whatsapp_parser/streamlit.py at main · PepeZuco/whatsapp_parser · GitHub

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from whatsapp_parser.whats_app_parser import WhatsAppParser
from utils import Utils
from io import BytesIO
import matplotlib.pyplot as plt
import streamlit as st
import tempfile
import os

try:
    st.set_page_config(
        page_title="WhatsApp Chat Analyzer",
        page_icon="large_green_circle",
        layout="wide",
    )

    st.set_option('deprecation.showPyplotGlobalUse', False)

    language = st.sidebar.selectbox('Language', ('Português 🇧🇷', 'English 🇺🇸'))
    texts = Utils.read_language_files(language)
    uploaded_file = st.sidebar.file_uploader(texts['select_file'], type=["txt"])
    st.sidebar.markdown(texts['warning'])

    # Garanta que a chave seja gerada e armazenada
    Utils.generate_and_store_key()

    if not uploaded_file:
        st.image('wpp_logo.png', width=80)
        st.markdown(texts['markdown'])
        st.info(texts['info'])

    if uploaded_file is not None:
        # Save the content of the uploaded file to a temporary file
        temp_file = tempfile.NamedTemporaryFile(delete=False)
        temp_file.write(uploaded_file.read())
        temp_file_path = temp_file.name
        temp_file.close()

        chat = WhatsAppParser(temp_file_path)

        # Clean up the temporary file
        os.remove(temp_file_path)

        # File was uploaded
        if chat:
            if not chat.chat_downloaded_from_apple_device:
                st.info(texts['not_from_apple'])
            if not chat.group_chat:
                st.markdown(f"""#### {texts['welcome']['group' if chat.group_chat else 'chat']} \n _{chat._folder_name.split('_')[2] if chat.group_chat else texts['welcome']['and'].join(chat.users)}_""")

            col1, col2 = st.columns(2)

            # Date input for start_date in the first column
            start_date = col1.date_input(texts['start_date'], chat.chat_dataframe['date'].min(), max_value=chat.chat_dataframe['date'].max(),
                                         min_value=chat.chat_dataframe['date'].min()).strftime('%Y-%m-%d')

            # Date input for end_date in the second column
            end_date = col2.date_input(texts['end_date'], chat.chat_dataframe['date'].max(), max_value=chat.chat_dataframe['date'].max(),
                                       min_value=chat.chat_dataframe['date'].min()).strftime('%Y-%m-%d')

            # Displaying dataframe
            df_display = chat.display_dataframe(start_date=start_date,
                                                end_date=end_date,
                                                language=language)
            st.dataframe(df_display.set_index(texts['dataframe_columns']['timestamp']), height=200)

            # Button to reset dates in the third column
            if col1.button(texts['reset_date']):
                start_date = chat.chat_dataframe['date'].min().strftime('%Y-%m-%d')
                end_date = chat.chat_dataframe['date'].max().strftime('%Y-%m-%d')

            if start_date > end_date: st.warning(texts['date_conflict'], icon="⚠️")
            else:
                st.markdown(f"#### {texts['Wordcloud']}")
                plt.imshow(chat.generate_word_cloud(), interpolation='bilinear')
                plt.axis("off")
                plt.show()
                st.pyplot()

                # Activity Heatmap
                fig6 = chat.generate_activity_heatmap(start_date=start_date, end_date=end_date, language=language).update_layout(height=400, width=1000)
                st.plotly_chart(fig6, theme="streamlit")

                # Number of messages per hour
                fig4 = chat.generate_graph_number_of_messages_per_hour(start_date=start_date, end_date=end_date, language=language)
                st.plotly_chart(fig4, theme="streamlit", use_container_width=True)

                # Number of messages per day
                fill_missing = st.checkbox(
                    value=False,
                    label=texts['Graph_1']['button']["label"],
                    help=texts['Graph_1']['button']["help"])
                fig1 = chat.generate_graph_number_of_messages_per_day(start_date=start_date, end_date=end_date, language=language, fill_missing=fill_missing).update_layout(width=1000)
                st.plotly_chart(fig1, theme="streamlit")

                # Number from type of messages per user
                if chat.chat_downloaded_from_apple_device:
                    fig3 = chat.generate_graph_number_of_types_of_messages_per_user(start_date=start_date, end_date=end_date, language=language)
                    st.plotly_chart(fig3, theme="streamlit", use_container_width=True)

                # Number of messages per user
                fig5 = chat.generate_number_of_messages_per_user(start_date=start_date, end_date=end_date, language=language)
                st.plotly_chart(fig5, theme="streamlit", use_container_width=True)

                # Number from type of messages
                if chat.chat_downloaded_from_apple_device:
                    fig2 = chat.generate_graph_number_of_types_of_messages(start_date=start_date, end_date=end_date, language=language)
                    st.plotly_chart(fig2, theme="streamlit", use_container_width=True)

                # Search word per person
                st.write(texts['count_word_occurrences_by_person']['title'])
                text_search = st.text_input(texts['count_word_occurrences_by_person']['sub_title'], texts['count_word_occurrences_by_person']['default'])
                df = chat.count_word_occurrences_by_person(text_search)
                df.columns = texts['count_word_occurrences_by_person']['columns']
                styler = df.style.bar(subset=texts['count_word_occurrences_by_person']['columns'][1],
                                      align='mid',
                                      color=chat.hex['main_wpp_7'])
                st.write(styler.to_html(), unsafe_allow_html=True)

                # Structure for excel download
                excel_buffer = BytesIO()
                chat.chat_dataframe.to_excel(excel_buffer, index=False, engine='xlsxwriter')
                excel_buffer.seek(0)
                st.sidebar.download_button(
                    label=texts['Download_excel_button'],
                    data=excel_buffer.read(),
                    file_name='chat_analysis.xlsx',
                    mime='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'
                )

except Exception as e:
    st.error(f"An error occurred: {e}")