Nov 12, 2020
diff --git a/scripts/35_scrape_hacktoberfest_events.py b/scripts/35_scrape_hacktoberfest_events.py
 import requests
 import pandas
 from bs4 import BeautifulSoup

 # creating a soup object with html we got from the response
 url = "https://hacktoberfest.digitalocean.com/events"
 response = requests.get(url)
 html = response.text
 soup = BeautifulSoup(html)

 # creating array of datas
 all_names = []
 all_locations = []
 all_dates = []
 all_time_zones = []
 all_urls = []

 # iterating on all the "tr" elements.
 for tr_element in soup.findAll("tr", attrs={"class": "past"}):

    # for each tr element we find the proper value and add it to its proper array
    name_element = tr_element.find("td", attrs={"class": "event_name"})
    name = name_element.text.strip()
    all_names.append(name)

    location_element = tr_element.find("td", attrs={"class": "location"})
    location = location_element.text.strip()
    all_locations.append(location)

    date_element = tr_element.find("td", attrs={"data-label": "date"})
    date = date_element.text.strip()
    all_dates.append(date)

    time_zone_element = tr_element.find("td", attrs={"data-label": "zone"})
    time_zone = time_zone_element.text.strip()
    all_time_zones.append(time_zone)

    url_element = tr_element.find("a", attrs={"class": "emphasis"})
    url = url_element['href']
    all_urls.append(url)

 # setting up our Comma Seperated Values
 csv_name = "events.csv"
 csv_structure = {
    "Name": all_names,
    "Location": all_locations,
    "Date": all_dates,
    "Time Zone": all_time_zones,
    "URL": all_urls,
 }
 # Creating a csv
 dataFrame = pandas.DataFrame(csv_structure)
 dataFrame.to_csv(csv_name, index=False, encoding='utf-8')
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,55 @@
		import requests
		import pandas
		from bs4 import BeautifulSoup

		# creating a soup object with html we got from the response
		url = "https://hacktoberfest.digitalocean.com/events"
		response = requests.get(url)
		html = response.text
		soup = BeautifulSoup(html)

		# creating array of datas
		all_names = []
		all_locations = []
		all_dates = []
		all_time_zones = []
		all_urls = []

		# iterating on all the "tr" elements.
		for tr_element in soup.findAll("tr", attrs={"class": "past"}):

		# for each tr element we find the proper value and add it to its proper array
		name_element = tr_element.find("td", attrs={"class": "event_name"})
		name = name_element.text.strip()
		all_names.append(name)

		location_element = tr_element.find("td", attrs={"class": "location"})
		location = location_element.text.strip()
		all_locations.append(location)

		date_element = tr_element.find("td", attrs={"data-label": "date"})
		date = date_element.text.strip()
		all_dates.append(date)

		time_zone_element = tr_element.find("td", attrs={"data-label": "zone"})
		time_zone = time_zone_element.text.strip()
		all_time_zones.append(time_zone)

		url_element = tr_element.find("a", attrs={"class": "emphasis"})
		url = url_element['href']
		all_urls.append(url)

		# setting up our Comma Seperated Values
		csv_name = "events.csv"
		csv_structure = {
		"Name": all_names,
		"Location": all_locations,
		"Date": all_dates,
		"Time Zone": all_time_zones,
		"URL": all_urls,
		}
		# Creating a csv
		dataFrame = pandas.DataFrame(csv_structure)
		dataFrame.to_csv(csv_name, index=False, encoding='utf-8')