I am trying to extract the balance sheet for an example ticker "MSFT" (Microsoft) from Yahoo Finance.
Using Selenium to click on the button "Expand All" before any scraping is done. This part seems to work.
By the way, when the Chrome web driver is launched, I manually click on the button(s) to accept or reject cookies. In a later step, I plan to add some more code so that this part is also automated. My question is though not on this one now.
Below is how the code currently looks like.
# for scraping the balance sheet from Yahoo Finance
import pandas as pd
import requests
from datetime import datetime
from bs4 import BeautifulSoup
# importing selenium to click on the "Expand All" button before scraping the financial statements
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
def get_balance_sheet_from_yfinance(ticker):
url = f"https://finance.yahoo.com/quote/{ticker}/balance-sheet?p={ticker}"
options = Options()
options.add_argument("start-maximized")
driver = webdriver.Chrome(chrome_options=options)
driver.get(url)
WebDriverWait(driver, 3600).until(EC.element_to_be_clickable((
By.XPATH, "//section[#data-test='qsp-financial']//span[text()='Expand All']"))).click()
#content whole page in html format
soup = BeautifulSoup(driver.page_source, 'html.parser')
# get the column headers (i.e. 'Breakdown' row)
div = soup.find_all('div', attrs={'class': 'D(tbhg)'})
if len(div) < 1:
print("Fail to retrieve table column header")
exit(0)
# get the list of columns from the column headers
col = []
for h in div[0].find_all('span'):
text = h.get_text()
if text != "Breakdown":
col.append(datetime.strptime(text, "%m/%d/%Y"))
df = pd.DataFrame(columns=col)
# the following code returns an empty list for index (why?)
# and values in a list that need actually be in a DataFrame
idx = []
for div in soup.find_all('div', attrs={'data-test': 'fin-row'}):
for h in div.find_all('title'):
text = h.get_text()
idx.append(text)
val = []
for div in soup.find_all('div', attrs={'data-test': 'fin-col'}):
for h in div.find_all('span'):
num = int(h.get_text().replace(",", "")) * 1000
val.append(num)
# if the above part is commented out and this block is used instead
# the following code manages to work well until the row "Cash Equivalents"
# that is because there are no entries for years 2020 and 2019 on this row
""" for div in soup.find_all('div', attrs={'data-test': 'fin-row'}):
i = 0
idx = ""
val = []
for h in div.find_all('span'):
if i % 5 == 0:
idx = h.get_text()
else:
num = int(h.get_text().replace(",", "")) * 1000
val.append(num)
i += 1
row = pd.DataFrame([val], columns=col, index=[idx])
df = pd.concat([df, row], axis=0) """
return idx, val
get_balance_sheet_from_yfinance("MSFT")
I could not get the data scraped from the expanded table in a usable tabular format. Instead, the function above returns what I managed to scrape from the webpage. There are some additional comments in the code.
Could you give me some ideas on how to properly extract the data and put it into a DataFrame object with index which should be the text under the "Breakdown" column? Basically, the DataFrame should look like the snapshot below, with what is under the first column in there being the index.
balance-sheet-df
i've spent a long time on this, hope it helps, basically your function now returns a dataFrame with the following formatting:
2022-06-29 2021-06-29 2020-06-29 2019-06-29
Total Assets 364,840,000 333,779,000 301,311,000 286,556,000
Current Assets 169,684,000 184,406,000 181,915,000 175,552,000
Cash, Cash Equivalents & Short Term Investments 104,749,000 130,334,000 136,527,000 133,819,000
Cash And Cash Equivalents 13,931,000 14,224,000 13,576,000 11,356,000
Cash 8,258,000 7,272,000 - -
... ... ... ... ...
