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View Code? Open in Web Editor NEWCampus Experts Hackday, 21st-22nd October 2017
Campus Experts Hackday, 21st-22nd October 2017
In the event of multiple modules being submitted in one PR, Prefect should comment with a warning, close the PR, and issue guidance on how to rebase commits out of a PR.
For some modules, it is easy to catch problems outside of a human review.
For module 1 in particular, there are some common failure modes:
Prefect can aid us in reviews by checking module 1 length, and the presence of required sections such as timeline.
Loads. Y'all rock, thank you so much for this weekend, it was a lot of fun working with you ๐
Apologies if I missed any one, I was up until 5am breaking a script that @PandelisZ later helped me fix ๐
@KaiFish I got this (body text wise) if no one else is doing it.
Students frequently use gendered language in submissions and comments where it is not needed. In many cases, this is due to language barriers. Prefect should support the growth of inclusivity in the community by catching these instances, and providing an explanation as to why it's uninclusive, and alternatives.
Examples:
There are numerous aspects of etiquette we want to enforce. Some are true for all of GitHub, some are true for experts.
In particular for experts, we want to discourage students adding reviewers, or tagging reviewers, or asking for review. Prefect should post a warning to students who do this.
@joenash is working on this
Prefect should greet new users.
For some modules, students frequently submit work that they did long before the training. These submissions should be discouraged: we do not want students to just take the shortest path to becoming an expert, the exercises are evidence of effort applied.
For some modules, this is especially easy to catch.
When this happens, Prefect should warn them that their submission may not be eligible for the application, and provide a link to the module choice issue.
Markdown is new to many students, and mistakes are often made in styling. Prefect should help our students with good markdown style, by linting their markdown documents.
There is a pull request template that has three functions:
This template is frequently ignored: when the required sections aren't deleted, it's a sign the instructions aren't being followed. The template is our brown m&ms.
When they don't delete the required lines, we should close the pull request, and post a message reminding them to follow instructions.
Prefect will provide data for Report Card.
POST /queue/exercise
. But only post when the "exercise" tag is added so we don't get typo corrections in there.DELETE /queue/exercise/:id
where id
is the github repo PR id (https://github.com/campus-experts/open-training/pull/724 this is 724 for example)POST /trainee/infringement
.I am working on adding this
video to guide people through making a pull request and following the template
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Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
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Data-Driven Documents codes.
China tencent open source team.