Fix run_raw_sql() operartor

[utkarsharma2]

Description

What is the current behavior?

When we pass multiple dataframes to run_raw_sql() the expected behavior is that the dataframes should be loaded to different temp tables. Currently, that's not happening, and all the data frames are loaded to the same temp table. Later dataframe overrides a former one.

closes: #1687

What is the new behavior?

Every dataframe is loaded to a different temp table.

Does this introduce a breaking change?

Nope

Checklist

• Created tests which fail without the change (if possible)
• Extended the README / documentation, if necessary

[codecov]

Codecov Report

Base: 93.63% // Head: 93.10% // Decreases project coverage by -0.53% ⚠️

Coverage data is based on head (709e024) compared to base (009de42).
Patch coverage: 100.00% of modified lines in pull request are covered.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1700      +/-   ##
==========================================
- Coverage   93.63%   93.10%   -0.53%     
==========================================
  Files          90       90              
  Lines        4712     4714       +2     
  Branches      468      468              
==========================================
- Hits         4412     4389      -23     
- Misses        213      234      +21     
- Partials       87       91       +4     

Impacted Files	Coverage Δ
...thon-sdk/src/astro/sql/operators/base_decorator.py	94.77% <100.00%> (+0.07%)	⬆️
python-sdk/src/astro/databases/snowflake.py	86.10% <0.00%> (-6.65%)	⬇️
python-sdk/src/astro/databases/base.py	90.30% <0.00%> (-3.09%)	⬇️
python-sdk/src/astro/sql/operators/load_file.py	93.20% <0.00%> (+1.94%)	⬆️
python-sdk/src/astro/utils/compat/functools.py	80.00% <0.00%> (+20.00%)	⬆️

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[pankajastro]

@utkarsharma2 how does it will behave after this change if I'll pass multiple Dataframe and a non-temp table? Does it will accept a list of output tables??

[utkarsharma2]

@pankajastro there is no impact for output_table it will still be the same. This change addresses an issue due to which if multiple dataframes were passed to function, we were not putting them in separate temp tables, instead, we were overriding/replacing the same temp table and populating it with a new data frame.

Example:

df_1 = Dataframe({"col1": [1, 2], "col2": [3, 4]})
df_2 = Dataframe({"col3": [1, 2], "col3": [3, 4]})

@aql.run_raw_sql()
def run(tbl_1, tbl_2):
   return "select col1 from {{tbl_1}}"   # <--- this will fail

Because the data of df_2 is loaded to temp_table dropping the data of df_1 so tbl_1 and tbl_2 are the same table.

[feluelle]

Good catch! 🚀

cc @tatiana: I think this is the PR you had meant yesterday 👍