Ignore data path on codeql actions

[avelino]

No description provided.

[codecov]

Codecov Report

Merging #604 (05c0ec9) into main (ada371e) will increase coverage by 0.17%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main     #604      +/-   ##
==========================================
+ Coverage   77.55%   77.73%   +0.17%     
==========================================
  Files          21       21              
  Lines        2647     2668      +21     
==========================================
+ Hits         2053     2074      +21     
  Misses        494      494              
  Partials      100      100              

Impacted Files	Coverage Δ
adapters/postgres/postgres.go	74.20% <100.00%> (ø)
template/funcregistry.go	100.00% <100.00%> (ø)

---

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update ada371e...05c0ec9. Read the comment docs.

[pull-request-quantifier-deprecated]

This PR has 382 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!

---

Quantification details

Label      : Large
Size       : +328 -54
Percentile : 78.2%

Total files changed: 19

Change summary by file extension:
.md : +138 -25
.yml : +14 -5
.go : +58 -8
.mod : +2 -2
.sum : +113 -12
.sql : +1 -0
Dockerfile : +1 -1
testdata/Dockerfile : +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 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
  • 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.

---

Was this comment helpful? 👍  :ok_hand:  :thumbsdown: (Email)
Customize PullRequestQuantifier for this repository.