Add a Polars backend #22
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The row order after a polars group_by().agg() is not consistent across multiple executions, so it does not make much sense to test it.
has the same functionality as pandas, need to support arrange / filter for window functions.
is never used
- make dense_rank a nullary operator - do not allow an operator to mutate it's args via mutate_args (this was just for rank and dense_rank and can be handled in a simpler way) - rank and dense_rank are an explicit special case in polars _translate_function since the polars rank function does not support ranking on multiple expressions, thus a conversion to a struct column is necessary
values should not be sorted or positive only up front as this can hide bugs
one cannot specify a tolerance for decimal-float comparison
it does not seem like something very common and every backend does something different and calls it string join / string agg or similar. The SQL backends do a cumulative join, polars not. Maybe we can add it back in as a function only allowed in summarise and not in mutate, since there the behaviour (apart from MSSQL, of course) is consistent.
we also implicitly convert dates to datetimes when comparing / subtracting them. the exact semantics still need to be defined (don't know what SQL does).
strings are 0-indexed.
Postgres and SQLite give cols that only contain null values after a join the Null type. Polars and MSSQL don't do that. transform does what the backend does.
in pl.read_database, DuckDB only accepts a string or some special DuckDB object, so we compile the query to a string for DuckDB. The changed test failed since DuckDB apparently produces floats on integer division. This will be investigated later.
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