Merge pull request #159 from RoopakMallik/web_scrapping_bot

Web scrapping Bot

Excel_Automation_Python/main.py

@@ -0,0 +1,56 @@
+from openpyxl import Workbook, load_workbook
+from openpyxl.utils import get_column_letter
+from openpyxl.styles import Font
+
+data = {
+    "James": {
+        "English": 65,
+        "Physics": 78,
+        "Computer": 98,
+        "History": 89
+    },
+    "Rhea": {
+        "English": 55,
+        "Physics": 77,
+        "Computer": 87,
+        "History": 95
+    },
+    "Harsh": {
+        "English": 100,
+        "Physics": 45,
+        "Computer": 75,
+        "History": 92
+    },
+    "Suman": {
+        "English": 30,
+        "Physics": 25,
+        "Computer": 45,
+        "History": 100
+    },
+    "Ryan": {
+        "English": 90,
+        "Physics": 100,
+        "Computer": 92,
+        "History": 60
+    }
+}
+
+wb = Workbook()
+ws = wb.active
+ws.title = "Student Marks"
+
+headings = ['Name'] + list(data['James'].keys())
+ws.append(headings)
+
+for person in data:
+    marks = list(data[person].values())
+    ws.append([person] + marks)
+
+for col in range(2, len(data['James']) + 2):
+    char = get_column_letter(col)
+    ws[char + "7"] = f"=SUM({char + '2'}:{char + '6'})/{len(data)}"
+
+for col in range(1, 6):
+    ws[get_column_letter(col) + '1'].font = Font(bold=True, color="0099CCFF")
+
+wb.save("StudentMarks.xlsx")

Web Scrapper Bot/web_scrapping_bot.py

@@ -0,0 +1,37 @@
+# importing the libraries and modules required
+import requests
+from bs4 import BeautifulSoup
+from datetime import datetime
+import time
+
+while(True):
+	now = datetime.now()
+
+	# time of web-scrapping
+	current_time = now.strftime("%H:%M:%S")
+	print(f'At time : {current_time} IST')
+
+	response = requests.get('https://coinmarketcap.com/')
+	text = response.text
+	html_data = BeautifulSoup(text, 'html.parser')
+	headings = html_data.find_all('tr')[0]
+	headings_list = []
+	for x in headings:
+		headings_list.append(x.text)
+	headings_list = headings_list[:10]
+
+	data = []
+
+	for x in range(1, 6):
+		row = html_data.find_all('tr')[x]
+		column_value = row.find_all('td')
+		dict = {}
+
+		for i in range(10):
+			dict[headings_list[i]] = column_value[i].text
+		data.append(dict)
+
+	for values in data:
+		print(values)
+		print('')
+	time.sleep(600)