BeautifulSoup:6k 条记录 - 但在解析 20 行后停止
BeautifulSoup: 6k records - but stops after parsing 20 lines
目标是快速了解欧洲的一系列免费志愿服务机会
目的是获取所有 6k 目标页面:https://europa.eu/youth/volunteering/organisation/48592 见下文 - 图像以及目标目标的解释和描述以及需要的数据。
我们获取..
https://europa.eu/youth/volunteering/organisation/50162
https://europa.eu/youth/volunteering/organisation/50163
and so forth and so forth
因为我们有 6000 多条记录 - 我承认我得到了结果。但是脚本只返回 20 条记录 - 即 20 行。
查看我目前的方法:我运行这里是这个小方法:
import requests
from bs4 import BeautifulSoup
import re
import csv
from tqdm import tqdm
first = "https://europa.eu/youth/volunteering/organisations_en?page={}"
second = "https://europa.eu/youth/volunteering/organisation/{}_en"
def catch(url):
with requests.Session() as req:
pages = []
print("Loading All IDS\n")
for item in tqdm(range(0, 347)):
r = req.get(url.format(item))
soup = BeautifulSoup(r.content, 'html.parser')
numbers = [item.get("href").split("/")[-1].split("_")[0] for item in soup.findAll(
"a", href=re.compile("^/youth/volunteering/organisation/"), class_="btn btn-default")]
pages.append(numbers)
return numbers
def parse(url):
links = catch(first)
with requests.Session() as req:
with open("Data.csv", 'w', newline="", encoding="UTF-8") as f:
writer = csv.writer(f)
writer.writerow(["Name", "Address", "Site", "Phone",
"Description", "Scope", "Rec", "Send", "PIC", "OID", "Topic"])
print("\nParsing Now... \n")
for link in tqdm(links):
r = req.get(url.format(link))
soup = BeautifulSoup(r.content, 'html.parser')
task = soup.find("section", class_="col-sm-12").contents
name = task[1].text
add = task[3].find(
"i", class_="fa fa-location-arrow fa-lg").parent.text.strip()
try:
site = task[3].find("a", class_="link-default").get("href")
except:
site = "N/A"
try:
phone = task[3].find(
"i", class_="fa fa-phone").next_element.strip()
except:
phone = "N/A"
desc = task[3].find(
"h3", class_="eyp-project-heading underline").find_next("p").text
scope = task[3].findAll("span", class_="pull-right")[1].text
rec = task[3].select("tbody td")[1].text
send = task[3].select("tbody td")[-1].text
pic = task[3].select(
"span.vertical-space")[0].text.split(" ")[1]
oid = task[3].select(
"span.vertical-space")[-1].text.split(" ")[1]
topic = [item.next_element.strip() for item in task[3].select(
"i.fa.fa-check.fa-lg")]
writer.writerow([name, add, site, phone, desc,
scope, rec, send, pic, oid, "".join(topic)])
parse(second)
但是在解析 20 个结果后停止
注意:我想要 return 页数而不是数字。
因为我想遍历页面而不是数字;但无论如何 - 如果我从 return 数字更改为 return 页 - 我没有得到更好的结果。
这里我似乎有一些错误:我猜 catch 函数中有一个奇特的错误:我们在这里 returning 数字,但我很确定这是一个错误:我们我们打算 returning 页面,这意味着当我们在另一个函数中迭代 catch(first) 的结果时,我们并没有迭代所有想要的东西。
我想我需要包括一个修复:我们需要在该函数的底部 return 页,而不是 return numbers
也就是说:因为我想遍历页面而不是数字;但无论如何 - 如果我从 return 数字更改为 return 页 - 我没有得到更好的结果。
任何想法 - 如何让解析器给出所有 6k 结果。
您可以使用此示例来解析页面:
import pandas
import requests
import pandas as pd
from bs4 import BeautifulSoup
def safe_get(to_find, what_next, if_not_found="N/A"):
if to_find:
return what_next(to_find)
return if_not_found
first_url = "https://europa.eu/youth/volunteering/organisations_en?page={}"
links = []
for page in range(0, 3): # <--- increase number of pages here
u = first_url.format(page)
