[Python] PyPolars, conditional join on two columns

How should one join two pl.LazyFrame using two columns from each pl.LazyFrame based on content in the columns of the left pl.LazyFrame ?

import polars as pl

lf1 = pl.LazyFrame(
data={
"col_1": ["a", "b", "c"],
"col_2": ["d", None, None],
"col_3": [None, "e", None],
},
)

lf2 = pl.LazyFrame(
data={
"col_a": ["d", "xyz"],
"col_b": ["xyz", "e"],
"col_c": ["relevant_info_1", "relevant_info_2"],
},
)


Pseudo-code of desired join :

lf1.join(lf2,
when(col("col_2").is_not_null().then(left_on="col_2", right_on="col_a")
when(col("col_3").is_not_null().then(left_on="col_3", right_on="col_b")
otherwise(do_nothing)
)


Expected result :

shape: (3, 4)
┌───────┬───────┬───────┬─────────────────┐
│ col_1 ┆ col_2 ┆ col_3 ┆ col_c │
│ --- ┆ --- ┆ --- ┆ --- │
│ str ┆ str ┆ str ┆ str │
╞═══════╪═══════╪═══════╪═════════════════╡
│ a ┆ d ┆ null ┆ relevant_info_1 │
│ b ┆ null ┆ e ┆ relevant_info_2 │
│ c ┆ null ┆ null ┆ null │
└───────┴───────┴───────┴─────────────────┘

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