Tangible Book Value 87,720,000 84,477,000 67,915,000 52,554,000
Total Debt 61,270,000 67,775,000 70,998,000 78,366,000
Net Debt 35,850,000 43,922,000 49,751,000 60,822,000
Share Issued 7,464,000 7,519,000 7,571,000 7,643,000
Ordinary Shares Number 7,464,000 7,519,000 7,571,000 7,643,000
and here's the final code:
# for scraping the balance sheet from Yahoo Finance
from time import sleep
import pandas as pd
import requests
from datetime import datetime
from bs4 import BeautifulSoup
# importing selenium to click on the "Expand All" button before scraping the financial statements
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
def get_balance_sheet_from_yfinance(ticker):
url = f"https://finance.yahoo.com/quote/{ticker}/balance-sheet?p={ticker}"
options = Options()
options.add_argument("start-maximized")
driver = webdriver.Chrome(chrome_options=options)
driver.get(url)
WebDriverWait(driver, 3600).until(EC.element_to_be_clickable((
By.XPATH, "//section[#data-test='qsp-financial']//span[text()='Expand All']"))).click()
# content whole page in html format
soup = BeautifulSoup(driver.page_source, 'html.parser')
# get the column headers (i.e. 'Breakdown' row)
div = soup.find_all('div', attrs={'class': 'D(tbhg)'})
if len(div) < 1:
print("Fail to retrieve table column header")
exit(0)
# get the list of columns from the column headers
col = []
for h in div[0].find_all('span'):
text = h.get_text()
if text != "Breakdown":
col.append(datetime.strptime(text, "%m/%d/%Y"))
row = {}
for div in soup.find_all('div', attrs={'data-test': 'fin-row'}):
head = div.find('span').get_text()
i = 4
for h in div.find_all('span'):
if h.get_text().replace(',', '').isdigit() or h.get_text()[0] == '-':
row[head].append(h.get_text())
i += 1
else:
while i < 4:
row[head].append('')
i += 1
else:
head = h.get_text()
row[head] = []
i = 0
for k, v in row.items():
while len(v) < 4:
row[k].append('-')
df = pd.DataFrame(columns=col, index=row.keys(), data=row.values())
print(df)
return df
get_balance_sheet_from_yfinance("MSFT")
i've removed some od the unused code and added a new scrapping method, but i have kept your method of getting the dates of all the columns.
if you have any questions don't hesitate to ask in the comments.
Related
My scraper is calling the website and hitting each of the 44 pages and creating a csv file but the csv file is empty. I am returning after each of the functions and saving the data to a csv at the end of the scraper.
Can anyone see what is wrong with my code?
Code:
import pandas,requests,bs4,time
from seleniumwire import webdriver
from webdriver_manager.firefox import GeckoDriverManager
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
import datetime
TODAY = datetime.datetime.today().strftime("%Y%m%d")
SAVE_FILENAME = "/Users/180284/jupyter-1.0.0/pssi_jobs-"+TODAY+".csv"
driver = webdriver.Chrome('~/Desktop/chromedriver_mac64')
driver.implicitly_wait(30)
URL_BASE = "https://jobs.pssi.com/us/en/search-resultskeywords=%22food%20safety%20team%20member%22&s=1"
MAX_PAGE = 44
HEADERS = {
'From': 'myemail'
}
def interceptor(request):
del request.headers['From']
request.headers['From'] = HEADERS["From"]
driver.request_interceptor = interceptor
def parse_job_post_div(div_html):
soup = bs4.BeautifulSoup(div_html)
job_ls = soup.findAll("div",{"class":"information"})
job_data = []
for job in job_ls:
job_listing = job.find("div",{"class":"information"}).get_text(separator=", ").strip()
title = job.find("span",{"role":"heading"}).get_text(separator=", ").strip()
job_location = job.find("p",{"class":"job-info"}).get_text(separator=", ").strip()
new_row = {"job_listing":job,"title":title,"job_location":job_location}
job_data.append(new_row)
return job_data
def get_data(wd):
job_postings = driver.find_element(By.CLASS_NAME, "information")
html = job_postings.get_attribute("innerHTML")
parsed = parse_job_post_div(html)
return pandas.DataFrame(parsed)
def process_page(url):
driver.get(url)
master_data = []
i = 0
while True:
df = get_data(driver)
master_data.append(df)
if i == (MAX_PAGE - 1):
break
driver.find_element(By.XPATH, "//span[#class='icon icon-arrow-right']").click()
time.sleep(10)
print(i)
i+=1
return pandas.concat(master_data,ignore_index=True)
data = process_page(URL_BASE)
data.to_csv(SAVE_FILENAME)
`
I have tried the above code.
The first problem I found in your code is that the job_ls is an empty list, i.e. soup.findAll("div",{"class":"information"}) doesn't find anything.
