Bump getdaft from 0.2.19 to 0.2.24

[dependabot]

Bumps getdaft from 0.2.19 to 0.2.24.

Release notes

Sourced from getdaft's releases.

v0.2.24

Changes

✨ New Features

• [FEAT] Allow returning of pyarrow arrays from UDFs @​jaychia (#2252)
• [FEAT] Add left, right, and outer joins @​kevinzwang (#2166)
• [FEAT] Add rpad and lpad expressions @​murex971 (#2157)
• [FEAT] AWS Profile override in S3Config @​samster25 (#2243)
• [FEAT] Add unpivot @​kevinzwang (#2204)
• [FEAT] Add string repeat functionality @​murex971 (#2198)
• [FEAT] Approximate quantile aggregation (pulled into main) @​jaychia (#2179)
• [FEAT] pivot @​colin-ho (#2183)

🚀 Performance Improvements

• [PERF] Adaptive Query Execution @​samster25 (#2176)
• [PERF]: swap out json_deserializer for simd_json @​universalmind303 (#2228)
• [PERF] Evaluate only true/false side of if_else if predicate is boolean @​colin-ho (#2222)
• [PERF] enable metadata preservation across materialization points @​samster25 (#2216)

👾 Bug Fixes

• [BUG] Fix tab completion on expression namespaced accessors @​jaychia (#2251)
• [BUG] route abfss to AzureBlob @​samster25 (#2244)

📖 Documentation

• [CHORE] Skip demo notebook @​jaychia (#2248)
• [FEAT] Add rpad and lpad expressions @​murex971 (#2157)
• [DOCS] Add user guide for read_sql @​colin-ho (#2226)
• [FEAT] Add unpivot @​kevinzwang (#2204)
• [DOCS] Add read_hudi in the api docs @​xushiyan (#2225)
• [FEAT] Add string repeat functionality @​murex971 (#2198)
• [DOCS] LinkedIn Big Data meetup tutorial @​jaychia (#2223)
• [FEAT] Approximate quantile aggregation (pulled into main) @​jaychia (#2179)
• [DOCS] Add read_lance docs @​jaychia (#2218)
• [FEAT] pivot @​colin-ho (#2183)

🧰 Maintenance

• [CHORE] Drop Python 3.7 @​samster25 (#2250)
• [CHORE] Improve timestamp repr @​colin-ho (#2245)
• [CHORE] Allow multiple group_bys for pivot @​colin-ho (#2242)
• [CHORE] Skip demo notebook @​jaychia (#2248)
• [CHORE] Return &str for expression name @​colin-ho (#2224)
• [CHORE] Mount provision.py for iceberg integration tests @​jaychia (#2232)
• [CHORE]: remove trait aliases @​universalmind303 (#2229)

⬆️ Dependencies

... (truncated)

Commits

• 62f9dd6 [FEAT] Allow returning of pyarrow arrays from UDFs (#2252)
• f1d6570 [CHORE] Drop Python 3.7 (#2250)
• 3b1a5ca [BUG] Fix tab completion on expression namespaced accessors (#2251)
• 0541774 [CHORE] Improve timestamp repr (#2245)
• b61461f [PERF] Adaptive Query Execution (#2176)
• 89e3916 [FEAT] Add left, right, and outer joins (#2166)
• e47b48a [CHORE] Allow multiple group_bys for pivot (#2242)
• 252721e [CHORE] Skip demo notebook (#2248)
• d035454 [FEAT] Add rpad and lpad expressions (#2157)
• 3e9dcd4 [BUG] route abfss to AzureBlob (#2244)
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[dsaad68]

@canimus

I have tried to bump the version of daft from 0.2.19 to 0.2.24 on python version 3.11.9, I can not pass any test successfully.

For example, the current implementation of the has_min check:

def has_min(self, rule: Rule, dataframe: daft.DataFrame) -> Union[bool, int]:
    perdicate = daft.col(rule.column).min()
    return dataframe.select(perdicate).to_pandas().iloc[0, 0] == rule.value

It will raise this error:

cuallee\__init__.py:1199: in validate
    return self.compute_engine.summary(self, dataframe)
cuallee\daft_validation.py:513: in summary
    unified_results = {
cuallee\daft_validation.py:514: in <dictcomp>
    rule.key: [operator.methodcaller(rule.method, rule, dataframe)(compute)]
cuallee\daft_validation.py:98: in has_min
    return dataframe.select(perdicate).to_pandas().iloc[0, 0] == rule.value
.venv\Lib\site-packages\daft\api_annotations.py:26: in _wrap
    return timed_method(*args, **kwargs)
.venv\Lib\site-packages\daft\analytics.py:189: in tracked_method
    result = method(*args, **kwargs)
.venv\Lib\site-packages\daft\dataframe\dataframe.py:662: in select
    builder = self._builder.select(self.__column_input_to_expression(columns))
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = * Source:
|   Number of partitions = 1
|   Output schema = id#Int32

to_select = [min(col(id))]

    def select(
        self,
        to_select: list[Expression],
    ) -> LogicalPlanBuilder:
        to_select_pyexprs = [expr._expr for expr in to_select]
>       builder = self._builder.select(to_select_pyexprs)
E       daft.exceptions.DaftCoreException: DaftError::ValueError Aggregation expressions are not currently supported in project: min(col(id))
E       If you would like to have this feature, please see https://github.com/Eventual-Inc/Daft/issues/1979#issue-2170913383

There are some internal changes in Daft package that might cause this, there are more information here.
I have also commented this there.

Suggestion

This method (and others) should be update like this:

def has_min(self, rule: Rule, dataframe: daft.DataFrame) -> Union[bool, int]:
    col = daft.col(rule.column)
    return dataframe.select(col).min(col).to_pandas().iloc[0, 0] == rule.value

[dsaad68]

@canimus based on the information provided by @kevinzwang, in here; I need to modify the methods in daft_validation.py to solve this problem.
It seems the suggested workaround above is going to be backward compatible.

[dependabot]

Looks like getdaft is up-to-date now, so this is no longer needed.