# Remote OTP with Ray Ray is a distributed execution framework for Python, and you can run `onetick.py` code remotely on your dedicated Ray instance, without need to installing OneTick binaries locally. ## Remote OTP Concepts Although, it isn't possible to use `onetick.py` without OneTick installation and its binaries, but it is still possible to run `onetick.py` code remotely on Ray instance, while developing locally in your preferable IDE or Jupyter.  Each request to Ray server needs to be done in initialized context: ```default import ray ray.init() ``` To `onetick-py` code you need to locate it inside some function, which in turn must be decorated with `@ray.remote(max_retries=1)` decorator to become so called "remote function". Argument `max_retries=1` is good to avoid retrying for failing calls of remote function, which is most probable will be caused by mistakes in your `onetick.py` code. ```default import onetick.py as otp @ray.remote(max_retries=1) def example_otp_code(): # here your OTP code goes ... return results ``` Following code runs remote function on Ray instance and return the results. ```default result = ray.get(example_otp_code.remote()) ``` When you finish, it is **necessary to shutdown your Ray connection** (don't forget to do it, as it is could lead to memory consumption on Ray server): ```default ray.shutdown() ```