Moreover, job_postings contains only one webelement (i.e. the first job of the list) instead of all 10 jobs shown in the page, that's because you used .find_element instead of .find_elements. As a result of these and other problems, process_page(URL_BASE) returns an empty dataframe.
In this case you can speed up the process and use less code using directly selenium instead of bs4
driver.get(URL_BASE)
driver.implicitly_wait(30)
MAX_PAGE = 4
titles, locations, descriptions = [], [], []
for i in range(MAX_PAGE):
print('current page:',i+1,end='\r')
titles += [title.text for title in driver.find_elements(By.CSS_SELECTOR, '.information > span[role=heading]')]
locations += [loc.text.replace('\n',', ') for loc in driver.find_elements(By.CSS_SELECTOR, '.information > p[class=job-info]')]
descriptions += [title.text for title in driver.find_elements(By.CSS_SELECTOR, '.information > p[data-ph-at-id=jobdescription-text')]
if i < MAX_PAGE-1:
driver.find_element(By.XPATH, "//span[#class='icon icon-arrow-right']").click()
else:
break
df = pandas.DataFrame({'title':titles,'location':locations,'description':descriptions})
df.to_csv(SAVE_FILENAME, index=False)
and df will be something like
I am new to web scraping, and I am trying to scrape the titles, dates, links, and contents of news articles on this website: https://www.iol.co.za/news/south-africa/eastern-cape.
The titles of the articles have different class names and heading (h) tag. I was able to scrape the dates, links, and titles using h tag. However, when I tried to store them in a pandas dataframe, I received the following errors-> ValueError: All arrays must be of the same length.
I also wrote the code to get the content of each article using the links. I got an error as well. I will thankful if I can be assisted.
I have tried different options to scrape the titles by creating a list of the different class names, but to no avail.
Please see my code below:
import sys, time
from bs4 import BeautifulSoup
import requests
import pandas as pd
from selenium import webdriver
from webdriver_manager.chrome import ChromeDriverManager
from datetime import timedelta
from selenium.common.exceptions import TimeoutException
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.wait import WebDriverWait
import re
art_title = [] # to store the titles of all news article
art_date = [] # to store the dates of all news article
art_link = [] # to store the links of all news article
pagesToGet = ['south-africa/eastern-cape']
for i in range(0, len(pagesToGet)):
print('processing page : \n')
url = 'https://www.iol.co.za' + str(pagesToGet[i])
print(url)
driver = webdriver.Chrome(ChromeDriverManager().install())
driver.maximize_window()
#time.sleep(5) # allow you to sleep your code before your retrieve the elements from the webpage. Additionally, to
# prevent the chrome driver opening a new instance for every url, open the browser outside of the loop.
# an exception might be thrown, so the code should be in a try-except block
try:
# use the browser to get the url. This is suspicious command that might blow up.
driver.get("https://www.iol.co.za/news/" +str(pagesToGet[i]))
except Exception as e: # this describes what to do if an exception is thrown
error_type, error_obj, error_info = sys.exc_info() # get the exception information
print('ERROR FOR LINK:', url) # print the link that cause the problem
print(error_type, 'Line:', error_info.tb_lineno) # print error info and line that threw the exception
continue # ignore this page. Abandon this and go back.
