def chinatime_GET_NEWS_time_threading(decide_time_begin, decide_time_end, q):
Title = []
Publish_time = []
Section = []
Body = []
Source = []
b_time = datetime.datetime.strptime(decide_time_begin, "%Y%m%d%H%M")
e_time = datetime.datetime.strptime(decide_time_end, "%Y%m%d%H%M")
#print(b_time, "\n", e_time)
loop_flag = False
for page in range(1, 11):
chinatime_home = "https://www.chinatimes.com/money/total?page=" + str(page) + "&chdtv"
try:
print("start collecting ChinaTime page..%s" % page)
r = crawler_tool.url_retry(chinatime_home)
soup = BeautifulSoup(r, "lxml")
time.sleep(5)
for i in range(len(soup.select("h3.title a"))):
chinatime_financial_url = "https://www.chinatimes.com" + soup.select("h3.title a")[i]["href"]
try:
r2 = crawler_tool.url_retry(chinatime_financial_url)
soup2 = BeautifulSoup(r2, "lxml")
r_time = datetime.datetime.strptime(soup2.find("meta", attrs={"name": "pubdate"})["content"], "%Y-%m-%dT%H:%M:%S+08:00")
if r_time > b_time:
continue
if r_time < e_time:
print("Web Crawler has collected ChinaTime data from {b_time} to {e_time}".format(b_time= b_time, e_time= e_time))
loop_flag = True
break
else:
Publish_time.append(r_time)
Title.append(re.sub(r"\s{1,}","",soup2.find("h1").string))
Section.append(soup2.find("meta", attrs={"name": "section"})["content"])
Source.append(soup2.find("meta", attrs={"name": "source"})["content"])
body = soup2.select("div.article-body p")
Body.append(crawler_tool.clean_html("".join(str(x) for x in body)))
time.sleep(random.uniform(0, 2))
print("ChinaTime:", r_time)
except rq.exceptions.RequestException as e:
print("in", e)
except rq.exceptions.RequestException as e:
print("home", e)
if loop_flag:
break
df = pd.DataFrame({"Title": Title, "Time": Publish_time, "Section": Section, "Source": Source, "Body": Body}).sort_values(by=["Time"])
file_name = "D:/User/Desktop/corpus/news/chinatime/" + decide_time_begin + "_" + decide_time_end + "_chinatime.csv"
df.to_csv(file_name, encoding="utf-8")
q.put(df)
def setn_GET_NEWS_time_threading(decide_time_begin, decide_time_end, q):
Title = []
Publish_time = []
Section = []
Body = []
Source = []
b_time = datetime.datetime.strptime(decide_time_begin, "%Y%m%d%H%M")
e_time = datetime.datetime.strptime(decide_time_end, "%Y%m%d%H%M")
#print(b_time, "\n", e_time)
loop_flag = False
for page in range(1, 19):
print("start collecting Setn page {page}".format(page=page))
home_url = "https://www.setn.com/ViewAll.aspx?PageGroupID=2&p=" + str(
page)
time.sleep(5)
try:
r = crawler_tool.url_retry(home_url)
soup = BeautifulSoup(r, "lxml")
for i in range(len(soup.select("h3.view-li-title a"))):
content_url = ("https://www.setn.com/" +
soup.select("h3.view-li-title a")[i]["href"])
r2 = crawler_tool.url_retry(content_url)
soup2 = BeautifulSoup(r2, "lxml")
r_time = datetime.datetime.strptime(
soup2.find("meta", attrs={"name": "pubdate"})["content"],
"%Y-%m-%dT%H:%M:%S")
if r_time > b_time:
continue
elif r_time < e_time:
loop_flag = True
print(
"Web Crawler has collected Setn data from {b_time} to {e_time}"
.format(b_time=b_time, e_time=e_time))
break
else:
Section.append(
soup2.find("meta", attrs={"property": "og:title"
})["content"].split("|")[1])
Title.append(
re.sub(
r"\s{1,}", "",
soup2.find("meta",
attrs={"property": "og:title"
})["content"].split("|")[0]))
Source.append(
soup2.find("meta", attrs={"property": "og:title"
})["content"].split("|")[2])
Publish_time.append(r_time)
Body.append(
crawler_tool.clean_html("".join(
str(x) for x in soup2.select("div#Content1 p"))))
print("Setn:", r_time)
time.sleep(random.uniform(0, 2))
except rq.exceptions.RequestException as e2:
print("home", e2)
if loop_flag == True:
break
df = pd.DataFrame({
"Title": Title,
"Time": Publish_time,
"Section": Section,
"Source": Source,
"Body": Body
})
file_name = "D:/User/Desktop/corpus/news/setn/" + decide_time_begin + "_" + decide_time_end + "_setn.csv"
