[Python] Polars str.starts_with() with values from another column

I have a polars DataFrame for example:

>>> df = pl.DataFrame({'A': ['a', 'b', 'c', 'd'], 'B': ['app', 'nop', 'cap', 'tab']})
>>> df
shape: (4, 2)
┌─────┬─────┐
│ A ┆ B │
│ --- ┆ --- │
│ str ┆ str │
╞═════╪═════╡
│ a ┆ app │
│ b ┆ nop │
│ c ┆ cap │
│ d ┆ tab │
└─────┴─────┘


I'm trying to get a third column C which is True if strings in column B starts with the strings in column A of the same row, otherwise, False. So in the case above, I'd expect:

┌─────┬─────┬───────┐
│ A ┆ B ┆ C │
│ --- ┆ --- ┆ --- │
│ str ┆ str ┆ bool │
╞═════╪═════╪═══════╡
│ a ┆ app ┆ true │
│ b ┆ nop ┆ false │
│ c ┆ cap ┆ true │
│ d ┆ tab ┆ false │
└─────┴─────┴───────┘


I'm aware of the df['B'].str.starts_with() function but passing in a column yielded:

>>> df['B'].str.starts_with(pl.col('A'))
... # Some stuff here.
TypeError: argument 'sub': 'Expr' object cannot be converted to 'PyString'


What's the way to do this? In pandas, you would do:

df.apply(lambda d: d['B'].startswith(d['A']), axis=1)

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