Dask is used and developed by individuals at a variety of institutions. It sits within the broader Python numeric ecosystem commonly referred to as PyData or SciPy.
Conversation happens in the following places:
Usage questions, requests for help, and general discussions happen in the Dask Discourse forum. If your discussion topic is not a bug report or a feature request, this is the best place to start. It’s also a good place to show off cool things you have built using Dask and to get to know other community members.
Usage questions may also be directed to Stack Overflow with the #dask tag, which is monitored by Dask developers. However, the scope of what is considered a good Stack Overflow question can be narrow, so the Dask Discourse forum may be a better place to start.
Bug reports and feature requests are managed on the GitHub issue tracker
Real-time chat occurs on https://dask.slack.com/. Note that Slack chat not easily searchable and indexed by search engines, so detailed discussion topics around bug reports or usage should go to GitHub issues or the Dask Discourse forum, respectively.
You can subscribe to this calendar to be notified of changes:
Asking for help¶
We welcome usage questions and bug reports from all users, even those who are new to using the project. There are a few things you can do to improve the likelihood of quickly getting a good answer.
Ask questions in the right place: We strongly prefer the use of Discourse or GitHub issues over Slack chat. Discourse and GitHub are more easily searchable by future users, and therefore can be useful to many more people than those directly involved.
If you have a general question about how something should work or want best practices then use Discourse. If you think you have found a bug then use GitHub
Ask only in one place: Please restrict yourself to posting your question in only one place (likely the Dask Discourse or GitHub) and don’t post in both
Create a minimal example: It is ideal to create minimal, complete, verifiable examples. This significantly reduces the time that answerers spend understanding your situation, resulting in higher quality answers more quickly.
See also this blogpost about crafting minimal bug reports. These have a much higher likelihood of being answered