Panic if tuple kwarg passed to df.with_columns(col_name = accidental_tuple_here)

[DeflateAwning]

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

# Step 1: Create a sample dataframe
df = pl.DataFrame({
    "col1": ["string1", "string2", "string3", "string4"],
    "col2": ["text1", "text2", "text3", "text4"]
})

# Step 2: Add a new column with a trailing comma after the kwarg column spec, making it a tuple
df = df.with_columns(
	new_col=(
		pl.lit("new_value"),  # <- extra comma here
	),
)
print(df)

Log output

No response

Issue description

Polars panics if a tuple kwarg is passed to df.with_columns(...)

For example: df.with_columns(col_name = accidental_tuple_here)

If you do the same thing with a df.select(...), you get the following output:

shape: (1, 1)
┌─────────────────────┐
│ new_col             │
│ ---                 │
│ list[extension]     │
╞═════════════════════╡
│ [String(new_value)] │
└─────────────────────┘

While I suppose you could technically want that for some insane metaprogramming thing, I think that both should result in an error like "You probably made a typo. Remove the extra comma you added by accident at the end of the {col_name} kwarg spec."

Expected behavior

I think that both df.with_columns and df.select should result in an error like "You probably made a typo. Remove the extra comma you added by accident at the end of the {col_name} kwarg spec.", if this issues is encountered.

At the very least, it shouldn't panic.

Installed versions

Tried with both v0.20.25 and v1.0.0.

--------Version info---------
Polars:               1.0.0
Index type:           UInt32
Platform:             Linux-6.5.0-1025-oem-x86_64-with-glibc2.35
Python:               3.11.9 (main, Apr  6 2024, 17:59:24) [GCC 11.4.0]

----Optional dependencies----
adbc_driver_manager:  0.9.0
cloudpickle:          <not installed>
connectorx:           0.3.2
deltalake:            <not installed>
fastexcel:            <not installed>
fsspec:               2024.6.0
gevent:               <not installed>
great_tables:         <not installed>
hvplot:               0.9.2
matplotlib:           3.8.0rc1
nest_asyncio:         1.5.7
numpy:                1.26.4
openpyxl:             3.1.2
pandas:               2.2.2
pyarrow:              16.1.0
pydantic:             2.7.4
pyiceberg:            <not installed>
sqlalchemy:           2.0.25
torch:                <not installed>
xlsx2csv:             0.8.1
xlsxwriter:           <not installed>

[cmdlineluser]

Can reproduce.

It seems to happen with lists also.

>>> pl.DataFrame({"x": [1]}).with_columns(y = [pl.lit(3)])
shape: (1, 2)
┌─────┬─────────────────┐
│ x   ┆ y               │
│ --- ┆ ---             │
│ i64 ┆ list[extension] │
╞═════╪═════════════════╡
│ 1   ┆ [dyn int: 3]    │
└─────┴─────────────────┘

pl.DataFrame({"x": [1, 2]}).with_columns(y = [pl.lit(3)])
# PanicException: called `Result::unwrap()` on an `Err` value: InvalidOperation(ErrString("`list_builder` operation not supported for dtype `object`"))