df.to_csv(file_name, encoding="utf-8")
q.put(df)
def moneyDJ_GET_NEWS_time(decide_time_begin, decide_time_end):
title = []
publish_time = []
body = []
section = []
source = []
loop_flag = False
decide_time_begin = '202104200830'
decide_time_end = '202104210830'
b_time = datetime.datetime.strptime(decide_time_begin, "%Y%m%d%H%M")
e_time = datetime.datetime.strptime(decide_time_end, "%Y%m%d%H%M")
for page in range(1, 50):
home_url = "https://www.moneydj.com/KMDJ/News/NewsRealList.aspx?index1=" + str(
page) + "&a=MB06"
r = crawler_tool.url_retry(home_url)
soup = BeautifulSoup(r, "lxml")
print("start collecting moneyDJ page..%s" % page)
for i in range(
len(
soup.find("table", attrs={
"class": "forumgrid"
}).find_all("a"))):
i = 4
url = "https://www.moneydj.com" + soup.find(
"table", attrs={
"class": "forumgrid"
}).find_all("a")[i]["href"]
r2 = crawler_tool.url_retry(url)
soup2 = BeautifulSoup(r2, "lxml")
maindata = soup2.select(
"article#MainContent_Contents_mainArticle")[0]
r_time = datetime.datetime.strptime(
soup2.find('span', attrs={
'id': 'MainContent_Contents_lbDate'
}).text, "%Y/%m/%d %H:%M")
if r_time > b_time:
continue
elif r_time < e_time:
print(
"Web Crawler has collected moneyDJ from {b_time} to {e_time}"
.format(b_time=b_time, e_time=e_time))
loop_flag = True
break
else:
title_temp = re.sub(r"\s{1, }", "",
soup2.select("h1 span")[0].string)
body_temp = re.sub(r"\s{1, }", "",
crawler_tool.clean_html(str(maindata)))
if len(re.sub(r"[0-9.]", "",
body_temp)) / len(body_temp) < 0.5:
title.append(title_temp)
body.append(title_temp)
elif len(title_temp) + 100 > len(
re.sub(r"[a-zA-Z0-9/,=?:;.{}()#%'&-]", "", body_temp)):
title.append(title_temp)
body.append(title_temp)
else:
title.append(title_temp)
body.append(body_temp)
publish_time.append(r_time)
section.append("台股")
source.append("moneyDJ")
print("moneyDJ:", r_time)
time.sleep(random.uniform(0.5, 1.5))
if loop_flag:
break
df = pd.DataFrame({
"Title": title,
"Time": publish_time,
"Section": section,
"Source": source,
"Body": body
})
file_name = "D:/User/Desktop/corpus/news/temporarily/" + decide_time_begin + "_" + decide_time_end + "_moneyDJ.csv"
df.to_csv(file_name, encoding="utf-8")
def moneyudn_GET_NEWS_time(decide_time_begin, decide_time_end):
begin_time = datetime.datetime.today()
title = []
publish_time = []
section = []
body = []
source = []
b_time = datetime.datetime.strptime(decide_time_begin, "%Y%m%d%H%M")
e_time = datetime.datetime.strptime(decide_time_end, "%Y%m%d%H%M")
loop_flag = False
for page in range(1, 100):
print("start collecting page {page}".format(page=page))
home_url = "https://money.udn.com/rank/newest/1001/0/" + str(page)
time.sleep(3)
try:
r = crawler_tool.url_retry(home_url)
soup = BeautifulSoup(r, "lxml")
for i in range(len(soup.select("td a"))):
url2 = soup.select("td a")[i]["href"]
html_page = crawler_tool.url_retry(url2)
soup2 = BeautifulSoup(html_page, "lxml")
r_time = datetime.datetime.strptime(
soup2.find("meta", attrs={"name": "date"})["content"],
"%Y/%m/%d %H:%M:%S")
if r_time > b_time:
continue
elif r_time < e_time:
loop_flag = True
print(
"Web Crawler has collected money_udn data from {b_time} to {e_time}"
.format(b_time=b_time, e_time=e_time))
break
else:
sub_section = soup2.select("div#nav a")[-1].string
if sub_section == "品味" or sub_section == "會員專區" or sub_section == "兩岸":
time.sleep(random.randint(1, 5))
continue
else:
print(r_time)
body.append(
crawler_tool.clean_html("".join(
str(x)
for x in soup2.select("div#article_body p "))))
publish_time.append(r_time) # time
title.append(
re.sub(
r"\s{1, }", "",
soup2.find("meta",
attrs={"property": "og:title"
})["content"].split("|")[0]))
section.append(sub_section)
source.append(soup2.select("div#nav a")[0].string)
time.sleep(0.2)
except rq.exceptions.RequestException as e2:
