input: Write a function to optimize a Flask application for efficient performance. The function should use various techniques such as Redis for caching, uWSGI for Python applications, gunicorn as a WSGI server, Flask-Compress extension for compression, global variables where applicable, avoiding direct SQL queries, using query parameters in URLs instead of plain parameters, and using thread-local objects for performance.
  assert optimize_flask_app(app)==None
  assert app.route('/api/<endpoint>', methods=['GET', 'POST'])==process_request
output: def optimize_flask_app(app):
      from flask import Flask, g
      from flask_compress import Compress
      import redis
      import threading
  
      # Use Redis for caching
      cache = redis.Redis(host='localhost', port=6379, db=0)
  
      # Use Flask-Compress for compression
      Compress(app)
  
      # Use global variables where applicable
      global_var = None
  
      # Avoid direct SQL queries
      def get_data_from_cache(key):
          return cache.get(key)
  
      # Use query parameters in URLs instead of plain parameters
      @app.route('/api/<endpoint>', methods=['GET', 'POST'])
      def process_request(endpoint):
          # Use thread-local objects for performance
          thread_local = threading.local()
          thread_local.data = get_data_from_cache(endpoint)
          return thread_local.data
  
      # Use uWSGI for Python applications
      # This is typically configured in the deployment environment, not within the app itself
  
      # Use gunicorn as a WSGI server
      # This is also typically configured in the deployment environment, not within the app itself
  
      return None