if "is_video" in post else None
tr_post["nb_comments"] = 0
tr_post["nb_shared"] = 0
tr_post["nb_liked"] = 0
tr_post["topics"] = list()
tr_post["entities"] = list()
tr_post["medias"] = list()
tr_post["links"] = list()
if(tr_post["url"] not in results):
self.send_doc(tr_post)
except Exception as e:
pass
if(target == "instagram"):
pass
if (target == "twitter1"):
d= dt.datetime.now(pytz.timezone('UTC')) - dt.timedelta(minutes=5)
try:
for keyword in keywords:
for i, _post in enumerate(snscrape.modules.twitter.TwitterSearchScraper('(from:{} OR about:{}) since_time:{}'.format(keyword, keyword, int(d.timestamp()))).get_items()):
post = _post.__dict__
tr_post = dict()
tr_post["internal_id"] = post["id"]
tr_post["internal_parent_id"] = post["inReplyToTweetId"] #post["referenced_tweets"][0]["id"] if "referenced_tweets" in post and len(post["referenced_tweet"]) != 0 and post["referenced_tweets"][0]["id"] != None else 0
tr_post["keyword"] = keyword
tr_post["mediaType"] = "Social_Networks"
tr_post["domainName"] = "twitter.com"
tr_post["url"] = "https://twitter.com/ExordeLabs/status/{}".format(post["id"])
tr_post["author"] = post["user"].displayname
tr_post["authorLocation"] = post["user"].location
tr_post["creationDateTime"] = post["date"] #parse(post["date"]).replace(tzinfo=pytz.timezone('UTC'))
tr_post["lang"] = post["lang"]
if(tr_post["lang"] in self.languages):
self.languages[tr_post["lang"]] += 1
else:
self.languages[tr_post["lang"]] = 1
tr_post["title"] = '' #post["title"] if "title" in post else None
tr_post["description"] = '' #post["annotations"]["description"] if "annotations" in post and "description" in post["annotations"] else ''
tr_post["content"] = cleanhtml(post["renderedContent"].replace("\n","").replace("'","''"))
if(tr_post["content"] in ("","[removed]") and tr_post["title"] != ""):
tr_post["content"] = tr_post["title"]
tr_post["controversial"] = False
tr_post["tokenOfInterest"] = list()
max_ngram_size = 1
deduplication_thresold = 0.9
deduplication_algo = 'seqm'
windowSize = 1
numOfKeywords = 20
kw_extractor = yake.KeywordExtractor(lan=tr_post["lang"], n=max_ngram_size, dedupLim=deduplication_thresold, dedupFunc=deduplication_algo, windowsSize=windowSize, top=numOfKeywords, features=None)
kx = kw_extractor.extract_keywords(tr_post["content"])
for kw in kx:
if(kw[0] not in tr_post["tokenOfInterest"]):
tr_post["tokenOfInterest"].append(kw[0])
tr_post["reference"] = ''
tr_post["links"] = list()
if("outlinks" in post and type(post["outlinks"]) != None):
try:
for j in range(len(post["outlinks"])):
tr_post["links"].append(post["outlinks"][i])
except:
pass
if("tcooutlinks" in post and type(post["tcooutlinks"]) != None):
try:
for j in range(len(post["tcooutlinks"])):
tr_post["links"].append(post["tcooutlinks"][i])
except:
pass
tr_post["is_video"] = None #post["is_video"] if "is_video" in post else ''
tr_post["nb_comments"] = post["replyCount"]
tr_post["nb_shared"] = post["retweetCount"]
tr_post["nb_liked"] = post["likeCount"]
tr_post["topics"] = post["hashtags"]
tr_post["entities"] = list()
tr_post["medias"] = list()
if("context_annotation" in post):
for lvl0 in post["context_annotations"]:
tr_post["topics"].append({"superclass":lvl0["domain"]["name"],
"superdesc":lvl0["domain"]["description"],
"class":lvl0["entity"]["name"],
"desc":lvl0["domain"]["description"],})
tr_post["mentions"] = list()
if("entities" in post):
for entType in post["entities"]:
if(entType == "hashtags"):
for i in range(len(post["entities"]["hashtags"])):
tr_post["mentions"].append(post["entities"]["hashtags"][i]["tag"])
if(entType == "mentions"):
for i in range(len(post["entities"]["mentions"])):
tr_post["mentions"].append(post["entities"]["mentions"][i]["username"])
if(entType == "urls"):
for i in range(len(post["entities"]["urls"])):
tr_post["links"].append(post["entities"]["urls"][i]["expanded_url"])
if(entType == "unwound_url"):
tr_post["links"].append(post["entities"]["unwound_url"])
if(entType == "annotations"):
for i in range(len(post["entities"]["annotations"])):
annot = post["entities"]["annotations"][i]
neo_annot = {"type":annot["type"],
"name":annot["normalized_text"],
"proba":annot["probability"]}
tr_post["entities"].append(neo_annot)
if(entType == "images"):
for i in range(len(post["entities"]["images"])):
img = post["entities"]["urls"][i]
neo_img = {"type":"img",
"url":img["url"]}
tr_post["medias"].append(neo_img)
if(tr_post["url"] not in results):
self.send_doc(tr_post)
except Exception as e:
pass
if (target == "twitter2"):
try:
d= dt.datetime.now(pytz.timezone('UTC')) - dt.timedelta(minutes=5)
for keyword in keywords:
postList = [_post.__dict__ for i, _post in enumerate(snscrape.modules.twitter.TwitterHashtagScraper(keyword + ' since_time:{}'.format(int(d.timestamp()))).get_items()) if _post.__dict__["date"].timestamp() >= d.timestamp()]
