dgiot / iotStudio

dgiot平台行业应用扩展插件 dgiot for application plugin
https://dgiot-dashboard.vercel.app/
Mozilla Public License 2.0
283 stars 102 forks source link

chore(deps): bump amis from 1.9.1-beta.11 to 2.3.1 #595

Closed dependabot[bot] closed 2 years ago

dependabot[bot] commented 2 years ago

Bumps amis from 1.9.1-beta.11 to 2.3.1.

Release notes

Sourced from amis's releases.

2.3.1

2022-09-30

问题修复 Bugfix 🐛

日常维护 Chore

  • chore: 优化刷新组件动作 (#5521) @​hsm-lv
  • chore: action args优化 (#5500) @​hsm-lv
  • chore: 补充 input-image 的 autoFill 单元测试 (#5507) @​nwind
  • chore: crud 加载更多按钮在无数据时变成 disable 而不是隐藏,避免在编辑器里看不见 (#5506) @​nwind

2.3.0

2022-09-30

Break Change 🔥

  • 由于ansi-to-react不支持React 18,我们取消了Log组件的高亮功能,组件的disableColor属性从2.3.0版本起不再支持
  • 规范了Range组件change事件的命名,updateValue => onChange

新功能 Features 🚀

问题修复 Bugfix 🐛

... (truncated)

Commits


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pull-request-quantifier-deprecated[bot] commented 2 years ago

This PR has 4 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

``` Label : Extra Small Size : +2 -2 Percentile : 1.6% Total files changed: 1 Change summary by file extension: .json : +2 -2 ``` > Change counts above are quantified counts, based on the [PullRequestQuantifier customizations](https://github.com/microsoft/PullRequestQuantifier/blob/main/docs/prquantifier-yaml.md).

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](https://github.com/microsoft/PullRequestQuantifier/releases) - 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 `Excluded` section from your `prquantifier.yaml` context profile. - Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your `prquantifier.yaml` context profile. - Only use the labels that matter to you, [see context specification](./docs/prquantifier-yaml.md) to customize your `prquantifier.yaml` context 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). #### 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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lsxredrain commented 2 years ago

bump amis from 1.9.1-beta.11 to 2.3.1