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app.py

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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 manipulation
+import os #os proces manipulation
+import base64 # byte object into a pdf file
+import camelot as cam # extracting tables from PDFs
+
+
+# to run this only once it's cached
+@st.cache
+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 the 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.b64encode(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 of the table
+
+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)

requirements.txt

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+opencv-python-headless
+camelot-py
+streamlit