Does anyone know how to make a basic calculated field in eazyBi reports to show only the names of people who left comments on Jira tickets? I don’t want to use JavaScript. I’m trying to get a list of unique commenters for each issue.
Here’s a sample of what I’ve tried:
def get_commenters(issue):
commenters = set()
if issue.comments:
for comment in issue.comments:
if comment.author:
commenters.add(comment.author.name)
return ', '.join(commenters)
issue.custom_field = get_commenters(issue)
This doesn’t work right now. Any ideas on how to fix it or do it differently? Thanks!
I’ve encountered a similar issue and found that modifying the report design rather than relying on calculated fields can work much better. In my experience, I added the ‘Comments’ measure and then included ‘Comment Author’ as a row attribute. I also applied a filter to remove empty authors and grouped the results by issue key so that each issue displays only unique commenters. This approach avoids the complexity of custom code and has proven reliable across various projects. Adjust the report’s display settings to best suit your needs.
yo dawg, i got a trick for ya. skip the fancy stuff and just use the comments measure in ur report. throw in comment author as a dimension, group by issue key, and bam! distinct count on authors. easy peasy. filters help clean it up too. works like a charm for me everytime, no headaches
Having dealt with similar challenges in eazyBi, I’ve found a straightforward solution that doesn’t require custom fields or complex calculations. Create a report using ‘Comments’ as your measure and ‘Comment Author’ as a dimension. Group by ‘Issue Key’ and apply a distinct count on ‘Comment Author’. This approach effectively lists unique commenters per issue.
To refine your results, add filters to exclude system-generated comments or empty authors. You can also use eazyBi’s built-in formatting options to present the data in a more readable format, such as a comma-separated list.
This method is both scalable and maintainable, adapting well to changes in your Jira instance without requiring frequent updates to custom fields or scripts. It’s been reliable across various projects I’ve worked on, saving time and reducing complexity in the long run.
Having worked extensively with eazyBi, I can suggest an alternative approach that doesn’t require JavaScript or complex calculations. Use the ‘Comments’ measure in your report, then add ‘Comment Author’ as a dimension. Group by Issue Key and apply a distinct count on Comment Author. This method effectively lists unique commenters per issue without custom code.
For enhanced clarity, consider adding a filter to exclude system-generated comments or empty authors. You can further refine the output by utilizing eazyBi’s built-in formatting options to present the data in a more readable format, such as a comma-separated list if that’s your preference.
This solution is both scalable and maintainable, adapting well to changes in your Jira instance without requiring frequent updates to custom fields or scripts.
As someone who’s been in the trenches with eazyBi and Jira integration, I can tell you that getting commenter names doesn’t have to be a headache. Here’s what’s worked for me:
Instead of messing with calculated fields, leverage eazyBi’s native functionality. Create a report with ‘Comments’ as your measure and ‘Comment Author’ as a dimension. Then, group by ‘Issue Key’ and apply a distinct count on ‘Comment Author’. This gives you a clean list of unique commenters per issue.
A pro tip: use eazyBi’s filtering to exclude system comments or blank authors, which will clean up your data nicely. I’ve found this method to be robust and scalable as your Jira instance grows.
One caveat: if you need this data in a specific format for another process, you might have to export and perform some light post-processing. For most cases, though, this approach is both efficient and simple.