time.sleep(3) # Allow 3 seconds for the web page to open
# Code to scroll the screen to the end and click on more news till the 15th page before scraping all the news
k = 1
while k<=2:
scroll_pause_time = 1 # You can set your own pause time. My laptop is a bit slow so I use 1 sec
screen_height = driver.execute_script("return window.screen.height;") # get the screen height of the web
i = 1
while True:
# scroll one screen height each time
driver.execute_script("window.scrollTo(0, {screen_height}*{i});".format(screen_height=screen_height, i=i))
i += 1
time.sleep(scroll_pause_time)
# update scroll height each time after scrolled, as the scroll height can change after we scrolled the page
scroll_height = driver.execute_script("return document.body.scrollHeight;")
# Break the loop when the height we need to scroll to is larger than the total scroll height
if (screen_height) * i > scroll_height:
break
driver.find_element(By.CSS_SELECTOR, '.Articles__MoreFromButton-sc-1mrfc98-0').click()
k += 1
time.sleep(1)
soup = BeautifulSoup(driver.page_source, 'html.parser')
news = soup.find_all('article', attrs={'class': 'sc-ifAKCX'})
print(len(news))
# Getting titles, dates, and links
for j in news:
# Article title
title = j.findAll(re.compile('^h[1-6]'))
for news_title in title:
art_title.append(news_title.text)
# Article dates
dates = j.find('p', attrs={'class': 'sc-cIShpX'})
if dates is not None:
date = dates.text
split_date = date.rsplit('|', 1)[1][10:].rsplit('<', 1)[0]
art_date.append(split_date)
# Article links
address = j.find('a').get('href')
news_link = 'https://www.iol.co.za' + address
art_link.append(news_link)
df = pd.DataFrame({'Article_Title': art_title, 'Date': art_date, 'Source': art_link})
# Getting contents
new_articles = ...struggling to write the code
df['Content'] = news_articles
df.to_csv('data.csv')
driver.quit()
I think this is what you are looking for:
# Needed libs
from selenium.webdriver import ActionChains, Keys
import time
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
from selenium import webdriver
# Initialize drivver and navigate
driver = webdriver.Chrome()
driver.maximize_window()
url = 'https://www.iol.co.za/news/south-africa/eastern-cape'
wait = WebDriverWait(driver, 5)
driver.get(url)
time.sleep(3)
# take the articles
articles = wait.until(EC.presence_of_all_elements_located((By.XPATH, f"//article//*[(name() = 'h1' or name()='h2' or name()='h3' or name()='h4' or name()='h5' or name()='h6' or name()='h7') and string-length(text()) > 0]/ancestor::article")))
# For every article we take what we want
for article in articles:
header = article.find_element(By.XPATH, f".//*[name() = 'h1' or name()='h2' or name()='h3' or name()='h4' or name()='h5' or name()='h6' or name()='h7']")
print(header.get_attribute('textContent'))
author_and_date = article.find_elements(By.XPATH, f".//*[name() = 'h1' or name()='h2' or name()='h3' or name()='h4' or name()='h5' or name()='h6' or name()='h7']/following-sibling::p[1]")
if author_and_date:
print(author_and_date[0].get_attribute('textContent'))
else:
print("No author found")
link = article.find_element(By.XPATH, f".//a")
print(link.get_attribute('href'))
I placed the code of a complete and properly functioning scraping that I own. Successfully scrapes all elements on the page.
However, I would like to scrape only a small limited section of the page with the same elements as scraping. This limited section is already scraped correctly along with all elements of the page, but I would like to scrape only it and not "all + it". The link is here
There are 4 tables on the page, but I would like to scrape just one, that is the table called "Programma", ie the html section "event-summary event" or "leagues-static event-summary-leagues ". But of this section only the elements of the last round (Matchday 14). Matchday 14 only. No round 15. So obviously that with each update of the page rounds, the last round is always scraped as well.
So I would need to insert something that makes scraping understand to download only the elements (which it already owns and scrapes) of of that section and the last round.
The code is already complete and works fine, so I'm not looking for code services, but for a little hint to tell me how to limit the scraping to just the section mentioned above. Scraping is in Selenium. I would like to stick with Selenium and my code as it is already functional and complete. Thanks
import selenium
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
driver = webdriver.Firefox()
driver.get("url")
driver.implicitly_wait(12)
#driver.minimize_window()
wait = WebDriverWait(driver, 10)
all_rows = driver.find_elements(By.CSS_SELECTOR, "div[class^='event__round'],div[class^='event__match']")
current_round = '?'
for bundesliga in all_rows:
classes = bundesliga.get_attribute('class')
#print(classes)
if 'event__round' in classes:
#round = row.find_elements(By.CSS_SELECTOR, "[class^='event__round event__round--static']")
#current_round = row.text # full text `Round 20`
current_round = bundesliga.text.split(" ")[-1] # only `20` without `Round`
else:
datetime = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__time']")
#Divide la data e l'ora
date, time = datetime.text.split(" ")
date = date.rstrip('.') # right-strip to remove `.` at the end of date
team_home = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__participant event__participant--home']")
team_away = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__participant event__participant--away']")
score_home = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--home']")
score_away = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--away']")
bundesliga = [current_round, date, time, team_home.text, team_away.text, score_home.text, score_away.text]
bundesliga.append(bundesliga)
print(bundesliga)
I think all you need to do is limit all_rows variable. One way to do this is finding the tab you are looking for with text and then getting the parent elements.
