dwardu89 / aws-ssm-parameter-store

A GitHub Action to store parameters into AWS Systems Manager Parameter Store.
Apache License 2.0
10 stars 11 forks source link

Update the node packages to the latest values #17

Closed dwardu89 closed 2 years ago

dwardu89 commented 2 years ago

Updating node packages to the latest version.

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

This PR has 104123 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

``` Label : Extra Large Size : +48617 -55506 Percentile : 100% Total files changed: 2910 Change summary by file extension: .yaml : +0 -0 .json : +1066 -2642 .md : +2349 -1354 .ts : +15342 -19666 .js : +29182 -28962 .map : +0 -0 .txt : +0 -273 .html : +0 -26 .tsbuildinfo : +0 -2582 node_modules/.bin/uuid : +1 -1 node_modules/.bin/xml2js : +1 -0 node_modules/@aws-crypto/util/LICENSE : +169 -0 node_modules/@aws-sdk/client-sts/LICENSE : +169 -0 node_modules/@aws-sdk/credential-provider-sso/LICENSE : +169 -0 node_modules/@aws-sdk/credential-provider-web-identity/LICENSE : +169 -0 ``` > 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 detetcted. - 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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