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import pandas as pd | |
import streamlit as st | |
import pandas as pd | |
import PyPDF2 | |
import functions | |
def main(): | |
st.title("PDF to CSV Converter") | |
# File uploader widget | |
uploaded_file = st.file_uploader("Upload PDF", type=["pdf"]) | |
if uploaded_file is not None: | |
# Read PDF file | |
pdf_reader = PyPDF2.PdfFileReader(uploaded_file) | |
num_pages = pdf_reader.numPages | |
# Extract text from each page | |
text = "" | |
for page_num in range(num_pages): | |
page = pdf_reader.getPage(page_num) | |
text += page.extractText() | |
# Convert text to CSV | |
csv_data = convert_to_csv(text) | |
# Display or download CSV | |
st.subheader("Converted CSV Data") | |
st.write(csv_data) | |
# Download link for CSV file | |
st.download_button( | |
label="Download CSV", | |
data=csv_data, | |
file_name="converted_data.csv", | |
mime="text/csv" | |
) | |
def convert_to_csv(text): | |
# Split text into lines and create a DataFrame | |
lines = text.split("\n") | |
df = pd.DataFrame(lines, columns=["Text"]) | |
# Convert DataFrame to CSV format | |
csv_data = df.to_csv(index=False) | |
return csv_data | |
backgroundPattern = """ | |
<style> | |
[data-testid="stAppViewContainer"] { | |
background-color: #0E1117; | |
opacity: 1; | |
background-image: radial-gradient(#282C34 0.75px, #0E1117 0.75px); | |
background-size: 15px 15px; | |
} | |
</style> | |
""" | |
st.markdown(backgroundPattern, unsafe_allow_html=True) | |
st.write(""" | |
# Resume Screening & Classification | |
""") | |
tab3 = st.tabs(['Rank']) | |
with tab3: | |
st.header('Input') | |
if __name__ == "__main__": | |
uploadedJobDescriptionRnk= main() | |
uploadedResumeRnk= main() |