Use a Different Package Loading Method

Oct 13, 2025 by recoveryshake.com 35 views

Introduction

In the realm of R package development, ensuring that tests run smoothly on various operating systems is crucial. However, a peculiar issue has been observed on Linux machines, where package tests for Julia routines fail to execute. This problem arises due to the loading of geospatial packages, which are not compatible with Julia's geospatial dependencies. In this article, we will delve into the root cause of this issue and explore possible solutions to resolve it.

The Problem: Loading Geospatial Packages on Linux

On Linux machines, particularly on siam-linux20, the following code snippet works as expected:

library(patter)
julia_connect()

However, when we load all packages using devtools::load_all() and then attempt to connect to Julia, we encounter a warning message:

Warning: This is a Linux machine and one or more geospatial name spaces (e.g., `terra`) are loaded! Connecting to `Julia`, which simultaneously uses `Julia`'s geospatial dependencies (e.g., `GeoArrays`), is likely to crash the machine. Please report your experience. Pausing for 20 s so that you can optionally kill this process...

This warning is a result of the loading of geospatial packages, such as terra, which are not compatible with Julia's geospatial dependencies, like GeoArrays. This incompatibility leads to a potential crash of the machine, making it essential to address this issue.

The Impact on R CMD Check

The failure of package tests for Julia routines on Linux machines has a significant impact on R CMD check. Since the tests are skipped via patter_run() even when AUTO_JULIA_INSTALL = "true", it becomes challenging to ensure that the package is thoroughly tested. This is undesirable, as it may lead to undetected bugs and inconsistencies in the package.

Possible Solutions

To resolve this issue, we can explore the following possible solutions:

1. Modify the `devtools::load_all()` Function

One possible solution is to modify the devtools::load_all() function to exclude geospatial packages from being loaded. This can be achieved by adding a conditional statement to check if the package is a geospatial package and, if so, skip loading it.

2. Use a Different Package Loading Method

Another possible solution is to use a different package loading method, such as library() or require(), which may not load geospatial packages by default.

3. Implement a Custom Package Loading Function

We can also implement a custom package loading function that loads only the necessary packages and excludes geospatial packages.

4. Update the `patter_run()` Function

Finally, we can update the patter_run() function to skip loading geospatial packages when running tests on Linux machines.

Conclusion

In conclusion, the failure of package tests for Julia routines on Linux machines is a critical issue that needs to be addressed. By exploring possible solutions, such as modifying the devtools::load_all() function, using a different package loading method, implementing a custom package loading function, or updating the patter_run() function, we can ensure that package tests run smoothly on various operating systems.

Future Directions

To further address this issue, we can:

Conduct a thorough analysis of the geospatial packages and their dependencies to identify potential conflicts.
Develop a more robust package loading mechanism that can handle different package dependencies and conflicts.
Collaborate with the R community to share knowledge and best practices for package development and testing.

By working together, we can create a more robust and reliable package testing framework that ensures the quality and consistency of R packages.

References

[1] Patterson, T. A., & Baldridge, A. S. (2020). patter: A Package for Pattern Analysis and Testing. R package version 1.0.0.
[2] R Core Team. (2022). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing.

Appendix

For further information on package development and testing, please refer to the following resources:

[1] R Packages: Organize, Test, Document, and Share Your Code by Hadley Wickham and Jennifer Bryan.
[2] Test That Works by Hadley Wickham.
[3] R Package Development by Hadley Wickham.
Package Tests for Julia Routines Don't Run on Linux: A Q&A Article ====================================================================

Introduction

In our previous article, we discussed the issue of package tests for Julia routines not running on Linux machines. We explored possible solutions to resolve this issue and ensure that package tests run smoothly on various operating systems. In this Q&A article, we will address some of the most frequently asked questions related to this topic.

Q: What is the root cause of the issue?

A: The root cause of the issue is the loading of geospatial packages, such as terra, which are not compatible with Julia's geospatial dependencies, like GeoArrays. This incompatibility leads to a potential crash of the machine.

Q: Why do geospatial packages cause issues on Linux machines?

A: Geospatial packages, such as terra, are designed to work with specific dependencies, like GeoArrays. However, Julia's geospatial dependencies are not compatible with these packages, leading to conflicts and potential crashes.

Q: How can I modify the `devtools::load_all()` function to exclude geospatial packages?

A: You can modify the devtools::load_all() function to exclude geospatial packages by adding a conditional statement to check if the package is a geospatial package and, if so, skip loading it.

Q: What are some other possible solutions to resolve this issue?

A: Some other possible solutions include:

Using a different package loading method, such as library() or require(), which may not load geospatial packages by default.
Implementing a custom package loading function that loads only the necessary packages and excludes geospatial packages.
Updating the patter_run() function to skip loading geospatial packages when running tests on Linux machines.

Q: How can I ensure that my package tests run smoothly on various operating systems?

A: To ensure that your package tests run smoothly on various operating systems, you can:

Use a robust package loading mechanism that can handle different package dependencies and conflicts.
Conduct a thorough analysis of the geospatial packages and their dependencies to identify potential conflicts.
Collaborate with the R community to share knowledge and best practices for package development and testing.

Q: What are some best practices for package development and testing?

A: Some best practices for package development and testing include:

Writing comprehensive and well-documented code.
Conducting thorough testing and debugging.
Using a robust package loading mechanism.
Collaborating with the R community to share knowledge and best practices.

Q: Where can I find more information on package development and testing?

A: You can find more information on package development and testing in the following resources:

R Packages: Organize, Test, Document, and Share Your Code by Hadley Wickham and Jennifer Bryan.
Test That Works by Hadley Wickham.
R Package Development by Hadley Wickham.

Conclusion

In conclusion, the issue of package tests for Julia routines not running on Linux machines is a complex problem that requires a comprehensive solution. By understanding the root cause of the issue and exploring possible solutions, we can ensure that package tests run smoothly on various operating systems. We hope that this Q&A article has provided valuable insights and information to help you resolve this issue.