Allow df_concat to be created without a linker #2144
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RobinL
commented
Apr 16, 2024
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| pipeline = CTEPipeline(input_dataframes) | ||
| # If the user has provided any ColumnExpression, convert to string |
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Lines 256-264 is a separate bug I found in this code whereby ColumnExpressions were not being converted into strings
RobinL
commented
Apr 16, 2024
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| from .linker import Linker | |||
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| def vertically_concatenate_sql(linker: Linker) -> str: | |||
| def vertically_concatenate_sql( | |||
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Main changes are here - rather than accepting a linker, this now accepts arguments, meaning it can be used outside the context of a linker
RobinL
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process_input_tables_simplification
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RobinL
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RobinL
commented
Apr 16, 2024
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| tables_as_splink_dataframes = {} | ||
| existing_tables = [] | ||
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| if not input_aliases: | ||
| # If any of the input_tables are strings, this means they refer |
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This doesn't work if the user provides e.g. fake_1000.parquet (a filename rather than a table). To be consistent with what happens when we register tables in linker.py, we'll just give every table an alias for now
f"_splink__input_table{i}" for i, _ in enumerate(input_tables)
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ADBond
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Apr 29, 2024
splink/vertically_concatenate.py
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| def vertically_concatenate_sql(linker: Linker) -> str: | ||
| def vertically_concatenate_sql( | ||
| input_tables: Dict[str, SplinkDataFrame], | ||
| salting_reqiured: bool, |
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Closes #2142
The
vertically_concatenate_sqlroutine now takes specific arguments rather than accepting a linker. This allows it to be used in cases where a linker is unavailable such asprofile_columns.This will allow the code to be used in a variety of other scenarios where __splink__df_concat` is needed such as if we're analysing blocking rules outside of the context of a linker.
This is built on top of #2143 which should be merged first.