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"""
Code to run streamlit dashboard
"""

import glob
from typing import Optional
import os
import time
import datetime

import streamlit as st
import pandas as pd
import plotly.graph_objects as go

from ffi_reports.generate_reports import generate_finance_reports
from db_utils import generate_db


class ReportsHelper:
    DEFAULT_DB_PATH = "./data/generated_txns.db"

    AVAILABLE_PRODUCTS = [
        "ProdA",
        "ProdB"
    ]

    DEFAULT_GENERAL_REPORTS = [
        "management_summary"
    ]

    DEFAULT_PRODUCT_REPORTS = [
        "summary_report",
        "exception_report_missing_transactions",
        "exception_report_missing_recon",
        "exception_report_amount_mismatch"
    ]

    def __init__(self, reports_dir: Optional[str] = "./data/reports"):
        """
        Initialize the ReportsHelper object which helps find the reports.

        Args:
            reports_dir (str, optional): The directory where the reports are stored.
        """
        self.reports_dir = reports_dir
        self.product_reports = ReportsHelper.DEFAULT_PRODUCT_REPORTS
        self.general_reports = ReportsHelper.DEFAULT_GENERAL_REPORTS
        self.available_products = ReportsHelper.AVAILABLE_PRODUCTS
        self.db_path = ReportsHelper.DEFAULT_DB_PATH

        if not os.path.exists(self.db_path):
            load_str = f"Generating database at: {self.db_path} " \
                       f"since running for the first time. This may take a while..."
            print(load_str)
            with st.spinner(load_str):
                generate_db.main(1000, 1000000)
        else:
            print(f"Database found at: {self.db_path}")

    def get_report_filepath(self, report_type: str, product_name: Optional[str] = None,
                            reports_dir: Optional[str] = "./data/reports") -> str:
        """
        Get the filepath for a report.

        Args:
            report_type (str): The type of report to get the filepath for. One of:
                                - management_summary
                                - summary_report
                                - exception_report_missing_transactions
                                - exception_report_missing_recon
                                - exception_report_amount_mismatch
            product_name (str): The name of the product to get the report for. Required for product reports.
            reports_dir (str, optional): The directory where the reports are stored.

        Returns:

        """
        report_type = report_type.lower()
        if report_type in self.product_reports and product_name is None:
            raise ValueError("'product_name' must be provided for product reports.")

        if report_type == 'management_summary':

            management_summaries = glob.glob(os.path.join(reports_dir, "management_summary_*.csv"))
            if len(management_summaries) == 0:
                report_file_name = report_type + ".csv"
            else:   
                report_file_name = os.path.basename(max(management_summaries, key=os.path.getctime))
        elif report_type in self.product_reports:
            report_file_name = f"{product_name}_{report_type}.csv"
        else:
            raise ValueError(f"Invalid 'report_type': {report_type}")

        return os.path.join(reports_dir, report_file_name)


def mock_progress_bar(max_seconds=15, max_steps=100):
    progress_bar = st.progress(0)
    seconds_per_step = max_seconds / max_steps
    for i in range(100):
        # Perform some work here
        time.sleep(seconds_per_step)
        progress_bar.progress(i + 1)


# Streamlit app
def run_app():
    # Start screen to select the start date and end date
    st.set_page_config(layout="wide")

    # Set the title and page layout for the report dashboard
    st.title("Report Dashboard")
    st.sidebar.title(" :gear:️ Options")

    st.sidebar.markdown("## Select Date Range")
    start_date = st.sidebar.date_input("Start Date", datetime.date(2022, 1, 1))
    end_date = st.sidebar.date_input("End Date", datetime.date.today())
    # Button to generate reports
    if st.sidebar.button("(Re)generate Reports"):
        # Generate reports based on start and end date
        with st.spinner("Generating reports..."):
            start_date_str = start_date.strftime('%Y-%m-%d')
            end_date_str = end_date.strftime('%Y-%m-%d')
            generate_finance_reports(start_date_str, end_date_str)
        st.success("Reports generated successfully!")

    st.sidebar.markdown("## Choose the report type and product")

    reports_helper = ReportsHelper()

    # Get the report type and product selection from the sidebar
    report_type_formatted = st.sidebar.selectbox("Report Type",
                                                 reports_helper.general_reports +
                                                 reports_helper.product_reports)

    report_type = report_type_formatted.lower().replace(" ", "_")
    product_name = None
    if report_type in reports_helper.product_reports:
        product_name = st.sidebar.selectbox("Product", reports_helper.available_products)

    # Display the original table (csv) on the left side of the screen
    col1, col2 = st.columns([1, 1])

    with col1:
        st.subheader("Table Explorer")
        filepath = os.path.abspath(reports_helper.get_report_filepath(report_type, product_name))
        if not os.path.exists(filepath):
            st.write(f"Report not found: {filepath}")
        else:
            df = pd.read_csv(reports_helper.get_report_filepath(report_type, product_name), decimal=".")
            st.write(df)

    with col2:
        if not os.path.exists(filepath):
            st.write(f"Report not found: {filepath}")
        else:
            # Calculate the sum of all number columns
            number_columns = df.select_dtypes(include=["int", "float"]).columns
            number_columns = [col for col in number_columns if
                              not col.lower().endswith("_id") and not col.lower().endswith("_type")]
            sum_values = df[number_columns].sum()

            if report_type == "management_summary":
                # Display the number columns as a line chart over the dates
                st.subheader("Line Chart")
                line_columns = st.multiselect("Select columns for Line Chart", number_columns, default=number_columns)

                if line_columns:
                    line_fig = go.Figure()
                    for column in line_columns:
                        line_fig.add_trace(go.Line(x=df["Date"], y=df[column], name=column))

                    line_fig.update_layout(hovermode="x unified")  # Set the hover mode
                    st.plotly_chart(line_fig)

            # Display the sum of number columns as a bar chart
            st.subheader("Totals")
            fig = go.Figure()
            fig.add_trace(go.Bar(x=sum_values.index, y=sum_values.values, name="", showlegend=False))
            fig.update_layout(xaxis_title="Column", yaxis_title="Sum")
            st.plotly_chart(fig)


if __name__ == "__main__":
    run_app()