import json
import os
import panel
from datetime import datetime
from typing import Any

import pandas as pd

from pydantic import BaseModel

from watt42_viewlib import attach_w42_state

panel.extension('echarts', 'ace', 'jsoneditor', 'perspective')

SYSTEM_ID = os.environ.get("WATT42_SYSTEM_ID", "invalid-system-id")
API_TOKEN = os.environ.get("WATT42_API_TOKEN", "invalid-api-token")

w42_state = panel.rx(None)

attach_w42_state(rx_var=w42_state, system_id=SYSTEM_ID, token=API_TOKEN)

class PvForecast(BaseModel):
    at: datetime = datetime.now()
    slots: list[float] = []

class LoadForecast(BaseModel):
    at: datetime = datetime.now()
    slots: list[float] = []


class InverterForecast(BaseModel):
    levels: list[float] = []
    grid_import_power: list[float] = []
    
class SystemState(BaseModel):
    pv_forecast: PvForecast = PvForecast()
    load_forecast: LoadForecast = LoadForecast()
    value: int = 42
    inverter: InverterForecast = InverterForecast()

def state_to_text(state: dict[str, Any]) -> str:
    return f"Watt42 State:\n\n```\n{json.dumps(state, indent=2)}\n```\n\nReplace this with some awesome visuals"

state_as_text = panel.bind(state_to_text, w42_state)

state_pane = panel.pane.Markdown(state_as_text, sizing_mode='stretch_width')

def chart1(state: SystemState) -> dict:
    """ Return an ECharts option dict visualizing some aspect of the state."""

    now = state.load_forecast.at
    pv_slots = state.pv_forecast.slots
    load_slots = state.load_forecast.slots
    hours = list(range(len(pv_slots)))
    option = {
        "title": {"text": f"PV and Load Forecast at {now.strftime('%Y-%m-%d %H:%M')}"},
        "tooltip": {"trigger": "axis"},
        "legend": {"data": ["PV Forecast", "Load Forecast", "Inverter Level", "Grid import"]},
        "xAxis": {"type": "category", "data": hours, "name": "Hours"},
        "yAxis": {"type": "value", "name": "Power (kW)"},
        "series": [
            {
                "name": "PV Forecast",
                "type": "line",
                "data": pv_slots,
            },
            {
                "name": "Load Forecast",
                "type": "line",
                "data": load_slots,
            },
            {
                "name": "Inverter Level",
                "type": "line",
                "data": state.inverter.levels,
            },
            {
                "name": "Grid import",
                "type": "line",
                "data": state.inverter.grid_import_power,
            }
        ],
    }
    return option

chart1_rx = panel.rx(chart1)(panel.rx(lambda s: SystemState.model_validate(s) if s else SystemState())(w42_state))

def series_as_df(state: SystemState) -> pd.DataFrame:
    """ Return a pandas DataFrame representation of the series data."""
    data = {
        "Time": [state.load_forecast.at + pd.Timedelta(minutes=15 * i) for i in range(len(state.load_forecast.slots))],
        "PV Forecast": state.pv_forecast.slots,
        "Load Forecast": state.load_forecast.slots,
        "Inverter Level": state.inverter.levels,
    }
    df = pd.DataFrame(data)
    return df

series_df_rx = panel.rx(series_as_df)(panel.rx(lambda s: SystemState.model_validate(s) if s else SystemState())(w42_state))

def summary_as_markdown(state: SystemState) -> str:
    """ Return a markdown summary of the system state."""
    md = f"""
### Summary

- Total PV Forecast: {sum(state.pv_forecast.slots) / 4000.0:.2f} kWh
- Total Load Forecast: {sum(state.load_forecast.slots) / 4000.0:.2f} kWh
- Total grid import: {sum(state.inverter.grid_import_power) / 4000.0:.2f} kWh
"""

    return md

state_summary_rx = panel.rx(summary_as_markdown)(panel.rx(lambda s: SystemState.model_validate(s) if s else SystemState())(w42_state))

sidebar_content = """
Demonstrates how to visualize the Watt42 "dumb inverter simulation" system state.

Find instructions on [how to use this example
here](https://source.c3.uber5.com/watt42-public/watt42_viewlib/src/branch/main/README.md#how-to-use).

"""

grid_config = json.loads('{"version":"3.8.0","plugin":"Datagrid","plugin_config":{"columns":{},"edit_mode":"READ_ONLY","scroll_lock":false},"columns_config":{},"settings":true,"theme":"Pro Light","title":null,"group_by":["level rounded"],"split_by":[],"sort":[["level rounded","desc"]],"filter":[],"expressions":{"level rounded":"round(\\"Inverter Level\\" / 100) * 100\\t","one":"1"},"columns":["index","one","Time","PV Forecast","Load Forecast","Inverter Level","level rounded"],"aggregates":{}}')

_ = panel.template.FastListTemplate(
    title="Watt42: Dumb Inverter Visualization Example",
    sidebar=[panel.pane.Markdown(sidebar_content, sizing_mode='stretch_width'), panel.pane.Markdown(state_summary_rx, sizing_mode='stretch_width')],
    main=[
        panel.pane.ECharts(chart1_rx, sizing_mode='stretch_width', height=400, theme='light'),
        panel.pane.Perspective(series_df_rx, sizing_mode='stretch_width',
                               height=400, columns=grid_config['columns'],
                               title="Group by rounded battery level (experimental)",
                               expressions=grid_config['expressions'],
                               aggregates=grid_config['aggregates'],
                               group_by=grid_config['group_by'],
                               sort=grid_config['sort'],
                               filters=grid_config['filter'],
                               ),
        # warn that above pane may not work on all browsers
        panel.pane.Markdown("**Note:** The above data grid uses the Perspective library which may not work on all browsers.", sizing_mode='stretch_width'),
        state_pane,
        w42_state,
    ],
).servable()