Prototype BigQuery CDC -> Anomaly detection python flex template.

[claudevdm]

No description provided.

[gemini-code-assist]

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[claudevdm]

/gemini summary

[codecov]

Codecov Report

❌ Patch coverage is 7.69231% with 24 lines in your changes missing coverage. Please review.
✅ Project coverage is 52.22%. Comparing base (7264b3a) to head (d0786b4).
⚠️ Report is 6 commits behind head on main.

Files with missing lines	Patch %	Lines
...loud/teleport/plugin/maven/TemplatesStageMojo.java	0.00%	17 Missing and 1 partial ⚠️
...gle/cloud/teleport/plugin/DockerfileGenerator.java	25.00%	6 Missing ⚠️

Additional details and impacted files

@@              Coverage Diff              @@
##               main    #3479       +/-   ##
=============================================
+ Coverage     33.37%   52.22%   +18.85%     
- Complexity      481     6050     +5569     
=============================================
  Files           215     1040      +825     
  Lines         12816    62963    +50147     
  Branches       1249     6896     +5647     
=============================================
+ Hits           4277    32883    +28606     
- Misses         8203    27856    +19653     
- Partials        336     2224     +1888     

Components	Coverage Δ
spanner-templates	72.23% <ø> (∅)
spanner-import-export	69.02% <ø> (∅)
spanner-live-forward-migration	80.49% <ø> (∅)
spanner-live-reverse-replication	77.88% <ø> (∅)
spanner-bulk-migration	89.18% <ø> (∅)
gcs-spanner-dv	85.34% <ø> (∅)

Files with missing lines	Coverage Δ
...gle/cloud/teleport/plugin/DockerfileGenerator.java	85.59% <25.00%> (-4.41%)	⬇️
...loud/teleport/plugin/maven/TemplatesStageMojo.java	17.53% <0.00%> (-0.37%)	⬇️

... and 847 files with indirect coverage changes

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[claudevdm]

/gemini review

[gemini-code-assist]

Code Review

This pull request introduces a new BigQuery Anomaly Detection template, which is a significant and valuable addition. The changes are well-structured, covering both Java and Python components, and include comprehensive unit and integration tests. The safe_eval module is particularly well-designed for secure expression evaluation, and the updates to Dockerfile generation enhance the flexibility of Python template deployment. The new README provides excellent documentation for users. Overall, this is a high-quality contribution.

[claudevdm]

@shunping can you please take a look at the anomaly detection parts?