print("home", e2)
if loop_flag == True:
break
df = pd.DataFrame({
"Title": title,
"Time": publish_time,
"Section": section,
"Source": source,
"Body": body
}).sort_values(by=["Time"])
file_name = "D:/User/Desktop/corpus/news/temporarily/" + decide_time_begin + "_" + decide_time_end + "_moneyudn.csv"
df.to_csv(file_name, encoding="utf-8")
print("processing time:", datetime.datetime.today() - begin_time)
return df
def anue_GET_NEWS_time(decide_time_begin, decide_time_end):
dt = datetime.datetime.today() - datetime.datetime.fromtimestamp(
1611763199) # 1/27差值
dta = (dt.days + 1) * 86400 + 1611763199
dtb = str(dta - 11 * 86400 + 1)
dta = str(dta)
title = []
publish_time = []
section = []
body = []
source = []
b_time = datetime.datetime.strptime(decide_time_begin, "%Y%m%d%H%M")
e_time = datetime.datetime.strptime(decide_time_end, "%Y%m%d%H%M")
loop_flag = False
for page in range(1, 30):
print("start collecting Anue page {page}".format(page=page))
home_url = "https://api.cnyes.com/media/api/v1/newslist/category/headline?limit=30&startAt="+dtb+"&endAt="+dta+"&page="\
+ str(page)
r = crawler_tool.url_retry_json(home_url)
time.sleep(5)
for i in range(len(r["items"]["data"])):
content_url = "https://news.cnyes.com/news/id/" + str(
r["items"]["data"][i]["newsId"])
r2 = crawler_tool.url_retry(content_url)
soup = BeautifulSoup(r2, "lxml")
try:
r_time = datetime.datetime.strptime(
soup.find("time").string, "%Y/%m/%d %H:%M")
if r_time > b_time:
continue
elif r_time < e_time:
loop_flag = True
print(
"---Web Crawler has collected Anue data from {b_time} to {e_time}---"
.format(b_time=b_time, e_time=e_time))
break
else:
section.append(
soup.find("meta", attrs={
"property": "og:title"
})["content"].split("|")[-1].split("-")[-1])
title.append(
re.sub(
r"\s{1,}", "",
soup.find("meta",
attrs={"property": "og:title"
})["content"].split("|")[0]))
source.append(
soup.find("meta", attrs={
"property": "og:title"
})["content"].split("|")[-1].split("-")[0])
publish_time.append(r_time)
body.append(
crawler_tool.clean_html("".join(
str(x) for x in soup.select("div._2E8y p"))))
print("Anue:", r_time)
time.sleep(random.uniform(0, 1.5))
except:
pass
if loop_flag == True:
break
df = pd.DataFrame({
"Title": title,
"Time": publish_time,
"Section": section,
"Source": source,
"Body": body
})
file_name = "D:/User/Desktop/corpus/news/temporarily/" + decide_time_begin + "_" + decide_time_end + "_Anue.csv"
df.to_csv(file_name, encoding="utf-8")
def ctee_GET_NEWS_time_threading(decide_time_begin, decide_time_end, q):
Title = []
Publish_time = []
Section = []
Body = []
Source = []
b_time = datetime.datetime.strptime(decide_time_begin, "%Y%m%d%H%M")
e_time = datetime.datetime.strptime(decide_time_end, "%Y%m%d%H%M")
loop_flag = False
for page in range(1, 11):
print("start ctee collecting page {page}".format(page=page))
home_url = "https://m.ctee.com.tw/livenews/all/page/" + str(page)
time.sleep(5)
try:
r = crawler_tool.url_retry(home_url)
soup = BeautifulSoup(r, "lxml")
for i in range(len(soup.select("p.now-title "))):
content_url = soup.select("p.now-title ")[i].find_all(
"a")[-1]["href"]
section = soup.select("p.now-title ")[i].find("span").string
r_time = datetime.datetime.strptime(
str(b_time.year) + "/" + crawler_tool.clean_html(
str(soup.select("p.now-title ")[i].find_all("a")
[1]).split("|")[-1]), "%Y/ %m/%d %H:%M ")
if r_time > b_time:
continue
elif r_time < e_time:
loop_flag = True
print(
"collected ctee news from {b_time} to {e_time}".format(
b_time=b_time, e_time=e_time))
break
else:
r2 = crawler_tool.url_retry(content_url)
soup2 = BeautifulSoup(r2, "lxml")
if section == "生活" or section == "政治":
time.sleep(random.uniform(0, 1.5))
continue
else:
Title.append(soup2.select("span.post-title")[0].string)
Section.append(section)
Source.append("工商時報")
Publish_time.append(r_time)
Body.append(