soup = BeautifulSoup(requests.get(u).content, "html.parser")
for a in soup.select("h5 > a"):
links.append("https://europa.eu" + a["href"])
data = []
for l in links:
print(l)
soup = BeautifulSoup(requests.get(l).content, "html.parser")
name = safe_get(soup.select_one("h5"), lambda t: t.text)
address = safe_get(
soup.select_one(".fa-location-arrow"),
lambda t: t.parent.get_text(strip=True),
)
link = safe_get(
soup.select_one(".fa-external-link"), lambda t: t.find_next("a")["href"]
)
phone = safe_get(
soup.select_one(".fa-phone"), lambda t: t.find_next(text=True).strip()
)
desc = safe_get(
soup.select_one("h3 ~ p"),
lambda t: t.get_text(strip=True, separator="\n"),
)
scope = safe_get(
soup.select_one(".fa-asterisk"),
lambda t: t.find_next("span").get_text(strip=True),
)
receiving = safe_get(
soup.select_one('td:-soup-contains("Receiving") ~ td'),
lambda t: t.get_text(strip=True),
)
sending = safe_get(
soup.select_one('td:-soup-contains("Sending") ~ td'),
lambda t: t.get_text(strip=True),
)
pic = safe_get(
soup.find("span", text=lambda t: t and t.startswith("PIC")),
lambda t: t.text.split()[-1],
)
oid = safe_get(
soup.find("span", text=lambda t: t and t.startswith("OID")),
lambda t: t.text.split()[-1],
)
topics = ", ".join(
[t.find_next(text=True).strip() for t in soup.select("p > .fa-check")]
)
data.append(
(
name,
address,
link,
phone,
desc,
scope,
receiving,
sending,
pic,
oid,
topics,
)
)
df = pd.DataFrame(
data,
columns=[
"Name",
"Address",
"Site",
"Phone",
"Description",
"Scope",
"Rec",
"Send",
"PIC",
"OID",
"Topic",
],
)
print(df)
df.to_csv("data.csv", index=False)
创建 data.csv
(来自 Libre Office 的屏幕截图):
目标是快速了解欧洲的一系列免费志愿服务机会
目的是获取所有 6k 目标页面:https://europa.eu/youth/volunteering/organisation/48592 见下文 - 图像以及目标目标的解释和描述以及需要的数据。
我们获取..
https://europa.eu/youth/volunteering/organisation/50162
https://europa.eu/youth/volunteering/organisation/50163
and so forth and so forth
因为我们有 6000 多条记录 - 我承认我得到了结果。但是脚本只返回 20 条记录 - 即 20 行。
查看我目前的方法:我运行这里是这个小方法:
import requests
from bs4 import BeautifulSoup
import re
import csv
from tqdm import tqdm
first = "https://europa.eu/youth/volunteering/organisations_en?page={}"
second = "https://europa.eu/youth/volunteering/organisation/{}_en"
def catch(url):
with requests.Session() as req:
pages = []
print("Loading All IDS\n")
for item in tqdm(range(0, 347)):
r = req.get(url.format(item))
soup = BeautifulSoup(r.content, 'html.parser')
numbers = [item.get("href").split("/")[-1].split("_")[0] for item in soup.findAll(
"a", href=re.compile("^/youth/volunteering/organisation/"), class_="btn btn-default")]
pages.append(numbers)
return numbers
def parse(url):
links = catch(first)
with requests.Session() as req:
with open("Data.csv", 'w', newline="", encoding="UTF-8") as f:
writer = csv.writer(f)
writer.writerow(["Name", "Address", "Site", "Phone",
"Description", "Scope", "Rec", "Send", "PIC", "OID", "Topic"])
print("\nParsing Now... \n")
for link in tqdm(links):
r = req.get(url.format(link))
soup = BeautifulSoup(r.content, 'html.parser')
task = soup.find("section", class_="col-sm-12").contents
name = task[1].text
add = task[3].find(
"i", class_="fa fa-location-arrow fa-lg").parent.text.strip()
