A Similar Discussion in Pandas

Oct 13, 2025 by wbrum.org 33 views

Introduction

The cudf namespace is a crucial part of the CUDA DataFrames library, providing a public interface for users to interact with the library. However, upon importing cudf, several modules and functions are imported for setup purposes but left in the namespace afterwards. This can lead to confusion and potential issues for users who are not aware of these extraneous objects. In this article, we will discuss the problem, propose a solution, and explore alternatives.

The Problem

When import cudf is called, several modules and functions are imported for setup purposes. These include:

_setup_numba
validate_setup
numba_config
cuda
cupy
rmm
rmm_cupy_allocator
RMMNumbaManager
core
clear_cache

These objects are scoped to just cudf Python and are designed to be public. However, they are not intended to be used directly by users and can cause confusion and potential issues.

For example, if a user imports cudf and then tries to access cudf.cupy.zeros(1), they will be able to do so because cupy is left in the namespace. However, this can lead to unexpected behavior and potential errors.

A Similar Discussion in Pandas

A similar discussion has taken place in the pandas community, as documented in issue 30296. In this issue, the pandas developers discussed the issue of importing unnecessary modules and functions into the pandas namespace.

The Solution

To address this issue, we propose removing the extraneous modules and functions from the cudf namespace. This can be achieved by using the del statement to remove the following objects:

_setup_numba
validate_setup
numba_config
cuda
cupy
rmm
rmm_cupy_allocator
RMMNumbaManager
core
clear_cache

Additionally, we propose removing the following objects which probably should not have a public API:

dtype
BaseIndex
isclose

By removing these objects, we can ensure that the cudf namespace is clean and free of unnecessary modules and functions.

Alternatives

One alternative to removing these objects is to maintain the status quo. However, this would mean that users would continue to have access to these extraneous modules and functions, which could lead to confusion and potential issues.

Additional Context

To further illustrate the issue, consider the following code example:

import cudf

print(cudf.cupy.zeros(1))  # This works because cupy is left in the namespace
print(cudf.dtype)  # This works because dtype is left in the namespace
print(cudf.BaseIndex)  # This works because BaseIndex is left in the namespace
print(cudf.isclose)  # This works because isclose is left in the namespace

As you can see, users can access these extraneous modules and functions simply by importing cudf. This can lead to unexpected behavior and potential errors.

Conclusion

In conclusion, removing extraneous modules and functions from the cudf namespace is a necessary step to ensure that the library is clean and free of unnecessary objects. By removing these objects, we can ensure that users have a clear and concise interface to interact with the library. We propose removing the following objects:

_setup_numba
validate_setup
numba_config
cuda
cupy
rmm
rmm_cupy_allocator
RMMNumbaManager
core
clear_cache
dtype
BaseIndex
isclose

Q: What is the purpose of removing extraneous modules and functions from the `cudf` namespace?

A: The purpose of removing extraneous modules and functions from the cudf namespace is to ensure that the library is clean and free of unnecessary objects. This will make it easier for users to interact with the library and reduce the risk of unexpected behavior and potential errors.

Q: Why are some modules and functions left in the namespace after importing `cudf`?

A: Some modules and functions are left in the namespace after importing cudf because they are imported for setup purposes. However, they are not intended to be used directly by users and can cause confusion and potential issues.

Q: What objects are proposed to be removed from the `cudf` namespace?

A: The following objects are proposed to be removed from the cudf namespace:

_setup_numba
validate_setup
numba_config
cuda
cupy
rmm
rmm_cupy_allocator
RMMNumbaManager
core
clear_cache
dtype
BaseIndex
isclose

Q: Why are `dtype`, `BaseIndex`, and `isclose` proposed to be removed from the `cudf` namespace?

A: dtype, BaseIndex, and isclose are proposed to be removed from the cudf namespace because they probably should not have a public API. They are internal objects that are used for specific purposes and should not be accessed directly by users.

Q: What are the benefits of removing extraneous modules and functions from the `cudf` namespace?

A: The benefits of removing extraneous modules and functions from the cudf namespace include:

A cleaner and more organized namespace
Reduced risk of unexpected behavior and potential errors
Easier interaction with the library for users
Improved maintainability and scalability of the library

Q: What are the potential drawbacks of removing extraneous modules and functions from the `cudf` namespace?

A: The potential drawbacks of removing extraneous modules and functions from the cudf namespace include:

Potential breakage of existing code that relies on these objects
Need for users to update their code to use the new API
Potential impact on performance or functionality of the library

Q: How can users prepare for the removal of extraneous modules and functions from the `cudf` namespace?

A: Users can prepare for the removal of extraneous modules and functions from the cudf namespace by:

Reviewing their code to ensure that it does not rely on these objects
Updating their code to use the new API
Testing their code to ensure that it works as expected with the new API

Q: What is the timeline for removing extraneous modules and functions from the `cudf` namespace?

A: The timeline for removing extraneous modules and functions from the cudf namespace is not yet determined. However, it is expected to be a gradual process that will involve multiple releases of the library.

Q: How can users provide feedback on the removal of extraneous modules and functions from the `cudf` namespace?

A: Users can provide feedback on the removal of extraneous modules and functions from the cudf namespace by:

Submitting issues or pull requests on the cudf GitHub repository
Participating in discussions on the cudf mailing list or forums
Providing feedback through the cudf documentation or website