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| import streamlit as st # data app development | |
| import subprocess # process in the os | |
| from subprocess import STDOUT, check_call #os process manipuation | |
| import os #os process manipuation | |
| import base64 # byte object into a pdf file | |
| import camelot as cam # extracting tables from PDFs | |
| # to run this only once and it's cached | |
| def gh(): | |
| """install ghostscript on the linux machine""" | |
| proc = subprocess.Popen('apt-get install -y ghostscript', shell=True, stdin=None, stdout=open(os.devnull,"wb"), stderr=STDOUT, executable="/bin/bash") | |
| proc.wait() | |
| gh() | |
| st.title("PDF Table Extractor") | |
| st.subheader("with `Camelot` Python library") | |
| st.image("https://raw.githubusercontent.com/camelot-dev/camelot/master/docs/_static/camelot.png", width=200) | |
| # file uploader on streamlit | |
| input_pdf = st.file_uploader(label = "upload your pdf here", type = 'pdf') | |
| st.markdown("### Page Number") | |
| page_number = st.text_input("Enter the page # from where you want to extract the PDF eg: 3", value = 1) | |
| # run this only when a PDF is uploaded | |
| if input_pdf is not None: | |
| # byte object into a PDF file | |
| with open("input.pdf", "wb") as f: | |
| base64_pdf = base64.b64encode(input_pdf.read()).decode('utf-8') | |
| f.write(base64.b64decode(base64_pdf)) | |
| f.close() | |
| # read the pdf and parse it using stream | |
| table = cam.read_pdf("input.pdf", pages = page_number, flavor = 'stream') | |
| st.markdown("### Number of Tables") | |
| # display the output after parsing | |
| st.write(table) | |
| # display the table | |
| if len(table) > 0: | |
| # extract the index value of the table | |
| option = st.selectbox(label = "Select the Table to be displayed", options = range(len(table) + 1)) | |
| st.markdown('### Output Table') | |
| # display the dataframe | |
| st.dataframe(table[int(option)-1].df) | |