问题
I want to get the historical hourly weather data from https://www.timeanddate.com/
This is the website link:https://www.timeanddate.com/weather/usa/dayton/historic?month=2&year=2016 - Here I am selecting February and 2016, and the result will appear in the bottom of the page.
I used the following steps:https://stackoverflow.com/a/47280970/9341589
and it is working perfectly on the "first day of each month", I want to parse all the month, and if it is possible all the year.
below the code I am using (to parse March 1, 2016):
from urllib.request import urlopen
from bs4 import BeautifulSoup
url = "https://www.timeanddate.com/weather/usa/dayton/historic?month=3&year=2016"
page = urlopen(url)
soup = BeautifulSoup(page, "html.parser")
Data = []
table = soup.find('table', attrs={'id':'wt-his'})
for tr in table.find('tbody').find_all('tr'):
dict = {}
dict['time'] = tr.find('th').text.strip()
all_td = tr.find_all('td')
dict['temp'] = all_td[1].text
dict['weather'] = all_td[2].text
dict['wind'] = all_td[3].text
arrow = all_td[4].text
dict['humidity'] = all_td[5].text
dict['barometer'] = all_td[6].text
dict['visibility'] = all_td[7].text
Data.append(dict)
this is the result for March 1:
This is because the website "url", the link only include the month and year, and to change the days, for instance, from Feb1 to Feb 3, the tab is shown in the pic attached needed to be used:
回答1:
You can iterate over the table elements (tr, th, and td) for a single page:
import requests, re, typing
from bs4 import BeautifulSoup as soup
import contextlib
def _remove(d:list) -> list:
return list(filter(None, [re.sub('\xa0', '', b) for b in d]))
@contextlib.contextmanager
def get_weather_data(url:str, by_url = True) -> typing.Generator[dict, None, None]:
d = soup(requests.get(url).text if by_url else url, 'html.parser')
_table = d.find('table', {'id':'wt-his'})
_data = [[[i.text for i in c.find_all('th')], *[i.text for i in c.find_all('td')]] for c in _table.find_all('tr')]
[h1], [h2], *data, _ = _data
_h2 = _remove(h2)
yield {tuple(_remove(h1)):[dict(zip(_h2, _remove([a, *i]))) for [[a], *i] in data]}
with get_weather_data('https://www.timeanddate.com/weather/usa/dayton/historic?month=2&year=2016') as weather:
print(weather)
Output:
{('Conditions', 'Comfort'): [{'Time': '12:58 amMon, Feb 1', 'Temp': '50°F', 'Weather': 'Light rain. Mostly cloudy.', 'Wind': '13 mph', 'Humidity': '↑', 'Barometer': '88%', 'Visibility': '29.79 "Hg'}, {'Time': '1:58 am', 'Temp': '46°F', 'Weather': 'Mostly cloudy.', 'Wind': '12 mph', 'Humidity': '↑', 'Barometer': '83%', 'Visibility': '29.82 "Hg'}, {'Time': '2:58 am', 'Temp': '43°F', 'Weather': 'Mostly cloudy.', 'Wind': '14 mph', 'Humidity': '↑', 'Barometer': '85%', 'Visibility': '29.87 "Hg'}, {'Time': '3:58 am', 'Temp': '42°F', 'Weather': 'Mostly cloudy.', 'Wind': '10 mph', 'Humidity': '↑', 'Barometer': '83%', 'Visibility': '29.89 "Hg'}, {'Time': '4:58 am', 'Temp': '41°F', 'Weather': 'Mostly cloudy.', 'Wind': '10 mph', 'Humidity': '↑', 'Barometer': '82%', 'Visibility': '29.91 "Hg'}, {'Time': '5:58 am', 'Temp': '39°F', 'Weather': 'Mostly cloudy.', 'Wind': '8 mph', 'Humidity': '↑', 'Barometer': '83%', 'Visibility': '29.93 "Hg'}, {'Time': '6:58 am', 'Temp': '38°F', 'Weather': 'Partly cloudy.', 'Wind': '5 mph', 'Humidity': '↑', 'Barometer': '82%', 'Visibility': '29.96 "Hg'}, {'Time': '7:58 