import selenium
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.common.exceptions import TimeoutException, NoSuchElementException
driver = webdriver.Firefox()
driver.get("https://www.someurl/some/other/page")
driver.implicitly_wait(12)
#driver.minimize_window()
wait = WebDriverWait(driver, 10)
# all_rows = driver.find_elements(By.CSS_SELECTOR, "div[class^='event__round'],div[class^='event__match']")
############### UPDATE ####################
def parent_element(element):
return element.find_element(By.XPATH, './..')
programma_element = WebDriverWait(driver, 10).until(
EC.visibility_of_element_located((By.XPATH, "//div[text()='Programma']")))
programma_element_p1 = parent_element(programma_element)
programma_element_p2 = parent_element(programma_element_p1)
programma_element_p3 = parent_element(programma_element_p2)
all_rows = programma_element_p3.find_elements(By.CSS_SELECTOR, "div[class^='event__round'],div[class^='event__match']")
filter_rows = []
for row in all_rows:
if "event__match--last" in row.get_attribute('class'):
filter_rows.append(row)
break
else:
filter_rows.append(row)
############### UPDATE ####################
current_round = '?'
for bundesliga in filter_rows:
classes = bundesliga.get_attribute('class')
#print(classes)
if 'event__round' in classes:
#round = row.find_elements(By.CSS_SELECTOR, "[class^='event__round event__round--static']")
#current_round = row.text # full text `Round 20`
current_round = bundesliga.text.split(" ")[-1] # only `20` without `Round`
else:
datetime = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__time']")
#Divide la data e l'ora
date, time = datetime.text.split(" ")
date = date.rstrip('.') # right-strip to remove `.` at the end of date
team_home = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__participant event__participant--home']")
team_away = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__participant event__participant--away']")
# score_home = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--home']")
# score_away = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--away']")
try:
score_home = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--home']")
except (TimeoutException, NoSuchElementException):
MyObject = type('MyObject', (object,), {})
score_home = MyObject()
score_home.text = "-"
try:
score_away = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--away']")
except (TimeoutException, NoSuchElementException):
MyObject = type('MyObject', (object,), {})
score_away = MyObject()
score_away.text = "-"
bundesliga = [current_round, date, time, team_home.text, team_away.text, score_home.text, score_away.text]
bundesliga.append(bundesliga)
print(bundesliga)
Hii guys I was scraping this data and my code is working fine but I am not able to understand how to store this scraped data into a excel file and I am getting more confused after looking at others solution and answers
here is my code
import time
import pandas as pd
from selenium import webdriver
from bs4 import BeautifulSoup
from selenium.webdriver.chrome.options import Options
from urllib.parse import urljoin
import openpyxl
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
##### Web scraper for infinite scrolling page #####
driver = webdriver.Chrome(executable_path='./chromedriver.exe')
driver.get("https://www.zomato.com/ncr/south-delhi-restaurants/fast-food?rating_range=4.0-5.0&category=2")
time.sleep(10) # Allow 2 seconds for the web page to open
scroll_pause_time = 1 # You can set your own pause time. My laptop is a bit slow so I use 1 sec
screen_height = driver.execute_script("return window.screen.height;") # get the screen height of the web
i = 1
count=0
while True:
# scroll one screen height each time
driver.execute_script("window.scrollTo(0, {screen_height}*{i});".format(screen_height=screen_height, i=i))
i += 1
time.sleep(scroll_pause_time)
# update scroll height each time after scrolled, as the scroll height can change after we scrolled the page
scroll_height = driver.execute_script("return document.body.scrollHeight;")
# Break the loop when the height we need to scroll to is larger than the total scroll height
if (screen_height) * i > scroll_height:
break
page_sources= BeautifulSoup(driver.page_source, "html.parser")
title=driver.find_elements_by_xpath("//a[#class='sc-jHZirH intUsQ']")
for i in title:
count += 1
name =i.find_element_by_xpath('./div/h4')
address = i.find_element_by_xpath('./p[1]')
#data = openpyxl.load_workbook('Bakery.xlsx')
df = pd.DataFrame({"Bakery Restaurants": name,"Address":address})
print(count)
driver.close()
this is the main block of code
page_sources= BeautifulSoup(driver.page_source, "html.parser")
title=driver.find_elements_by_xpath("//a[#class='sc-jHZirH intUsQ']")
for i in title:
count += 1
name =i.find_element_by_xpath('./div/h4')
address = i.find_element_by_xpath('./p[1]')
#data = openpyxl.load_workbook('Bakery.xlsx')
df = pd.DataFrame({"Bakery Restaurants": name,"Address":address})
print(count)
driver.close()
please help me out, I am too confused ,any suggestion/solution will be appreciated
Assuming your scraping is working correctly. You need to store name and address to the excel
# scraping code
#
#
names = [] # Create lists to hold your columns
addresses = [] # Create lists to hold your columns
for i in title:
count += 1
name =i.find_element_by_xpath('./div/h4')
names.append(name)
address = i.find_element_by_xpath('./p[1]')
addresses.append(address)
df = pd.DataFrame({'Names': names, 'Addresses': addresses}) # Create a DF with the lists
with pd.ExcelWriter('output.xlsx') as writer:
df.to_excel(writer, sheet_name='Sheet1')
Note: Make sure the datatype of the scraped values is string or a type supported by pandas and excel. And not a python object.
