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 = "./app/azure/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 app = FastAPI() # Mount the Dash app as a sub-application in the FastAPI server app.mount("/dashboard1", WSGIMiddleware(dashboard1.server)) #app.mount("/dashboard2", WSGIMiddleware(dashboard2.server)) # Define the main API endpoint @app.get("/") def index(): return "Hello" # Start the FastAPI server if __name__ == "__main__": uvicorn.run(app, host="0.0.0.0")