polars LazyFrame.with_context().filter() throws unexpected NotFoundError for column - python-polars

Question

I have two LazyFrames, df1 and df2.
After filtering df2 according to df1 max value, I want to concatenate them.
But combination of with_context() and filter() on LazyFrames will raise NotFoundError.
What's the best way to do this?
import polars as pl
df1 = pl.DataFrame({'foo': [0, 1], 'bar': ['a', 'a']}).lazy()
df2 = pl.DataFrame({'foo': [1, 2, 3], 'bar': ['b', 'b', 'b']}).lazy()
df = pl.concat(
[
df1,
df2.with_context(df1.select(pl.col('foo').alias('foo_')))
.filter(pl.col('foo') > pl.col('foo_').max())
]).collect()
# ---------------------------------------------------------------------------
# NotFoundError Traceback (most recent call last)
# [<ipython-input-2-cf44deab2d4b>](https://localhost:8080/#) in <module>
# 4 df2 = pl.DataFrame({'foo': [1, 2, 3], 'bar': ['b', 'b', 'b']}).lazy()
# 5
# ----> 6 df = pl.concat(
# 7 [
# 8 df1,
#
# 1 frames
# [/usr/local/lib/python3.8/dist-packages/polars/utils.py](https://localhost:8080/#) in wrapper(*args, **kwargs)
# 327 def wrapper(*args: P.args, **kwargs: P.kwargs) -> T:
# 328 _rename_kwargs(fn.__name__, kwargs, aliases)
# --> 329 return fn(*args, **kwargs)
# 330
# 331 return wrapper
#
# [/usr/local/lib/python3.8/dist-packages/polars/internals/lazyframe/frame.py](https://localhost:8080/#) in collect(self, type_coercion, predicate_pushdown, projection_pushdown, simplify_expression, no_optimization, slice_pushdown, common_subplan_elimination, streaming)
# 1166 streaming,
# 1167 )
# -> 1168 return pli.wrap_df(ldf.collect())
# 1169
# 1170 def sink_parquet(
#
# NotFoundError: foo_
When I assign comparison result as a column, error not raised,
(df2.with_context(df1.select(pl.col('foo').alias('foo_')))
.with_column((pl.col('foo') > pl.col('foo_').max()).alias('x'))
.filter(pl.col('x'))).collect()
# OK
But I drop that column after filter(), error again.
(df2.with_context(df1.select(pl.col('foo').alias('foo_')))
.with_column((pl.col('foo') > pl.col('foo_').max()).alias('x'))
.filter(pl.col('x'))
.drop('x')).collect()
# NotFoundError: foo_
Finally I find this works. But what's the difference between the previous?
(it seems verbose. other good solution exists?)
(df2.with_context(df1.select(pl.col('foo').alias('foo_')))
.with_column(pl.col('foo_').max())
.filter(pl.col('foo') > pl.col('foo_'))
.drop('foo_')).collect()
# OK
related?
https://stackoverflow.com/a/71108312/7402018