Regression in polars 1.14.0 results in corrupt dataframes when adding columns from literals

[jakob-keller]

Checks

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of Polars.

Reproducible example

import polars as pl

value = 1
values = [value] * 5
foo = pl.DataFrame({"foo": values})

# dataframe with column `bar` from Series
foo_with_bar_from_series = foo.with_columns(pl.Series("bar", values))
print(foo_with_bar_from_series)
"""
shape: (5, 2)
┌─────┬─────┐
│ foo ┆ bar │
│ --- ┆ --- │
│ i64 ┆ i64 │
╞═════╪═════╡
│ 1   ┆ 1   │
│ 1   ┆ 1   │
│ 1   ┆ 1   │
│ 1   ┆ 1   │
│ 1   ┆ 1   │
└─────┴─────┘
"""

# dataframe with column `bar` from literal
foo_with_bar_from_literal = foo.with_columns(pl.lit(value).alias("bar"))
print(foo_with_bar_from_literal)
"""
shape: (5, 2)
┌─────┬─────┐
│ foo ┆ bar │
│ --- ┆ --- │
│ i64 ┆ i32 │
╞═════╪═════╡
│ 1   ┆ 1   │
│ 1   ┆ 1   │
│ 1   ┆ 1   │
│ 1   ┆ 1   │
│ 1   ┆ 1   │
└─────┴─────┘
"""

# both dataframes are equal
print(foo_with_bar_from_series.equals(foo_with_bar_from_literal))
"""
True
"""

# works as expected
print(foo_with_bar_from_series.gather_every(2))
"""
shape: (3, 2)
┌─────┬─────┐
│ foo ┆ bar │
│ --- ┆ --- │
│ i64 ┆ i64 │
╞═════╪═════╡
│ 1   ┆ 1   │
│ 1   ┆ 1   │
│ 1   ┆ 1   │
└─────┴─────┘
"""

# raises ShapeError since polars 1.14.0
print(foo_with_bar_from_literal.gather_every(2))
"""
polars.exceptions.ShapeError: Series length 3 doesn't match the DataFrame height of 5
"""

# weird work around exists
print(
    foo_with_bar_from_literal[:, : foo_with_bar_from_literal.width].gather_every(2),
)
"""
shape: (3, 2)
┌─────┬─────┐
│ foo ┆ bar │
│ --- ┆ --- │
│ i64 ┆ i32 │
╞═════╪═════╡
│ 1   ┆ 1   │
│ 1   ┆ 1   │
│ 1   ┆ 1   │
└─────┴─────┘
"""

Log output

No response

Issue description

A regression introduced in polars 1.14.0 results in corrupt dataframes when adding columns from literals. Subsequent operations, such as .gather_every() result in ShapeError. See example for details, including a workaround that apparently fixes affected metadata.

Expected behavior

No ShapeError is thrown, i.e. behavior reverts to polars<1.14.0

Installed versions

--------Version info---------
Polars:              1.14.0
Index type:          UInt32
Platform:            macOS-15.1.1-arm64-arm-64bit
Python:              3.12.7 (main, Oct 16 2024, 07:12:08) [Clang 18.1.8 ]
LTS CPU:             False

----Optional dependencies----
adbc_driver_manager  <not installed>
altair               <not installed>
boto3                1.35.36
cloudpickle          <not installed>
connectorx           <not installed>
deltalake            <not installed>
fastexcel            <not installed>
fsspec               <not installed>
gevent               <not installed>
google.auth          <not installed>
great_tables         <not installed>
matplotlib           <not installed>
nest_asyncio         <not installed>
numpy                2.1.3
openpyxl             <not installed>
pandas               <not installed>
pyarrow              <not installed>
pydantic             2.10.1
pyiceberg            <not installed>
sqlalchemy           <not installed>
torch                <not installed>
xlsx2csv             <not installed>
xlsxwriter           <not installed>

[jakob-keller]

I just noticed the different dtypes occuring in my example, but that is unrelated to the issue.