import uvicorn
from fastapi import FastAPI
from fastapi.middleware.wsgi import WSGIMiddleware
from dash_plotly_QC_scRNA import app as dashboard1
#from app2 import app as dashboard2

#########################################################
import dash
from dash import dcc, html, Output, Input
import plotly.express as px
import dash_callback_chain
import yaml
import polars as pl
pl.enable_string_cache(False)

# Set custom resolution for plots:
config_fig = {
  'toImageButtonOptions': {
    'format': 'svg',
    'filename': 'custom_image',
    'height': 600,
    'width': 700,
    'scale': 1,
  }
}

config_path = "./azure/data/config.yaml"

# Add the read-in data from the yaml file
def read_config(filename):
    with open(filename, 'r') as yaml_file:
        config = yaml.safe_load(yaml_file)
    return config

config = read_config(config_path)
path_parquet = config.get("path_parquet")
conditions = config.get("conditions")
col_features = config.get("col_features")
col_counts = config.get("col_counts")
col_mt = config.get("col_mt")

# Import the data from one .parquet file
df = pl.read_parquet(path_parquet)
#df = df.rename({"__index_level_0__": "Unnamed: 0"})

# Setup the app
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

######################################################################
# Define the FastAPI server
# Mount the Dash app as a sub-application in the FastAPI server
#app.mount("/dashboard2", WSGIMiddleware(dashboard2.server))

# Start the FastAPI server
if __name__ == "__main__":
    app = FastAPI()
    app.mount("/dashboard1", WSGIMiddleware(dashboard1.server))
    uvicorn.run(app, host="0.0.0.0")