am', 'Temp': '38°F', 'Weather': 'Partly sunny.', 'Wind': '5 mph', 'Humidity': '↑', 'Barometer': '80%', 'Visibility': '29.99 "Hg'}, {'Time': '8:58 am', 'Temp': '38°F', 'Weather': 'Overcast.', 'Wind': '5 mph', 'Humidity': '↑', 'Barometer': '78%', 'Visibility': '30.01 "Hg'}, {'Time': '9:58 am', 'Temp': '40°F', 'Weather': 'Broken clouds.', 'Wind': '7 mph', 'Humidity': '↑', 'Barometer': 'N/A', 'Visibility': '30.01 "Hg'}, {'Time': '10:58 am', 'Temp': '41°F', 'Weather': 'Broken clouds.', 'Wind': '1 mph', 'Humidity': '↑', 'Barometer': '72%', 'Visibility': '30.02 "Hg'}, {'Time': '11:58 am', 'Temp': '41°F', 'Weather': 'Partly sunny.', 'Wind': '2 mph', 'Humidity': '↑', 'Barometer': '70%', 'Visibility': '30.04 "Hg'}, {'Time': '12:58 pm', 'Temp': '42°F', 'Weather': 'Scattered clouds.', 'Wind': '2 mph', 'Humidity': '↑', 'Barometer': '69%', 'Visibility': '30.04 "Hg'}, {'Time': '1:58 pm', 'Temp': '43°F', 'Weather': 'Partly sunny.', 'Wind': '3 mph', 'Humidity': '↑', 'Barometer': '65%', 'Visibility': '30.03 "Hg'}, {'Time': '2:58 pm', 'Temp': '44°F', 'Weather': 'Partly sunny.', 'Wind': 'No wind', 'Humidity': '↑', 'Barometer': '62%', 'Visibility': '30.02 "Hg'}, {'Time': '3:58 pm', 'Temp': '46°F', 'Weather': 'Passing clouds.', 'Wind': '6 mph', 'Humidity': '↑', 'Barometer': '58%', 'Visibility': '30.03 "Hg'}, {'Time': '4:58 pm', 'Temp': '46°F', 'Weather': 'Sunny.', 'Wind': '6 mph', 'Humidity': '↑', 'Barometer': '57%', 'Visibility': '30.04 "Hg'}, {'Time': '5:58 pm', 'Temp': '43°F', 'Weather': 'Clear.', 'Wind': '3 mph', 'Humidity': '↑', 'Barometer': '65%', 'Visibility': '30.06 "Hg'}, {'Time': '6:58 pm', 'Temp': '39°F', 'Weather': 'Clear.', 'Wind': '1 mph', 'Humidity': '↑', 'Barometer': '71%', 'Visibility': '30.09 "Hg'}, {'Time': '7:58 pm', 'Temp': '35°F', 'Weather': 'Clear.', 'Wind': '1 mph', 'Humidity': '↑', 'Barometer': '79%', 'Visibility': '30.11 "Hg'}, {'Time': '8:58 pm', 'Temp': '32°F', 'Weather': 'Clear.', 'Wind': 'No wind', 'Humidity': '↑', 'Barometer': '85%', 'Visibility': '30.13 "Hg'}, {'Time': '9:58 pm', 'Temp': '30°F', 'Weather': 'Clear.', 'Wind': 'No wind', 'Humidity': '↑', 'Barometer': '91%', 'Visibility': '30.14 "Hg'}, {'Time': '10:58 pm', 'Temp': '28°F', 'Weather': 'Clear.', 'Wind': '5 mph', 'Humidity': '↑', 'Barometer': '93%', 'Visibility': '30.14 "Hg'}, {'Time': '11:58 pm', 'Temp': '29°F', 'Weather': 'Clear.', 'Wind': 'No wind', 'Humidity': '↑', 'Barometer': '90%', 'Visibility': '30.13 "Hg'}]}
However, in order to scrape the data for all days in the desired month, selenium must be used, as the site dynamically updates the DOM via a request to the backend:
from selenium import webdriver
d = webdriver.Chrome('/Path/to/chromedriver')
d.get('https://www.timeanddate.com/weather/usa/dayton/historic?month=2&year=2016')
_d = {}
for i in d.find_element_by_id('wt-his-select').find_elements_by_tag_name('option'):
i.click()
with get_weather_data(d.page_source, False) as weather:
_d[i.text] = weather
Edit: to iterate over the full data results, use dict.items:
for a, b in _d.items():
pass #do something with a and b
回答2:
Using the developer tools in chrome, it looks like you can search for and click a link with text first_three_letters_of_month day using driver.find_element_by_link_text(date_here).click()
来源：https://stackoverflow.com/questions/51756775/scraping-table-from-website-timeanddate-com