refactor: rewrite as_polars_df.data.frame

[eitsupi]

Close #816
It used to call pl$DataFrame internally, but has been completely rewritten to not call it.

Speeds seem to be comparable, but memory usage may have been reduced.
(The bench package does not measure memory usage on the Rust side, but given that the output RPolarsDataFrame is the same, memory usage on the Rust side should not be much different.)

big_df = do.call(rbind, lapply(1:10, \(x) nycflights13::flights))

library(polars)
library(nanoarrow)

bench::mark(
  pl_DataFrame = {
    pl$DataFrame(big_df)
  },
  as_polars_df = {
    as_polars_df(big_df)
  },
  from_nanoarrow = {
    as_polars_df(as_nanoarrow_array_stream(big_df))
  },
  check = FALSE,
  min_iterations = 10L
)
#> # A tibble: 3 × 6
#>   expression          min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>     <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 pl_DataFrame   826.41ms 839.49ms     1.16     1.91MB    0.289
#> 2 as_polars_df   738.85ms 864.31ms     1.16   204.05KB    0.129
#> 3 from_nanoarrow    1.15s    1.27s     0.790   77.48MB    0.339

^{Created on 2024-02-17 with reprex v2.0.2}

[eitsupi]

I will update the test and documentation later.

@etiennebacher @sorhawell If you are interested, check the performance in the benchmarks above.

[etiennebacher]

I'll review in more details later, but I'm a bit confused about the objective of this PR. If the speed isn't affected and we don't know if the memory used decreases, then why rewrite this? Is this an intermediate step to fix #676?

[eitsupi]

Yes, pl$DataFrame is not optimized for the purpose of scanning data.frame and has a lot of extra processing.
In the current main branch, as_polars_df depends on pl$DataFrame, but this should clearly be reversed, given that the latter has more to do, and as_polars_df should not depend on pl$DataFrame.

[eitsupi]

Given the simplicity of the process, it is not surprising that memory usage is reduced.