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app.py

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+
+import utils as utils
+
+import streamlit as st
+from io import StringIO
+from datetime import datetime, date
+
+def dataframe_to_csv_download(dataframe):
+    # Convert the DataFrame to a CSV string
+    csv = dataframe.to_csv(index=False)
+    csv_bytes = csv.encode('utf-8')
+
+    # Create a buffer to hold the CSV string in bytes
+    buf = StringIO()
+    buf.write(csv)
+    buf.seek(0)
+
+    today = datetime.now().strftime("%Y-%m-%d %H:%M")
+
+    # Create a download button in the Streamlit app
+    st.download_button(
+        label="Download CSV File",
+        data=csv_bytes,
+        file_name=f"ScrappedData_{today}.csv",
+        mime="text/csv",
+    )
+
+
+
+if __name__=='__main__':
+    st.title('LinkedIn Job Scraper')
+    st.write('This app scrapes LinkedIn for job listings.')
+    url = st.text_area("Enter the url here..")
+
+    if st.button("Get Records") and url:
+        with st.spinner("Scrapping the given URL"):
+            scrap_df = utils.scrap_data(url)
+        st.dataframe(scrap_df)
+        dataframe_to_csv_download(scrap_df)
+        
+        st.write('')

utils.py

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+import utils as utils
+import streamlit as st
+from io import StringIO
+from datetime import datetime, date
+
+def dataframe_to_csv_download(dataframe):
+    # Convert the DataFrame to a CSV string
+    csv = dataframe.to_csv(index=False)
+    csv_bytes = csv.encode('utf-8')
+
+    # Create a buffer to hold the CSV string in bytes
+    buf = StringIO()
+    buf.write(csv)
+    buf.seek(0)
+
+    today = datetime.now().strftime("%Y-%m-%d %H:%M")
+
+    # Create a download button in the Streamlit app
+    st.download_button(
+        label="Download CSV File",
+        data=csv_bytes,
+        file_name=f"ScrappedData_{today}.csv",
+        mime="text/csv",
+    )
+
+
+
+if __name__=='__main__':
+    st.title('LinkedIn Job Scraper')
+    st.write('This app scrapes LinkedIn for job listings.')
+    url = st.text_area("Enter the url here..")
+
+    if st.button("Get Records") and url:
+        with st.spinner("Scrapping the given URL"):
+            scrap_df = utils.scrap_data(url)
+        st.dataframe(scrap_df)
+        dataframe_to_csv_download(scrap_df)
+        
+        st.write('')