crawler_tool.clean_html("".join(
str(x)
for x in soup2.select("div.entry-content p"))))
print("ctee:", r_time)
time.sleep(random.uniform(0, 1.5))
except rq.exceptions.RequestException as e2:
print("home", e2)
if loop_flag == True:
break
df = pd.DataFrame({
"Title": Title,
"Time": Publish_time,
"Section": Section,
"Source": Source,
"Body": Body
}).sort_values(by=["Time"])
file_name = "D:/User/Desktop/corpus/news/ctee/" + decide_time_begin + "_" + decide_time_end + "_ctee.csv"
df.to_csv(file_name, encoding="utf-8")
q.put(df)
def cna_GET_NEWS_time(decide_time_begin, decide_time_end):
title = []
publish_time = []
body = []
section = []
source = []
b_time = datetime.datetime.strptime(decide_time_begin, "%Y%m%d%H%M")
e_time = datetime.datetime.strptime(decide_time_end, "%Y%m%d%H%M")
for category in ["aie", "asc"]:
loop_flag = False
for pageidx in range(1, 6):
resp = rq.post(
"https://www.cna.com.tw/cna2018api/api/WNewsList", {
"action": "0",
"category": category,
"pageidx": pageidx,
"pagesize": "20"
})
j = json.loads(resp.content)
for i in range(len(j['ResultData']["Items"])):
r_time = datetime.datetime.strptime(
j['ResultData']["Items"][i]["CreateTime"],
"%Y/%m/%d %H:%M")
if r_time > b_time:
continue
elif r_time < e_time:
loop_flag = True
print(
"Web Crawler has collected 中央通訊社 from {b_time} to {e_time}"
.format(b_time=b_time, e_time=e_time))
break
else:
url = j['ResultData']["Items"][i]["PageUrl"]
section.append(j['ResultData']["Items"][i]["ClassName"])
title.append(
re.sub(r"\s{1, }", "",
j['ResultData']["Items"][i]["HeadLine"]))
publish_time.append(r_time)
soup = BeautifulSoup(rq.get(url).text, "lxml")
source.append("中央通訊社")
body.append("".join(
crawler_tool.clean_html(str(x))
for x in soup.select("div.paragraph p")))
print("中央通訊社:", category, r_time)
time.sleep(random.uniform(0.5, 1.5))
if loop_flag == True:
break
df = pd.DataFrame({
"Title": title,
"Time": publish_time,
"Section": section,
"Source": source,
"Body": body
})
file_name = "D:/User/Desktop/corpus/news/temporarily/" + decide_time_begin + "_" + decide_time_end + "_cna.csv"
df.to_csv(file_name, encoding="utf-8")
def rti_GET_NEWS_time_threading(decide_time_begin, decide_time_end, q):
title = []
publish_time = []
section = []
body = []
source = []
b_time = datetime.datetime.strptime(decide_time_begin, "%Y%m%d%H%M")
e_time = datetime.datetime.strptime(decide_time_end, "%Y%m%d%H%M")
#print(b_time, "\n", e_time)
loop_flag = False
for page in range(1, 100):
print("start collecting Rti page {page}".format(page=page))
home_url = "https://www.rti.org.tw/news/list/categoryId/2/page/" + str(
page)
r = crawler_tool.url_retry(home_url)
soup = BeautifulSoup(r, "lxml")
time.sleep(5)
for i in range(len(soup.select("div.main_wrapper ul a"))):
content_url = "https://www.rti.org.tw" + soup.select(
"div.main_wrapper ul a")[i]["href"]
r2 = crawler_tool.url_retry(content_url)
soup2 = BeautifulSoup(r2, "lxml")
r_time = datetime.datetime.strptime(
re.sub("[^0-9]", "",
soup2.find("li", attrs={
"class": "date"
}).string), "%Y%m%d%H%M")
if r_time > b_time:
continue
elif r_time < e_time:
loop_flag = True
print(
"Web Crawler has collected Rti data from {b_time} to {e_time}"
.format(b_time=b_time, e_time=e_time))
break
else:
section.append("財經")
title.append(
re.sub(r"\s{1,}", "",
soup2.find("title").string.split("-")[0]))
source.append(soup2.find("title").string.split("-")[-1])
publish_time.append(r_time)
body.append(
crawler_tool.clean_html("".join(
str(x) for x in soup2.select("article p"))))
print("Rti:", r_time)
time.sleep(random.uniform(0, 2))
if loop_flag == True:
break
df = pd.DataFrame({
"Title": title,
"Time": publish_time,
"Section": section,
"Source": source,
"Body": body
})
file_name = "D:/User/Desktop/corpus/news/rti/" + decide_time_begin + "_" + decide_time_end + "_rti.csv"
df.to_csv(file_name, encoding="utf-8")
q.put(df)
