Upload app.py

app.py

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+# -*- coding: utf-8 -*-
+"""app2.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1EcIl8KoJxnisZgC7-76wSYIyis_eRKAL
+"""
+
+# 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()
+#