import os
import gradio as gr
import plotly.express as px
import pandas as pd

from utils import duckdb_queries as dq
from utils.gradio import get_window_url_params
from utils.indicators import IndexGenerator

# Instantiate outside gradio app to avoid re-initializing GEE, which is slow
indexgenerator = IndexGenerator()

metric_names = os.listdir('metrics')
for i in range(len(metric_names)):
    metric_names[i] = metric_names[i].split('.yaml')[0].replace('_', ' ')

def toggle_metric_definition_box(text_input):
    if text_input is None or text_input == '':
        return indexgenerator.get_metric_file()
    else:
        return None

def make_timeseries_plot(df):
    for col in df.columns:
        df[col] = pd.to_numeric(df[col], errors='ignore')
    return px.line(df, x='Year', y='Score (Area * Value)', markers=True)

with gr.Blocks() as demo:
    with gr.Column():
        with gr.Row():
            m1 = gr.Plot(label='Project Map')
            ts_plot = gr.Plot(label='Metric scores over time')
        with gr.Row():
            project_name = gr.Dropdown([], label="Project", value="Select project")
            metric = gr.Dropdown(metric_names, label='Metric', value='Select metric')
            start_year = gr.Number(value=2017, label="Start Year", precision=0)
            end_year = gr.Number(value=2022, label="End Year", precision=0)
        with gr.Row():
            view_btn = gr.Button(value="Show project map")
            calc_btn = gr.Button(value="Calculate metric")
            metric_btn = gr.Button(value='Show/hide metric definition')
        metric_docs = gr.Textbox(
            label="The chosen metric is a linear combination of these components normalized to a range of 0 to 1 and with the given coefficients",
            interactive=False)
        results_df = gr.Dataframe(
            headers=["Year", "Project Name", "Score"],
            datatype=["number", "str", "number"],
            label="Scores by year",
        )
    calc_btn.click(
        indexgenerator.calculate_score,
        inputs=[start_year, end_year],
        outputs=results_df,
    ).then(
        make_timeseries_plot,
        inputs=results_df,
        outputs=ts_plot
    )
    view_btn.click(
        fn=indexgenerator.show_project_map,
        outputs=[m1],
    )

    def update_project_dropdown_list(url_params):
        username = url_params.get("username", "default")
        projects = dq.list_projects_by_author(author_id=username)
        # Initialize the first project in the list
        project_names = projects['name'].tolist()
        return gr.Dropdown.update(choices=project_names)

    # Change the project name in the index generator object when the
    # user selects a new project
    project_name.change(
        indexgenerator.set_project,
        inputs=project_name
    )

    # Set the metric to be calculated
    metric.change(
        indexgenerator.set_metric,
        inputs=metric
    )

    # Toggle display of metric information
    metric_btn.click(
        toggle_metric_definition_box,
        inputs=metric_docs,
        outputs=metric_docs
    )

    # Get url params
    url_params = gr.JSON({"username": "default"}, visible=False, label="URL Params")

    # Gradio has a bug
    # For dropdown to update by demo.load, dropdown value must be called downstream
    b1 = gr.Button("Hidden button that fixes bug.", visible=False)
    b1.click(lambda x: x, inputs=project_name, outputs=[])

    # Update project dropdown list on page load
    demo.load(
        fn=update_project_dropdown_list,
        inputs=[url_params],
        outputs=[project_name],
        _js=get_window_url_params,
        queue=False,
    )

demo.launch()