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 tvbs_GET_NEWS_time_threading(decide_time_begin, decide_time_end, q):
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")
r = crawler_tool.url_retry("https://news.tvbs.com.tw/money")
soup = BeautifulSoup(r, "lxml")
for i in range(len(soup.select("div.content_center_contxt_box_news a"))):
url = "https://news.tvbs.com.tw" + soup.select(
"div.content_center_contxt_box_news a")[i]["href"]
r2 = crawler_tool.url_retry(url)
soup2 = BeautifulSoup(r2, "lxml")
try:
j = json.loads(
soup2.find("script", attrs={
"type": "application/ld+json"
}).string)
r_time = datetime.datetime.strptime(j["datePublished"],
"%Y/%m/%d %H:%M")
if r_time > b_time:
continue
elif r_time < e_time:
print(
"Web Crawler has collected TVBS from {b_time} to {e_time}"
.format(b_time=b_time, e_time=e_time))
break
else:
title.append(
re.sub(r"\s{1, }", "", j["headline"].split("│")[0]))
publish_time.append(r_time)
body.append(j["articleBody"])
section.append(j["articleSection"])
source.append("TVBS新聞網")
print("TVBS新聞網:", r_time)
time.sleep(random.uniform(0.5, 1.5))
except json.decoder.JSONDecodeError:
print("json.decoder.JSONDecodeError")
df = pd.DataFrame({
"Title": title,
"Time": publish_time,
"Section": section,
"Source": source,
"Body": body
})
file_name = "D:/User/Desktop/corpus/news/tvbs/" + decide_time_begin + "_" + decide_time_end + "_tvbs.csv"
df.to_csv(file_name, encoding="utf-8")
q.put(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 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)
