import asyncio
from datetime import datetime, date, time

from faicons import icon_svg

from modules.get_rules_in_window import (
    DF, 
    LAST_UPDATED, 
    START_DATE, 
    GET_SIGNIFICANT, 
    METADATA, 
    AGENCIES, 
    groupby_agency, 
    groupby_ym, 
    plot_agency, 
    plot_month, 
    )

from shiny import reactive
from shiny.express import input, render, ui

FOOTER = f"""
    -----
    
    Developed by the [GW Regulatory Studies Center](https://go.gwu.edu/regstudies). See our page on the [Congressional Review Act](https://regulatorystudies.columbian.gwu.edu/congressional-review-act) for more information.
    """

ui.page_opts(
    title="Rules in the Congressional Review Act (CRA) Window", #fillable=True, 
    )

with ui.sidebar(title="Settings"):
    ui.input_date("start_date", "Start of window", value=START_DATE, min=START_DATE, max=date.today())
    
    ui.input_switch("switch", "Show significant rules in plots", False)
    
    ui.input_select("menu_agency", "Select agencies", choices=["all"] + AGENCIES, selected="all")
    
    #ui.input_checkbox_group(
    #    "significant",
    #    "EO 12866 Significance",
    #    ["Section 3(f)(1)", "Other"],
    #)

with ui.layout_column_wrap():
    with ui.value_box(showcase=icon_svg("book")):
        "All final rules"
        @render.text
        def count_rules():
            return f"{filtered_df()['document_number'].count()}"
        ui.input_action_button("filter_all", "View", ) #class_="btn-success")
    
    with ui.value_box(showcase=icon_svg("book")):
        "Section 3(f)(1) Significant rules"
        @render.text
        def count_3f1_significant():
            output = "Not available"
            if GET_SIGNIFICANT:
                output = f"{filtered_df()['3f1_significant'].sum()}"
            return output
        ui.input_action_button("filter_3f1", "View", ) #class_="btn-success")
    
    with ui.value_box(showcase=icon_svg("book")):
        "Other Significant rules"
        @render.text
        def count_other_significant():
            output = "Not available"
            if GET_SIGNIFICANT:
                output = f"{filtered_df()['other_significant'].sum()}"
            return output
        ui.input_action_button("filter_other", "View", )

with ui.navset_card_underline(title=""):
    
    with ui.nav_panel("Rules in detail"):
        @render.data_frame
        def table_rule_detail():
            df = filtered_sig()
            #print(df.columns)
            #df.loc[:, "date"] = df.apply(lambda x: f"{x['publication_year']}-{x['publication_month']}-{x['publication_day']}", axis=1)
            df.loc[:, "date"] = df.loc[:, "publication_date"].apply(lambda x: f"{x.date()}")
            char, limit = " ", 10
            df.loc[:, "title"] = df["title"].apply(lambda x: x if len(x.split(char)) < (limit + 1) else f"{char.join(x.split(char)[:limit])}...")
            df.loc[:, "agencies"] = df["parent_slug"].apply(lambda x: "; ".join(x))
            cols = [
                "date", 
                "title", 
                "agencies", 
                "3f1_significant", 
                "other_significant", 
                ]
            return render.DataGrid(df.loc[:, [c for c in cols if c in df.columns]], width="100%") #filters=True)
    
    with ui.nav_panel("By month"):
        
        with ui.layout_columns():
        
            @render.plot
            def plot_by_month():
                grouped = grouped_df_month()
                return plot_month(
                    grouped
                    )
    
            @render.data_frame
            def table_by_month():
                grouped = grouped_df_month()
                cols = [
                    "publication_year", 
                    "publication_month",
                    "rules",
                    "3f1_significant", 
                    "other_significant", 
                    ]
                return render.DataTable(grouped.loc[:, [c for c in cols if c in grouped.columns]])

    with ui.nav_panel("By agency"):
        
        with ui.layout_columns():
            
            @render.plot
            def plot_by_agency():
                grouped = grouped_df_agency()                
                if input.switch():
                    pass
                    # placeholder for stacked bar chart
                else:
                    plot = plot_agency(
                        grouped.head(10),
                        )
                    return plot

            @render.data_frame
            def table_by_agency():
                grouped = grouped_df_agency()
                cols = [
                    "agency", 
                    "acronym",
                    "rules",
                    "3f1_significant", 
                    "other_significant", 
                    ]
                return render.DataTable(grouped.loc[:, [c for c in cols if c in grouped.columns]])

with ui.accordion(open=False):
    
    with ui.accordion_panel("Download Data"):
        
        @render.download(
            label="Download data as CSV",
            filename=f"rules_in_cra_window_accessed_{date.today()}.csv",
        )
        async def download():
            await asyncio.sleep(0.25)
            yield filtered_df().to_csv(index=False)

with ui.accordion(open=False):
    
    with ui.accordion_panel("Notes"):
        
        ui.markdown(
            f"""
            Rule data retrieved from the [Federal Register API](https://www.federalregister.gov/developers/documentation/api/v1).
            
            Executive Order 12866 significance data last updated **{LAST_UPDATED}**.
            """
            )

ui.markdown(
    FOOTER
)

#ui.tags.footer()


# ----- REACTIVE CALCULATIONS ----- #


@reactive.calc
def filtered_df():
    filt_df = DF
    
    # filter dates
    try:
        filt_df = filt_df.loc[filt_df["publication_date"] >= input.start_date()]
    except TypeError:
        filt_df = filt_df.loc[filt_df["publication_date"] >= datetime.combine(input.start_date(), time(0, 0))]
    
    # filter agencies
    if input.menu_agency() != "all":
        bool_agency = [True if input.menu_agency() in agency else False for agency in filt_df["parent_slug"]]
        filt_df = filt_df.loc[bool_agency]
    
    return filt_df

@reactive.calc
def filtered_sig():    
    filt_df = filtered_df()
    
    # filter significance
    if filter_value.get() == "all":
        pass
    elif filter_value.get() == "3f1":
        filt_df = filt_df.loc[filt_df["3f1_significant"] == 1]
    elif filter_value.get() == "other":
        filt_df = filt_df.loc[filt_df["other_significant"] == 1]
    
    return filt_df

@reactive.calc
def grouped_df_month():
    filt_df = filtered_sig()
    grouped = groupby_ym(filt_df, significant=GET_SIGNIFICANT)
    return grouped


@reactive.calc
def grouped_df_agency():
    filt_df = filtered_sig()
    grouped = groupby_agency(filt_df, metadata=METADATA, significant=GET_SIGNIFICANT)
    return grouped


# ----- REACTIVE VALUES ----- #


filter_value = reactive.value("all")

@reactive.effect
@reactive.event(input.filter_all)
def _():
    filter_value.set("all")
    filtered_df()

@reactive.effect
@reactive.event(input.filter_3f1)
def _():
    filter_value.set("3f1")
    filtered_df()

@reactive.effect
@reactive.event(input.filter_other)
def _():
    filter_value.set("other")
    filtered_df()