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Wait-Event - Adding -TimeSpan
Adding a -TimeSpan parameter to Wait-Event (Fixes #19704). This allows more granularity in waiting on events.
Additionally, changed the polling interval within the command to be 1/100th of the timespan.
These changes improve the performance of Wait-Event substantially, as Wait-Event was always going to wait at least 1/5th of a second.
Due to requests for this to include an argument transformation attribute, this also fixes #20112 .
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@PowerShell/wg-powershell-cmdlets reviewed this, we agree that the desired behavior is for -Timeout to take a [TimeSpan] and having a parameter type convertor that accepts an int (to maintain existing behavior) or a double, so that partial seconds could be specified rather than having an additional parameter.
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This pull request has been automatically marked as stale because it has been marked as requiring author feedback but has not had any activity for 15 days. It will be closed if no further activity occurs within 10 days of this comment.
This pull request has been automatically marked as stale because it has been marked as requiring author feedback but has not had any activity for 15 days. It will be closed if no further activity occurs within 10 days of this comment.
@StartAutomating can you review the CodeFactor issues? Also, CI isn't passing.
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@SteveL-MSFT
@StartAutomating can you review the CodeFactor issues? Also, CI isn't passing.
Fixed.
Please let me know if you'd like some tests on the ArgumentTransform attribute as well.
This pull request has been automatically marked as Review Needed because it has been there has not been any activity for 7 days.
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This pull request has been automatically marked as Review Needed because it has been there has not been any activity for 7 days.
Maintainer, please provide feedback and/or mark it as Waiting on Author
@SteveL-MSFT thanks for the approval, however, I was still planning on making the [ArgumentTransform] a bit better.
If this isn't fully merged, please let me do that this week.
This PR has 137 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!
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Label : Medium
Size : +119 -18
Percentile : 47.4%
Total files changed: 5
Change summary by file extension:
.cs : +60 -9
.ps1 : +59 -9
Change counts above are quantified counts, based on the PullRequestQuantifier customizations.
Why proper sizing of changes matters
Optimal pull request sizes drive a better predictable PR flow as they strike a balance between between PR complexity and PR review overhead. PRs within the optimal size (typical small, or medium sized PRs) mean:
- Fast and predictable releases to production:
- Optimal size changes are more likely to be reviewed faster with fewer iterations.
- Similarity in low PR complexity drives similar review times.
- Review quality is likely higher as complexity is lower:
- Bugs are more likely to be detected.
- Code inconsistencies are more likely to be detected.
- Knowledge sharing is improved within the participants:
- Small portions can be assimilated better.
- Better engineering practices are exercised:
- Solving big problems by dividing them in well contained, smaller problems.
- Exercising separation of concerns within the code changes.
What can I do to optimize my changes
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- For PRs that fall outside of the desired spectrum, review the details and check if:
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How to interpret the change counts in git diff output
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This PR has 144 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!
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Label : Medium
Size : +124 -20
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Total files changed: 6
Change summary by file extension:
.cs : +60 -9
.ps1 : +64 -11
Change counts above are quantified counts, based on the PullRequestQuantifier customizations.
Why proper sizing of changes matters
Optimal pull request sizes drive a better predictable PR flow as they strike a balance between between PR complexity and PR review overhead. PRs within the optimal size (typical small, or medium sized PRs) mean:
- Fast and predictable releases to production:
- Optimal size changes are more likely to be reviewed faster with fewer iterations.
- Similarity in low PR complexity drives similar review times.
- Review quality is likely higher as complexity is lower:
- Bugs are more likely to be detected.
- Code inconsistencies are more likely to be detected.
- Knowledge sharing is improved within the participants:
- Small portions can be assimilated better.
- Better engineering practices are exercised:
- Solving big problems by dividing them in well contained, smaller problems.
- Exercising separation of concerns within the code changes.
What can I do to optimize my changes
- Use the PullRequestQuantifier to quantify your PR accurately
- Create a context profile for your repo using the context generator
- Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the
Excludedsection from yourprquantifier.yamlcontext profile. - Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your
prquantifier.yamlcontext profile. - Only use the labels that matter to you, see context specification to customize your
prquantifier.yamlcontext profile.
- Change your engineering behaviors
- For PRs that fall outside of the desired spectrum, review the details and check if:
- Your PR could be split in smaller, self-contained PRs instead
- Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR).
- For PRs that fall outside of the desired spectrum, review the details and check if:
How to interpret the change counts in git diff output
- One line was added:
+1 -0 - One line was deleted:
+0 -1 - One line was modified:
+1 -1(git diff doesn't know about modified, it will interpret that line like one addition plus one deletion) - Change percentiles: Change characteristics (addition, deletion, modification) of this PR in relation to all other PRs within the repository.
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