GH-37051: [Dev][JS] Add Dependabot configuration for npm

[kou]

Rationale for this change

We can add MINOR: [JS] prefix to PRs from Dependabot automatically.

What changes are included in this PR?

Add a configuration for npm.

Are these changes tested?

No. I want to test this by merging this to main.

Are there any user-facing changes?

No.

• Closes: [Dev][JS] Add Dependabot configuration for npm #37051

[github-actions]

⚠️ GitHub issue #37051 has been automatically assigned in GitHub to PR creator.

[assignUser]

Sounds good. @domoritz what do you think?

[domoritz]

I don't think we need weekly updates since it would just add extra work to review and merge.

Do we have a script to automatically merge patch and minor updates that don't break the tests?

[assignUser]

I don't think we need weekly updates since it would just add extra work to review and merge.

We can change the interval to monthly?

Do we have a script to automatically merge patch and minor updates that don't break the tests?

While technically possible I don't think the ASF policy would allow that (only if the bot was using a PAT by a committer who would then be personally responsible for any changes contributed with their PAT.)

[kou]

If we can merge PRs from Dependabot only when CI is green, I'll do it. It's not a large work.

Do we have a script to automatically merge patch and minor updates that don't break the tests?

We can do it by a on: pull_request_target GitHub Actions workflow. But it's out-of-scope of this. This just wants to prepare title of PRs from Dependabot. Formatting PR titles by hand is a very bother task for me.

[domoritz]

That all sounds good to me. I'd change it to monthly.

[kou]

OK. I've changed to "monthly".
I'll merge this.

[conbench-apache-arrow]

After merging your PR, Conbench analyzed the 6 benchmarking runs that have been run so far on merge-commit 77d87a9.

There were 3 benchmark results indicating a performance regression:

• Commit Run on ursa-i9-9960x at 2023-08-12 01:50:56Z
  • file-read (R) with compression=uncompressed, dataset=fanniemae_2016Q4, file_type=feather, language=R, output_type=table
  • dataframe-to-table (R) with dataset=type_floats, language=R
• and 1 more (see the report linked below)

The full Conbench report has more details.