How to extract text from multiple pdf in a location with specific line and store in Excel?

I have 100 pdf stored in a location and I want to extract text from them and store in excel below is pdf image in this i want (stored in page1)

bid no,end date,item category,organisation name 

needed

OEM Average Turnover (Last 3 Years),Years of Past Experience required,MSE Exemption for Years Of Experience
and Turnover,Startup Exemption for Years of Experience
and Turnover,Estimated Bid Value,EMD Required

Consignee address only)

Tika is one of the Python packages that you can use to extract the data from your PDF files.

In the example below I'm using Tika and regular expressions to extract these five data elements:

• bid no
• end date
• item category
• organisation name
• total quantity

import re as regex
from tika import parser

parse_entire_pdf = parser.from_file('2022251527199.pdf', xmlContent=True)
for key, values in parse_entire_pdf.items():
    if key == 'content':
        bid_number = regex.search(r'(Bid Number:)\W(GEM\W\d{4}\W[A-Z]\W\d+)', values)
        print(bid_number.group(2))
        GEM/2022/B/1916455

        bid_end_date = regex.search(r'(Bid End Date\WTime)\W(\d{2}-\d{2}-\d{4}\W\d{2}:\d{2}:\d{2})', values)
        print(bid_end_date.group(2))
        21-02-2022 15:00:00

        org_name = regex.search(r'(Organisation Name)\W(.*)', values)
        print(org_name.group(2))
        State Election Commission (sec), Gujarat

        item_category = regex.search(r'(Item Category)\W(.*)', values)
        print(item_category.group(2))
        Desktop Computers (Q2) , Computer Printers (Q2)
 
        total_quantity = regex.search(r'(Total Quantity)\W(\d+)', values)
        print(total_quantity.group(2))
        18

Here is one way to write out the extracted data to a CSV file:

import csv
import re as regex
from tika import parser

document_elements = []

# processing 2 documents 
documents = ['202225114747453.pdf', '2022251527199.pdf']
for doc in documents:
    parse_entire_pdf = parser.from_file(doc, xmlContent=True)
    for key, values in parse_entire_pdf.items():
        if key == 'content':
            bid_number = regex.search(r'(Bid Number:)\W(GEM\W\d{4}\W[A-Z]\W\d+)', values)

            bid_end_date = regex.search(r'(Bid End Date\WTime)\W(\d{2}-\d{2}-\d{4}\W\d{2}:\d{2}:\d{2})', values)

            org_name = regex.search(r'(Organisation Name)\W(.*)', values)

            item_category = regex.search(r'(Item Category)\W(.*)', values)

            total_quantity = regex.search(r'(Total Quantity)\W(\d+)', values)
            
            document_elements.append([bid_number.group(2),
                                      bid_end_date.group(2), 
                                      org_name.group(2), 
                                      item_category.group(2),
                                      total_quantity.group(2)])


with open("out.csv", "w", newline="") as f:
    headerList = ['bid_number', 'bid_end_date', 'org_name', 'item_category', 'total_quantity']
    writer = csv.writer(f)
    writer.writerow(headerList)
    writer.writerows(document_elements)

Here is the additional code that you asked for in the comments.

import os
import re as regex
from tika import parser

document_elements = []

image_directory = "pdf_files"
image_directory_abspath = os.path.abspath(image_directory)
for dirpath, dirnames, filenames in os.walk(image_directory_abspath):
    for filename in [f for f in filenames if f.endswith(".pdf")]:
        parse_entire_pdf = parser.from_file(os.path.join(dirpath, filename), xmlContent=True)
        for key, values in parse_entire_pdf.items():
            if key == 'content':
                bid_number = regex.search(r'(Bid Number:)\W(GEM\W\d{4}\W[A-Z]\W\d+)', values)

                bid_end_date = regex.search(r'(Bid End Date\WTime)\W(\d{2}-\d{2}-\d{4}\W\d{2}:\d{2}:\d{2})', values)

                org_name = regex.search(r'(Organisation Name)\W(.*)', values)

                item_category = regex.search(r'(Item Category)\W(.*)', values)

                total_quantity = regex.search(r'(Total Quantity)\W(\d+)', values)

                document_elements.append([bid_number.group(2),
                                          bid_end_date.group(2),
                                          org_name.group(2),
                                          item_category.group(2),
                                          total_quantity.group(2)])

with open("out.csv", "w", newline="") as f:
    headerList = ['bid_number', 'bid_end_date', 'org_name', 'item_category', 'total_quantity']
    writer = csv.writer(f)
    writer.writerow(headerList)
    writer.writerows(document_elements)

SPECIAL NOTE: I noted that some PDFs don't have an org_name, so you will have to figure out how to handle these with either a N/A, None, or Null