fix: extract tables from jinja

[justinpark]

SUMMARY

When running a query containing Jinja templates in SQL Lab, Airbnb uses the extract_tables_from_jinja_sql function to check permissions on the tables used in the query. However, if the template string includes undeclared variables, these are replaced with blanks, which can cause syntax errors.

This issue has been addressed in the current master branch with an improved parsing logic.
This commit updates only the relevant changes that were not included in version 5.0 of this logic.

BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF

No error thrown

TESTING INSTRUCTIONS

Please design your security manager using extract_tables_from_jinja_sql and then run the following query

select * from table1 where column1 = {{ var1 }}

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

[korbit-ai]

I've completed my review and didn't find any issues.

Files scanned

​

File Path	Reviewed
superset/sql_parse.py	✅

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[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Please upload report for BASE (5.0@fb035f4). Learn more about missing BASE report.

Additional details and impacted files

@@          Coverage Diff           @@
##             5.0   #34307   +/-   ##
======================================
  Coverage       ?   83.24%           
======================================
  Files          ?      547           
  Lines          ?    39953           
  Branches       ?        0           
======================================
  Hits           ?    33258           
  Misses         ?     6695           
  Partials       ?        0           

Flag	Coverage Δ
hive	47.85% <100.00%> (?)
mysql	74.51% <100.00%> (?)
postgres	74.57% <100.00%> (?)
presto	52.33% <100.00%> (?)
python	83.24% <100.00%> (?)
sqlite	74.09% <100.00%> (?)
unit	61.41% <100.00%> (?)

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