feat(logs context): Adding dashboard id to logs context

[Vitor-Avila]

SUMMARY

Includes the dashboard_id information to the logs context, so that it can be included in the sql mutator. Refer to below links for additional context:

• feat: global logs context #26418
• feat: add chart id and dataset id to global logs #26443.

BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF

No UI changes.

TESTING INSTRUCTIONS

1. Update the sql mutator logic to get data from the logs context. For example:

def mutator(sql: str, **kwargs: Any) -> str:
    if dashboard_id := g.logs_context.get("dashboard_id"):
        output = (
            f"-- Metadata:\n"
            + f"-- dashboard_id: {dashboard_id}\n"
        )
        return output + f"{sql}"
    return sql

2. Access a dashboard, and click on the three ellipses for any chart > View query.
3. Validate that the dashboard ID is included in the query comments.

ADDITIONAL INFORMATION

• Has associated issue:
• Required feature flags:
• Changes UI
• Includes DB Migration (follow approval process in SIP-59)
  • Migration is atomic, supports rollback & is backwards-compatible
  • Confirm DB migration upgrade and downgrade tested
  • Runtime estimates and downtime expectations provided
• Introduces new feature or API
• Removes existing feature or API

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 69.69%. Comparing base (b16c899) to head (d410355).

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #27298      +/-   ##
==========================================
+ Coverage   69.57%   69.69%   +0.11%     
==========================================
  Files        1908     1908              
  Lines       74543    74543              
  Branches     8313     8313              
==========================================
+ Hits        51866    51953      +87     
+ Misses      20625    20538      -87     
  Partials     2052     2052              

Flag	Coverage Δ
hive	53.78% <ø> (?)
mysql	78.00% <ø> (ø)
postgres	78.10% <ø> (ø)
presto	53.73% <ø> (?)
python	83.12% <ø> (+0.24%)	⬆️
sqlite	77.62% <ø> (ø)
unit	56.50% <ø> (ø)

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[eschutho]

Thanks @Vitor-Avila!