codecov[bot]
commented
1 month ago Codecov Report
Attention: Patch coverage is 97.50000% with 1 line in your changes missing coverage. Please review.
Project coverage is 85.93%. Comparing base (
81c2675) to head (6d41262). Report is 2 commits behind head on main.
| Files | Patch % | Lines |
|---|---|---|
| v3/src/models/data/data-set.ts | 97.22% | 1 Missing :warning: |
Additional details and impacted files
```diff @@ Coverage Diff @@ ## main #1396 +/- ## ========================================== - Coverage 85.95% 85.93% -0.03% ========================================== Files 533 533 Lines 25988 26011 +23 Branches 7083 7088 +5 ========================================== + Hits 22339 22353 +14 - Misses 3494 3503 +9 Partials 155 155 ``` | [Flag](https://app.codecov.io/gh/concord-consortium/codap/pull/1396/flags?src=pr&el=flags&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=concord-consortium) | Coverage Δ | | |---|---|---| | [cypress](https://app.codecov.io/gh/concord-consortium/codap/pull/1396/flags?src=pr&el=flag&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=concord-consortium) | `72.55% <37.50%> (-0.11%)` | :arrow_down: | | [jest](https://app.codecov.io/gh/concord-consortium/codap/pull/1396/flags?src=pr&el=flag&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=concord-consortium) | `53.83% <97.50%> (+0.03%)` | :arrow_up: | Flags with carried forward coverage won't be shown. [Click here](https://docs.codecov.io/docs/carryforward-flags?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=concord-consortium#carryforward-flags-in-the-pull-request-comment) to find out more.:umbrella: View full report in Codecov by Sentry.
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cypress[bot]
PT Story: https://www.pivotaltracker.com/story/show/187178550
This PR improves the efficiency of the
notify itemSearch itemOrderAPI request by adding a newdataset.moveItemsaction that rearranges the order of items without removing them and then re-adding them.As a step towards this solution, I also improved the efficiency of
dataset.removeCases, changing it from O(n^2) to O(n*log(n)). Even though the API request no longer uses this action, it still seemed worth keeping the improvement for other cases where it's used.I tested all three variants with tables shared between three users with approximately 5000 items. Here are the results:
removeCases) - 1200-1500 msremoveCases- 850-1000 msmoveItems- 650-800 ms