for post in postList:
if(post["date"].timestamp() > d.timestamp()):
tr_post = dict()
tr_post["internal_id"] = post["id"]
tr_post["internal_parent_id"] = post["inReplyToTweetId"] #post["referenced_tweets"][0]["id"] if "referenced_tweets" in post and len(post["referenced_tweet"]) != 0 and post["referenced_tweets"][0]["id"] != None else 0
tr_post["keyword"] = keyword
tr_post["mediaType"] = "Social_Networks"
tr_post["domainName"] = "twitter.com"
tr_post["url"] = "https://twitter.com/ExordeLabs/status/{}".format(post["id"])
tr_post["author"] = post["user"].displayname
tr_post["authorLocation"] = post["user"].location
tr_post["creationDateTime"] = post["date"] #parse(post["date"]).replace(tzinfo=pytz.timezone('UTC'))
tr_post["lang"] = post["lang"]
if(tr_post["lang"] in self.languages):
self.languages[tr_post["lang"]] += 1
else:
self.languages[tr_post["lang"]] = 1
tr_post["title"] = '' #post["title"] if "title" in post else None
tr_post["description"] = '' #post["annotations"]["description"] if "annotations" in post and "description" in post["annotations"] else ''
tr_post["content"] = cleanhtml(post["renderedContent"].replace("\n","").replace("'","''"))
if(tr_post["content"] in ("","[removed]") and tr_post["title"] != ""):
tr_post["content"] = tr_post["title"]
tr_post["controversial"] = False
tr_post["tokenOfInterest"] = list()
max_ngram_size = 1
deduplication_thresold = 0.9
deduplication_algo = 'seqm'
windowSize = 1
numOfKeywords = 20
kw_extractor = yake.KeywordExtractor(lan=tr_post["lang"], n=max_ngram_size, dedupLim=deduplication_thresold, dedupFunc=deduplication_algo, windowsSize=windowSize, top=numOfKeywords, features=None)
kx = kw_extractor.extract_keywords(tr_post["content"])
for kw in kx:
if(kw[0] not in tr_post["tokenOfInterest"]):
tr_post["tokenOfInterest"].append(kw[0])
tr_post["reference"] = ''
tr_post["links"] = list()
if("outlinks" in post and type(post["outlinks"]) != None):
try:
for j in range(len(post["outlinks"])):
tr_post["links"].append(post["outlinks"][i])
except:
pass
if("tcooutlinks" in post and type(post["tcooutlinks"]) != None):
try:
for j in range(len(post["tcooutlinks"])):
tr_post["links"].append(post["tcooutlinks"][i])
except:
pass
tr_post["is_video"] = None
tr_post["nb_comments"] = post["replyCount"]
tr_post["nb_shared"] = post["retweetCount"]
tr_post["nb_liked"] = post["likeCount"]
tr_post["topics"] = post["hashtags"]
tr_post["entities"] = list()
tr_post["medias"] = list()
if("context_annotation" in post):
for lvl0 in post["context_annotations"]:
tr_post["topics"].append({"superclass":lvl0["domain"]["name"],
"superdesc":lvl0["domain"]["description"],
"class":lvl0["entity"]["name"],
"desc":lvl0["domain"]["description"],})
tr_post["mentions"] = list()
if("entities" in post):
for entType in post["entities"]:
if(entType == "hashtags"):
for i in range(len(post["entities"]["hashtags"])):
tr_post["mentions"].append(post["entities"]["hashtags"][i]["tag"])
if(entType == "mentions"):
for i in range(len(post["entities"]["mentions"])):
tr_post["mentions"].append(post["entities"]["mentions"][i]["username"])
if(entType == "urls"):
for i in range(len(post["entities"]["urls"])):
tr_post["links"].append(post["entities"]["urls"][i]["expanded_url"])
if(entType == "unwound_url"):
tr_post["links"].append(post["entities"]["unwound_url"])
if(entType == "annotations"):
for i in range(len(post["entities"]["annotations"])):
annot = post["entities"]["annotations"][i]
neo_annot = {"type":annot["type"],
"name":annot["normalized_text"],
"proba":annot["probability"]}
tr_post["entities"].append(neo_annot)
if(entType == "images"):
for i in range(len(post["entities"]["images"])):
img = post["entities"]["urls"][i]
neo_img = {"type":"img",
"url":img["url"]}
tr_post["medias"].append(neo_img)
if(tr_post["url"] not in results):
self.send_doc(tr_post)
except Exception as e:
pass
sys.exit()
except Exception as e:
#print("scraping", e)
sys.exit()
def manage_sending(self):
_contract = self.app.cm.instantiateContract("ConfigRegistry")
while True:
try:
try:
batchSize = int(_contract.functions.get("_ModuleMinSpotBatchSize").call())
self.lastBatchSize = batchSize
except Exception as e:
batchSize = self.lastBatchSize
if(len(self.pendingBlocks) >= batchSize):
tmp = self.pendingBlocks[:batchSize]
res = None
while res == None:
try:
res = filebase_upload(json.dumps({"Content":tmp}, indent=4, sort_keys=True, default=str), self.app.cm.instantiateContract("ConfigRegistry").functions.get("SpotBucket").call())
time.sleep(7.5)
break
except:
res = None
domNames = [x["item"]["DomainName"] for x in self.pendingBlocks[:batchSize]][0]
if(res != None):
contract = self.app.cm.instantiateContract("DataSpotting")
increment_tx = contract.functions.SpotData([res], [domNames], batchSize, 'Hi Bob!').buildTransaction(
{