import logging
import streamlit as st
import json
import sql
import pandas as pd

from enums import CounterType

logger = logging.getLogger(__name__)

if "counter_id" in st.query_params.keys():
    counter_id = int(st.query_params["counter_id"])
    df = sql.get_counter(counter_id)

    st.header('Counter: ' + df['name'])

    color ='#' + df['color']
    match df['type']:
        case CounterType.DAILY.value | CounterType.SIMPLE.value:
            st.bar_chart(sql.get_daily_analytics(int(df['id'])), x="date", y="count", color=color)
        case CounterType.WEEKLY.value:
            st.bar_chart(sql.get_weekly_analytics(int(df['id'])), x="week", y="count", color=color)
        case CounterType.MONTHLY.value:
            st.bar_chart(sql.get_monthly_analytics(int(df['id'])), x="month", y="count", color=color)
        case CounterType.YEARLY.value:
            st.bar_chart(sql.get_yearly_analytics(int(df['id'])), x="year", y="count", color=color)

else:

    st.header("Statistics")

    entries = sql.get_analytics()
    entries_norm = pd.json_normalize(entries.counters.apply(json.loads)).fillna(0)
    entries_full = pd.concat([entries, entries_norm], axis=1).drop(['counters'], axis=1)

    selected_counters = [c for c in entries_full.columns if c != "date"]
    all_counters = sql.get_counters()
    colors = all_counters.loc[all_counters['name'].isin(selected_counters), ["name", "color"]]
    colors.name = colors.name.astype("category")
    colors.name = colors.name.cat.set_categories(selected_counters)
    colors = colors.sort_values(["name"])
    colors = colors.color.apply(lambda c: "#" + c).tolist()

    st.bar_chart(entries_full, x="date", x_label="Date", y_label="Count", color=colors)