From 0cae8252c7f6c08a025304f8f16bc04f6fb7170a Mon Sep 17 00:00:00 2001
From: Paul Sin <jiyoungsin97@gmail.com>
Date: Thu, 12 Nov 2020 15:22:19 -0500
Subject: [PATCH] Scrape Hacktoberfest Events 2020 fixes#16

---
 scripts/35_scrape_hacktoberfest_events.py | 55 +++++++++++++++++++++++
 1 file changed, 55 insertions(+)
 create mode 100644 scripts/35_scrape_hacktoberfest_events.py

diff --git a/scripts/35_scrape_hacktoberfest_events.py b/scripts/35_scrape_hacktoberfest_events.py
new file mode 100644
index 0000000..00bbfcd
--- /dev/null
+++ b/scripts/35_scrape_hacktoberfest_events.py
@@ -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')
+
+