exercism/blazon

Name: blazon

Owner: exercism

Description: Internal tool to let maintainers create duplicate issues in relevant track repositories.

Created: 2016-01-29 22:54:44.0

Updated: 2016-11-20 16:17:33.0

Pushed: 2017-01-02 21:48:33.0

Homepage: null

Size: 9

Language: Go

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README

Blazon

Internal tool to let track maintainers create duplicate issues in all relevant language track repositories.

Installation

If you have Go:

go get -u github.com/exercism/blazon

If not, grab the most recent release.

Configuration

Create a personal api token, giving it the scope “public_repo”. Save it to an environment variable named BLAZON_GITHUB_API_TOKEN.

Usage

Run blazon to see the available flags.

Tips
Top Level Issue

Before submitting the blazon issue, make sure that there is an issue that summarizes the problem/solution. If it doesn't already exist, then create one (it might fit into the https://github.com/exercism/x-common repository, or the https://github.com/exercism/todo repository).

Then include a link to the summary issue in the body of the text for the blazon issue.

This will ensure that the summary issue contains references to each of the individual issues in each of the track repositories. Each of these links will include an icon whose color indicates the status of the issue (open|closed).

This ensures that there is a handy, visible “todo” list that immediately shows the overall status of the effort, and once all of the related links are red, the summary issue can be closed.

Canonical Data

If you're submitting a cross-track issue about an exercise, it is worth checking if there's a JSON file containing the canonical data for the exercise.

If there is no JSON file, then perhaps we need to do a survey first and then create the JSON file before notifying everyone. This would reduce the amount of noise generated if it turns out that the survey uncovers interesting edge cases that the first blazon issue didn't.

If there is a JSON file, then it's worth making sure that it reflects these changes first, so that each language track can reference the canonical data, or (if it has generators) simply regenerate it.


This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.