05 Sep Python execution module
A quick update from us: We have developed a new Python based execution module for PowerBot, which allows a much quicker start and faster execution when developing custom algorithms.
When companies implement and start trading with their own algorithms, they usually have crossed a number of difficulties, challenges and unexpected problems. This is a normal process for everyone working on automation strategies and writing algorithms for their use cases. However, it can make the process of developing algorithms time and resource intensive. As we offer a system for algorithmic trading, we felt the need to tackle this problem for our customers. Hence, our team took up the challenge and developed a solution and the result is our new Python execution module (EM).
The EM is designed for an easy and fast development and implementation of your algorithms. Every use case (does not matter, if it is closing open positions or marketing of flexible capacities) requires the same basic features. Therefore, we figured it is not necessary for every company to spend time developing standard features and we integrated them into the EM. As Python is the most popular programming language for our clients, this decision was very easy for us.
But what exactly does the EM do? PowerBot is originally designed around an OpenAPI to allow fast development of applications. In addition, we provide event subscription on web socket basis, which enables much faster reaction times and the data usually needs to be synced with data retrieved from the OpenAPI, which contains additional information. The connection management for web socket subscriptions, reconnection and fallback-mechanisms as well as synchronization are a regular issue for algorithm developers.
Whilst providing other useful functions like integrated order management features and error handling, the EM also takes care of a fast and efficient execution of your algorithms. For this, the EM integrates parallel execution of algorithms based on market driven events.
The new EM improves the process of creating algorithms and lets you focus on the relevant aspect: creating your algorithms.