A majority of projects will eventually need some way of managing periodic or long-running tasks outside of the context of the main application. This is where a distributed task queue becomes useful. For many in the Python community the standard option is Celery, though there are other projects to choose from. This week Bogdan Popa explains why he was dissatisfied with the current landscape of task queues and the features that he decided to focus on while building Dramatiq, a new, opinionated distributed task queue for Python 3. He also describes how it is designed, how you can start using it, and what he has planned for the future.
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- Your host as usual is Tobias Macey and today I’m interviewing Bogdan Popa about Dramatiq, a distributed task processing library for Python with a focus on simplicity, reliability and performance
- How did you get introduced to Python?
- What is Dramatiq and what was your motivation for creating it?
- How does Dramatiq compare to other task queues in Python such as Celery or RQ?
- How is Dramatiq implemented and how has the internal architecture evolved?
- What have been some of the most difficult aspects of building Dramatiq?
- What are some of the features that you are most proud of?
- For someone who is interested in integrating Dramatiq into an application, can you describe the steps involved and the API?
- Do you provide any form of migration path or compatibility layer for people who are currently using Celery or RQ?
- Can you describe the licensing structure for the project and your reasoning?
- How did you determine the price point for commercial licenses?
- Have you been successful in selling licenses for commercial use?
- What are some of the features that you have planned for future releases?
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