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Description
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
df = pl.DataFrame({"a": [1]})
pl.SQLContext(df)Log output
TypeError: the truth value of a DataFrame is ambiguous
Hint: to check if a DataFrame contains any values, use `is_empty()`.Issue description
SQLContext only accepts named objects, e.g. pl.SQLContext(df=df), but the error message when one passes an unnamed object is quite obscure.
Expected behavior
InvalidOperationError: all frames must be named.
or something similar.
Installed versions
--------Version info---------
Polars: 1.24.0
Index type: UInt32
Platform: Linux-6.8.0-52-generic-x86_64-with-glibc2.39
Python: 3.12.3 (main, Feb 4 2025, 14:48:35) [GCC 13.3.0]
LTS CPU: False
----Optional dependencies----
Azure CLI <not installed>
adbc_driver_manager <not installed>
altair <not installed>
azure.identity <not installed>
boto3 <not installed>
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>
numpy 2.1.2
openpyxl <not installed>
pandas 2.2.3
polars_cloud <not installed>
pyarrow 18.1.0
pydantic <not installed>
pyiceberg <not installed>
sqlalchemy <not installed>
torch <not installed>
xlsx2csv <not installed>
xlsxwriter <not installed>