input: Write a function to optimize a Flask application for efficient performance by implementing performance optimization techniques such as using Redis for caching session and query performance, using uWSGI for Python applications, using gunicorn as WSGI server, using Flask-Compress extension for compression, using global variables where applicable, avoiding direct SQL queries and using model methods instead, using query parameters in URLs instead of plain parameters, and using thread-local objects for performance.
  
  assert optimize_flask()
output: def optimize_flask():
      from flask import Flask, g
      from flask_compress import Compress
      from flask_redis import FlaskRedis
      from werkzeug.local import LocalProxy
  
      app = Flask(__name__)
      Compress(app)
      redis_client = FlaskRedis(app)
  
      @app.before_request
      def before_request():
          g.redis = redis_client
          g.thread_local = LocalProxy(lambda: g._thread_local)
          g._thread_local = {}
  
      @app.route('/query')
      def query():
          query_result = g.redis.get('cached_query')
          if query_result is None:
              query_result = perform_query()
              g.redis.set('cached_query', query_result)
          return query_result
  
      @app.route('/model_method')
      def model_method():
          result = MyModel.query_method()
          return result
  
      @app.route('/url_param/<int:param>')
      def url_param(param):
          return f"Parameter: {param}"
  
      @app.route('/thread_local')
      def thread_local():
          g.thread_local['data'] = "Thread-local data"
          return g.thread_local['data']
  
      return app