Delete app.py

app.py

@@ -1,168 +0,0 @@
-# -*- coding: utf-8 -*-
-"""app1
-
-Automatically generated by Colab.
-
-Original file is located at
-    https://colab.research.google.com/drive/1-gnGd0dCkJpDPuHmih9Ev8b0E_mP0swv
-"""
-
-! pip install streamlit
-
-! pip install pypdf2
-
-# Commented out IPython magic to ensure Python compatibility.
-# %%writefile app.py
-# import streamlit as st
-# import PyPDF2
-# import re
-# import csv
-# import base64
-# import os  # Import the os module for file operations
-# 
-# def extract_data_from_pdf(pdf_path):
-#     data_list = []
-#     with open(pdf_path, "rb") as file:
-#         reader = PyPDF2.PdfReader(file)
-#         for page_num in range(2, len(reader.pages)):
-#             single_page = reader.pages[page_num].extract_text()
-#             data = singlePageData(single_page)
-#             data_list.append(data)
-#     return data_list
-# 
-# def singlePageData(singlePage):
-#     seat_no_pattern = re.compile(r"Seat No:\s*([^\s]+)")
-#     seat_match = seat_no_pattern.search(singlePage)
-#     seat_no = seat_match.group(1) if seat_match else ""
-# 
-#     prn_no_pattern = re.compile(r"PRN:\s*(\d+)")
-#     prn_no_match = prn_no_pattern.search(singlePage)
-#     prn_no = prn_no_match.group(1) if prn_no_match else ""
-# 
-#     name_pattern = re.compile(r"Name:\s*([^\n]+)")
-#     name_match = name_pattern.search(singlePage)
-#     name = name_match.group(1).strip() if name_match else ""
-# 
-#     sem3_data = semData(singlePage, 3)
-#     sem4_data = semData(singlePage, 4)
-# 
-#     overall_status_pattern = re.compile(r"\|Status:\s*(\w+)\s*\|C")
-#     overall_status_match = overall_status_pattern.search(singlePage)
-#     overall_status = overall_status_match.group(1) if overall_status_match else ""
-# 
-#     percentage_match = re.compile(r"\|Percentage:\s*(\d+\.\d+)\s*\%").search(singlePage)
-#     percentage = percentage_match.group(1) if percentage_match else ""
-# 
-#     return {
-#         "Exam_Seat_No": seat_no,
-#         "PRN_No": prn_no,
-#         "Name": name,
-#         "Sem3": sem3_data,
-#         "Sem4": sem4_data,
-#         "Status": overall_status,
-#         "Percentage": percentage,
-#     }
-# 
-# def semData(singlePage, sem):
-#     data = {}
-#     subject_pattern = re.compile(fr"BTN06{sem}\d+\s*\|\s*(\S+)\s*\|\s*\S+\s*\|\s*\S+\s*\|\s*\S+\s*\|\s*(\d+)\s*\|\s*(\d+)")
-#     matches = subject_pattern.findall(singlePage)
-#     for match in matches:
-#         subject_code = match[0]
-#         ese_marks = match[1]
-#         ise_marks = match[2]
-#         total_marks = str(int(ese_marks) + int(ise_marks))
-#         data[subject_code] = {
-#             "ESE": ese_marks,
-#             "ISE": ise_marks,
-#             "Total": total_marks
-#         }
-#     return data
-# 
-# def write_data_to_csv(data_list, output_path):
-#     fieldnames = [
-#         "Exam_Seat_No", "PRN_No", "Name",
-#         "Sem3_Subject", "Sem3_ESE", "Sem3_ISE", "Sem3_Total",
-#         "Sem4_Subject", "Sem4_ESE", "Sem4_ISE", "Sem4_Total",
-#         "Status", "Percentage"
-#     ]
-# 
-#     with open(output_path, "w", newline="") as csvfile:
-#         writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
-#         writer.writeheader()
-# 
-#         for student in data_list:
-#             sem3_data = student["Sem3"]
-#             sem4_data = student["Sem4"]
-# 
-#             for subject_code, sem3_marks in sem3_data.items():
-#                 sem4_marks = sem4_data.get(subject_code, {"ESE": "", "ISE": "", "Total": ""})
-# 
-#                 writer.writerow({
-#                     "Exam_Seat_No": student["Exam_Seat_No"],
-#                     "PRN_No": student["PRN_No"],
-#                     "Name": student["Name"],
-#                     "Sem3_Subject": subject_code,
-#                     "Sem3_ESE": sem3_marks["ESE"],
-#                     "Sem3_ISE": sem3_marks["ISE"],
-#                     "Sem3_Total": sem3_marks["Total"],
-#                     "Sem4_Subject": subject_code,
-#                     "Sem4_ESE": sem4_marks["ESE"],
-#                     "Sem4_ISE": sem4_marks["ISE"],
-#                     "Sem4_Total": sem4_marks["Total"],
-#                     "Status": student["Status"],
-#                     "Percentage": student["Percentage"]
-#                 })
-# 
-# def main():
-#     st.title("PDF to CSV Converter")
-# 
-#     # File upload section
-#     uploaded_file = st.file_uploader("Upload a PDF file", type="pdf")
-# 
-#     if uploaded_file is not None:
-#         # Save the uploaded PDF file to a temporary location
-#         input_pdf_path = save_uploaded_file(uploaded_file)
-# 
-#         try:
-#             # Extract data from the PDF
-#             data_list = extract_data_from_pdf(input_pdf_path)
-# 
-#             # Save extracted data to CSV
-#             output_csv_path = "/tmp/output.csv"
-#             write_data_to_csv(data_list, output_csv_path)
-# 
-#             # Provide download link for the CSV file
-#             st.success("PDF successfully processed!")
-#             st.markdown(get_binary_file_downloader_html(output_csv_path, "CSV"), unsafe_allow_html=True)
-# 
-#         except Exception as e:
-#             st.error(f"Error encountered during PDF extraction: {str(e)}")
-# 
-# def save_uploaded_file(uploaded_file):
-#     # Save the uploaded PDF file to a temporary location
-#     temp_dir = "/tmp/pdf_converter"
-#     os.makedirs(temp_dir, exist_ok=True)
-#     input_pdf_path = os.path.join(temp_dir, "input.pdf")
-#     with open(input_pdf_path, "wb") as f:
-#         f.write(uploaded_file.read())
-#     return input_pdf_path
-# 
-# def get_binary_file_downloader_html(bin_file, file_label='File'):
-#     # Generate download link for the CSV file
-#     with open(bin_file, 'rb') as f:
-#         data = f.read()
-#     b64 = base64.b64encode(data).decode()
-#     href = f'<a href="data:application/octet-stream;base64,{b64}" download="{os.path.basename(bin_file)}">Download {file_label}</a>'
-#     return href
-# 
-# if __name__ == "__main__":
-#     main()
-#
-
-!npm install localtunnel
-
-!streamlit run app.py &>/content/logs.txt &
-
-!npx localtunnel --port 8501 & curl ipv4.icanhazip.com
-