Bump actions/upload-pages-artifact from 2 to 3

[dependabot]

Bumps actions/upload-pages-artifact from 2 to 3.

Release notes

Sourced from actions/upload-pages-artifact's releases.

v3.0.0

Changelog

• Use v4 upload-artifact tag @​robherley (#80)
• Upload pages artifact with upload-artifact v4-beta @​konradpabjan (#78)

To deploy a GitHub Pages site which has been uploaded with this version of actions/upload-pages-artifact, you must also use actions/deploy-pages@v4 or newer.

See details of all code changes since previous release.

Commits

• 0252fc4 Merge pull request #81 from actions/artifacts-next
• 2a5c144 Use actions/download-artifact@v4 in test
• 7e3f6bb Merge pull request #80 from robherley/patch-1
• 257e666 Use v4 upload-artifact tag
• 0313a19 Merge pull request #78 from konradpabjan/main
• 1228e65 Update action.yml
• eb31309 Update artifact names in tests
• 241a975 Correct artifact name during download
• ef95519 Unique artifact name per job
• ecdd3ed Switch to using download@v4-beta
• Additional commits viewable in compare view

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[github-actions]

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[pull-request-quantifier-deprecated]

This PR has 2 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!

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Quantification details

Label      : Extra Small
Size       : +1 -1
Percentile : 0.8%

Total files changed: 1

Change summary by file extension:
.yml : +1 -1

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 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 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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