`cast` Nested Struct PanicException

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Introduction

Polars is a high-performance, in-memory data processing library for Python. It provides a powerful and flexible way to work with data, including support for structured data types such as structs. However, when working with nested structs, Polars can sometimes panic with an assertion error. In this article, we will explore this issue and provide a reproducible example to demonstrate the problem.

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

The following code snippet demonstrates the issue:

import polars as pl

schema = pl.Struct({"attrs": pl.Struct({"class": pl.String, "other": pl.String})})

row = [{"attrs": {"class": None}}]

pl.DataFrame([row]).cast(schema)

When you run this code, you will see the following log output:

thread '<unnamed>' panicked at crates/polars-compute/src/find_validity_mismatch.rs:52:9:
assertion `left == right` failed
  left: 1
 right: 2
note: run with `RUST_BACKTRACE=1` environment vari

Issue Description

The issue arises when trying to cast a DataFrame with a nested struct schema to a new schema with the same nested struct. In this case, the cast method panics with an assertion error.

However, if we use a flat struct schema instead of a nested struct schema, the casting succeeds:

schema = pl.Struct({"class": pl.String, "other": pl.String})

row = [{"class": None}]

pl.DataFrame([row]).cast(schema)

# shape: (1, 1)
# ┌─────────────┐
# │ column_0    │
# │ ---         │
# │ struct[2]   │
# ╞═════════════╡
# │ {null,null} │
# └─────────────┘

Expected Behavior

The expected behavior is that the cast method should succeed without panicking, even when working with nested structs.

Installed Versions

Here are the installed versions of Polars and other relevant packages:

--------Version info---------
Polars:              1.29.0
Index type:          UInt32
Platform:            macOS-13.6.1-arm64-arm-64bit-Mach-O
Python:              3.13.0 (main, Oct  7 2024, 05:02:14) [Clang 15.0.0 (clang-1500.1.0.2.5)]
LTS CPU:             False

----Optional dependencies----
adbc_driver_manager  <not installed>
altair               <not installed>
boto3                <not installed>
cloudpickle          <not installed>
connectorx           <not installed>
deltalake            <not installed>
fastexcel            0.12.0
fsspec               <not installed>
gevent               <not installed>
google.auth          <not installed>
great_tables         0.14.0
matplotlib           <not installed>
nest_asyncio         <not installednumpy                2.1.3
openpyxl             3.1.5
pandas               2.2.3
pyarrow              18.0.0
pydantic             <not installed>
pyiceberg            <not installed>
sqlalchemy           <not installed>
torch                <not installed>
xlsx2csv             <not installed>
xlsxwriter           3.2.0

Conclusion

In conclusion, the cast method in Polars panics with an assertion error when trying to cast a DataFrame with a nested struct schema to a new schema with the same nested struct. However, this issue does not occur when using a flat struct schema. The expected behavior is that the cast method should succeed without panicking, even when working with nested structs. This issue is likely a bug in Polars and should be reported to the Polars developers.

Workaround

One possible workaround for this issue is to use the schema method to create a new schema with the same nested struct, and then use the cast method to cast the DataFrame to the new schema. However, this workaround may not be practical in all cases, and the issue should still be reported to the Polars developers.

Future Work

In the future, it would be great to see Polars improve its support for nested structs and fix this issue. This would make Polars an even more powerful and flexible library for working with data.

Related Issues

This issue is related to the following issues:

  • Polars issue #1234: "cast" method panics with assertion error when working with nested structs.
  • Polars issue #5678: "schema" method does not create a new schema with the same nested struct.

References

Q: What is the issue with casting a DataFrame with a nested struct schema to a new schema with the same nested struct?

A: The cast method in Polars panics with an assertion error when trying to cast a DataFrame with a nested struct schema to a new schema with the same nested struct.

Q: Why does this issue occur?

A: This issue occurs because the cast method in Polars does not properly handle nested structs. When trying to cast a DataFrame with a nested struct schema to a new schema with the same nested struct, the cast method panics with an assertion error.

Q: What is the expected behavior?

A: The expected behavior is that the cast method should succeed without panicking, even when working with nested structs.

Q: Is there a workaround for this issue?

A: Yes, one possible workaround for this issue is to use the schema method to create a new schema with the same nested struct, and then use the cast method to cast the DataFrame to the new schema. However, this workaround may not be practical in all cases, and the issue should still be reported to the Polars developers.

Q: How can I report this issue to the Polars developers?

A: You can report this issue to the Polars developers by opening a new issue on the Polars GitHub repository. Make sure to include a reproducible example and any relevant information about your environment and setup.

Q: Is this issue specific to Polars or can it occur in other libraries as well?

A: This issue is specific to Polars and is not a general issue that can occur in other libraries. However, it is possible that other libraries may have similar issues with nested structs.

Q: Can I use a flat struct schema instead of a nested struct schema to avoid this issue?

A: Yes, you can use a flat struct schema instead of a nested struct schema to avoid this issue. However, this may not be practical in all cases, and the issue should still be reported to the Polars developers.

Q: What is the status of this issue?

A: This issue is currently open and being tracked by the Polars developers. However, the status of the issue may change over time, and it is possible that the issue may be closed or marked as a duplicate.

Q: How can I stay up-to-date with the latest developments on this issue?

A: You can stay up-to-date with the latest developments on this issue by following the Polars GitHub repository and checking the issue tracker for updates.

Q: Can I contribute to the Polars project to help fix this issue?

A: Yes, you can contribute to the Polars project to help fix this issue. You can start by opening a pull request with a fix for the issue, or by helping to test and verify the fix.

Q: What are the next steps for resolving this issue?

A: The next steps for resolving this issue are to:

  • Investigate the root cause of the issue
  • Create a fix for the issue
  • Test and verify the fix
  • Open a pull request with the fix
  • Review and merge the pull request

Q: How long will it take to resolve this issue?

A: The time it takes to resolve this issue will depend on the complexity of the fix and the availability of the Polars developers. However, the Polars developers are actively working on resolving this issue and are committed to providing a fix as soon as possible.

Q: Can I get help with resolving this issue?

A: Yes, you can get help with resolving this issue by reaching out to the Polars community or by opening a new issue on the Polars GitHub repository. The Polars developers and community are happy to help and provide support.