Docs: Insert into DataFrame
DataFrame to Excel
this is my attempt and working fine
names=[]
addresses=[]
for i in title:
count += 1
name =i.find_element_by_xpath('./div/h4').text
address = i.find_element_by_xpath('./p[1]').text
names.append(name)
addresses.append(address)
df = pd.DataFrame({'Names': names, 'Addresses': addresses})
writer = pd.ExcelWriter('pandas_simple.xlsx')
df.to_excel(writer,'Sheet1')
writer.save()
I'm pretty new to web scraping and am trying to scrape backdated data from timeanddate.com and output it to a csv. I'm using Selenium to get the data table for each date.
My code:
from bs4 import BeautifulSoup
from selenium import webdriver
import csv
def getData (url, month, year):
driver = webdriver.Chrome('C:/Users/adam/Desktop/chromedriver.exe')
driver.get(url)
Data = []
soup = BeautifulSoup(driver.page_source, "lxml")
for i in driver.find_element_by_id("wt-his-select").find_elements_by_tag_name("option"):
i.click()
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['humidity'] = all_td[5].text
Data.append(dict)
fileName = "output_month="+month+"_year="+year+".csv"
keys = Data[0].keys()
with open(fileName, 'w') as result:
dictWriter = csv.DictWriter(result, keys)
dictWriter.writeheader()
dictWriter.writerows(Data)
year_num = int(input("Enter your year to collect data from: "))
month_num = 1
year = str(year_num)
for i in range (0,12):
month = str(month_num)
url = "https://www.timeanddate.com/weather/usa/new-york/historic?month="+month+"&year="+year
data = getData(url, month, year)
print (data)
month_num += 1
The table I'm trying to scrape data from is weather data and I want to get the humidity data from each day in the month.
The program cycles through the months but the output is the data for Mon, 1 Jan. Although the date changes in-browser, the same data is appended to the file each time (current output) rather than each new day being appended (desired output). I can't work out why it does this and any help fixing it would be much appreciated.
The problem is that you parse the website only once even though the site changes with each date selection. However, it is not enough to move parsing inside the for loop as it is also necessary to wait until the page is loaded before starting re-parsing.
Below is my solution. There are two things to note:
I am making use of the WebDriverWait and expected_conditions provided built-in with Selenium
I prefer finding by CSS selectors, which greatly simplifies syntax. This awesome game can help you learn them
# Necessary imports
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
def getData (url, month, year):
driver = webdriver.Chrome('C:/Users/adam/Desktop/chromedriver.exe')
driver.get(url)
wait = WebDriverWait(driver, 5);
Data = []
for opt in driver.find_elements_by_css_selector("#wt-his-select option"):
opt.click()
# wait until the table title changes to selected date
wait.until(EC.text_to_be_present_in_element((By.ID, 'wt-his-title'), opt.text))
for tr in driver.find_elements_by_css_selector('#wt-his tbody tr'):
dict = {}
dict['time'] = tr.find_element_by_tag_name('th').text.strip()
# Note that I replaced 5 with 6 as nth-of-xxx starts indexing from 1
dict['humidity'] = tr.find_element_by_tag_name('td:nth-of-type(6)').text.strip()
Data.append(dict)
# continue with csv handlers ...