fix(rust,python): Harden Series.reshape against invalid parameters

[datenzauberai]

This is a fix for #15543

Improvements:

• dimensions < -1 will raise an error instead of panicking
• dimensions will be inferred from placeholders -1 whenever it is possible; (-1, -1) will be inferred to either (0, 0) for an empty series or to (len(), 1) for a non-empty series
• empty series can only be reshaped to (0, 0) or (0, ) (after inferring)
• dimensions that do not fulfil rows*cols == len() after inferring placeholders will raise an error

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 80.81%. Comparing base (11fe9d8) to head (a6e343f).

Additional details and impacted files

@@            Coverage Diff             @@
##             main   #16281      +/-   ##
==========================================
+ Coverage   80.80%   80.81%   +0.01%     
==========================================
  Files        1393     1393              
  Lines      179406   179406              
  Branches     2921     2921              
==========================================
+ Hits       144971   144989      +18     
+ Misses      33932    33914      -18     
  Partials      503      503              

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[datenzauberai]

While pl.List gets first exploded and is reshaped according to the spec...

print(pl.DataFrame(pl.Series(name="a", values=[[1, 2, 3, 4]], dtype=pl.List(pl.Int64))).select(pl.col("a").reshape((2,2))))
print(pl.DataFrame(pl.Series(name="a", values=[[1], [2], [3], [4]], dtype=pl.List(pl.Int64))).select(pl.col("a").reshape((2,2))))
┌───────────┐
│ a         │
│ ---       │
│ list[i64] │
╞═══════════╡
│ [1, 2]    │
│ [3, 4]    │
└───────────┘

pl.Array is treated differently right now more like a scalar datatype...

print(pl.DataFrame(pl.Series(name="a", values=[[1, 2, 3, 4]], dtype=pl.Array(pl.Int64, width=4))).select(pl.col("a").reshape((2, 2))))
ComputeError: cannot reshape len 1 into shape [2, 2]
print(pl.DataFrame(pl.Series(name="a", values=[[1], [2], [3], [4]], dtype=pl.Array(pl.Int64, width=1))).select(pl.col("a").reshape((2, 2))))
┌─────────────────────┐
│ a                   │
│ ---                 │
│ list[array[i64, 1]] │
╞═════════════════════╡
│ [[1], [2]]          │
│ [[3], [4]]          │
└─────────────────────┘

We could explode pl.Array(inner_dtype) as well and then return pl.List(inner_dtype), but one could also argue that not exploding is how it should work and makes sense if one uses pl.Array for struct-like things.

pl.Array would even be a much more natural output type than pl.List for this operation, but it would not be able to handle empty series (no pl.Array(width=0)) and I guess that's too much of a change...

[ritchie46]

Thank you @datenzauberai