try:
site = task[3].find("a", class_="link-default").get("href")
except:
site = "N/A"
try:
phone = task[3].find(
"i", class_="fa fa-phone").next_element.strip()
except:
phone = "N/A"
desc = task[3].find(
"h3", class_="eyp-project-heading underline").find_next("p").text
scope = task[3].findAll("span", class_="pull-right")[1].text
rec = task[3].select("tbody td")[1].text
send = task[3].select("tbody td")[-1].text
pic = task[3].select(
"span.vertical-space")[0].text.split(" ")[1]
oid = task[3].select(
"span.vertical-space")[-1].text.split(" ")[1]
topic = [item.next_element.strip() for item in task[3].select(
"i.fa.fa-check.fa-lg")]
writer.writerow([name, add, site, phone, desc,
scope, rec, send, pic, oid, "".join(topic)])
parse(second)
但是在解析 20 个结果后停止
注意:我想要 return 页数而不是数字。
因为我想遍历页面而不是数字;但无论如何 - 如果我从 return 数字更改为 return 页 - 我没有得到更好的结果。
这里我似乎有一些错误:我猜 catch 函数中有一个奇特的错误:我们在这里 returning 数字,但我很确定这是一个错误:我们我们打算 returning 页面,这意味着当我们在另一个函数中迭代 catch(first) 的结果时,我们并没有迭代所有想要的东西。 我想我需要包括一个修复:我们需要在该函数的底部 return 页,而不是 return numbers
也就是说:因为我想遍历页面而不是数字;但无论如何 - 如果我从 return 数字更改为 return 页 - 我没有得到更好的结果。
任何想法 - 如何让解析器给出所有 6k 结果。
您可以使用此示例来解析页面:
import pandas
import requests
import pandas as pd
from bs4 import BeautifulSoup
def safe_get(to_find, what_next, if_not_found="N/A"):
if to_find:
return what_next(to_find)
return if_not_found
first_url = "https://europa.eu/youth/volunteering/organisations_en?page={}"
links = []
for page in range(0, 3): # <--- increase number of pages here
u = first_url.format(page)
soup = BeautifulSoup(requests.get(u).content, "html.parser")
for a in soup.select("h5 > a"):
links.append("https://europa.eu" + a["href"])
data = []
for l in links:
print(l)
soup = BeautifulSoup(requests.get(l).content, "html.parser")
name = safe_get(soup.select_one("h5"), lambda t: t.text)
address = safe_get(
soup.select_one(".fa-location-arrow"),
lambda t: t.parent.get_text(strip=True),
)
link = safe_get(
soup.select_one(".fa-external-link"), lambda t: t.find_next("a")["href"]
)
phone = safe_get(
soup.select_one(".fa-phone"), lambda t: t.find_next(text=True).strip()
)
desc = safe_get(
soup.select_one("h3 ~ p"),
lambda t: t.get_text(strip=True, separator="\n"),
)
scope = safe_get(
soup.select_one(".fa-asterisk"),
lambda t: t.find_next("span").get_text(strip=True),
)
receiving = safe_get(
soup.select_one('td:-soup-contains("Receiving") ~ td'),
lambda t: t.get_text(strip=True),
)
sending = safe_get(
soup.select_one('td:-soup-contains("Sending") ~ td'),
lambda t: t.get_text(strip=True),
)
pic = safe_get(
soup.find("span", text=lambda t: t and t.startswith("PIC")),
lambda t: t.text.split()[-1],
)
oid = safe_get(
soup.find("span", text=lambda t: t and t.startswith("OID")),
lambda t: t.text.split()[-1],
)
topics = ", ".join(
[t.find_next(text=True).strip() for t in soup.select("p > .fa-check")]
)
data.append(
(
name,
address,
link,
phone,
desc,
scope,
receiving,
sending,
pic,
oid,
topics,
)
)
df = pd.DataFrame(
data,
columns=[
"Name",
"Address",
"Site",
"Phone",
"Description",
"Scope",
"Rec",
"Send",
"PIC",
"OID",
"Topic",
],
)
print(df)
df.to_csv("data.csv", index=False)
创建 data.csv
(来自 Libre Office 的屏幕截图):