MET 12.1.0 Python Embedding Bugfix Guide Python 3.10 Failure

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Introduction

Hey guys! Today, we're diving into a tricky bug that surfaced in MET (Model Evaluation Tools) version 12.1.0 when using Python embedding with Python 3.10. It's one of those head-scratchers that can really throw a wrench in your workflow, so let's break it down, see what's causing it, and figure out how to tackle it. This article will walk you through the problem, the debugging process, and potential solutions, ensuring your MET setup runs smoothly with Python 3.10. Understanding and resolving this bug is crucial for maintaining the reliability and efficiency of your meteorological evaluations. Python embedding is a key feature in MET, allowing users to leverage Python scripts for data processing and analysis. Therefore, any issues in this area can significantly impact the usability of the tool. Let’s get started!

The Problem: Python Embedding Failure

Describe the Problem

So, here's the deal: When you compile MET version 12.1.0 using Python 3.10, the Python embedding feature just doesn't play nice. It throws errors and refuses to cooperate. But, weirdly enough, if you compile it with Python 3.12, everything works like a charm. This is super important because the Conda build of MET 12.1.0 actually uses Python 3.10, and our buddy @georgemccabe confirmed that the issue pops up there too. This inconsistency can lead to significant disruptions in workflows, especially for users who rely on Python embedding for their data analysis tasks. The failure not only affects the immediate execution of MET tools but also raises concerns about the long-term maintainability and compatibility of the software. Moreover, it highlights the importance of thorough testing across different Python versions to ensure consistent performance.

Expected Behavior

Ideally, Python embedding should work flawlessly whether you're using Python 3.10 or 3.12. No hiccups, no errors – just smooth sailing. The expectation is that MET 12.1.0 should provide a consistent experience across different Python versions, allowing users to seamlessly integrate Python scripts into their workflows. This seamless integration is crucial for tasks such as custom data processing, advanced statistical analysis, and the creation of specialized visualizations. When Python embedding functions as expected, it enhances the flexibility and power of MET, enabling users to tailor their analyses to specific needs. Therefore, addressing this discrepancy is essential for ensuring that MET remains a reliable and versatile tool for meteorological research and forecasting.

Environment

Let's talk environments. @georgemccabe first spotted this using the MET version 12.1.0 Conda build. Then, @JohnHalleyGotway, another hero, replicated the issue on the project machine seneca by compiling the main_v12.1 branch using Python 3.10. This replication across different environments reinforces the validity of the bug and suggests that it's not tied to a specific setup. Understanding the environments where the bug occurs helps in narrowing down the potential causes and developing targeted solutions. The fact that it was observed in both a Conda build and a custom compilation indicates that the issue lies within the core code or the interaction between MET and Python 3.10. Such insights are invaluable for the debugging process and for ensuring that the fix addresses the root cause of the problem.

To Reproduce

Want to see the chaos for yourself? Just run this command:

/d1/personal/johnhg/MET/MET_development/MET-main_v12.1/bin/plot_data_plane \
PYTHON_NUMPY \
letter_numpy_grid_name.ps \
'name = "/d1/personal/johnhg/MET/MET_development/MET-main_v12.1/internal/test_unit/../../share/met/python/examples/read_ascii_numpy_grid.py /d1/projects/MET/MET_test_data/unit_test/python/letter.txt LETTER";' \
-plot_range 0.0 255.0 \
-title "Grid Name: 'G212'" \
-v 10

This should give you this lovely error:

ModuleNotFoundError: No module named 'met'
WARNING: 
WARNING: straight_python_dataplane() -> an error occurred importing module "/d1/personal/johnhg/MET/MET_development/MET-main_v12.1/internal/test_unit/../../share/met/python/examples/read_ascii_numpy_grid"
WARNING:

This error is a clear indicator that the Python embedding is failing because the 'met' module cannot be found. The ModuleNotFoundError is a common Python exception that arises when the interpreter is unable to locate a module that has been imported in the code. In this context, it suggests that the Python environment being used by MET is not correctly configured to find the 'met' module, which is essential for its operation. Providing a clear, reproducible test case like this is crucial for developers to quickly understand and address the bug. By following these steps, others can verify the issue and confirm that any proposed solutions effectively resolve the problem.

Debugging Details: Diving Deep into the Code

Tracing the Source of the Problem

Alright, so here's where things get interesting. We tracked down the culprit! MET version 12.1.0 started using the Py_InitializeFromConfig function, which you can see on this line in the code. This function is part of the Python C API and is used to initialize the Python interpreter with a configuration. Understanding how this function interacts with the Python environment is key to resolving the bug. The introduction of Py_InitializeFromConfig was intended to provide a more robust and flexible way to initialize the Python interpreter, but in this case, it appears to have introduced an unintended side effect. The challenge now is to understand why this function behaves differently between Python 3.10 and 3.12 and how to ensure consistent behavior across versions.

The Path to the 'met' Module

Before the call to Py_InitializeFromConfig, the GP.initialize() function (on line 164) adds crucial elements to the Python path, making sure the met module can be found. The Python path is a list of directories that the Python interpreter searches when importing modules. Ensuring that the correct directories are included in this path is essential for the Python embedding to work correctly. The initial path looks something like this:

DEBUG 1: JHG sys.path BEFORE Py_InitializeFromConfig
['/nrit/ral/met-python3.10/lib/python310.zip',
'/nrit/ral/met-python3.10/lib/python3.10',
'/nrit/ral/met-python3.10/lib/python3.10/lib-dynload',
'/home/johnhg/.local/lib/python3.10/site-packages',
'/nrit/ral/met-python3.10/lib/python3.10/site-packages',
'/d1/personal/johnhg/MET/MET_development/MET-main_v12.1/internal/test_unit/../../share/met/wrappers',
'/d1/personal/johnhg/MET/MET_development/MET-main_v12.1/internal/test_unit/../../share/met/python',
'/d1/personal/johnhg/MET/MET_development/MET-main_v12.1/internal/test_unit/../../share/met/python/examples']

But, after the call to Py_InitializedFromConfig, disaster strikes! The path gets reset, and the location of the met module, along with site-packages, vanishes into thin air. This is where the Python embedding falls apart. The reset of the Python path means that the interpreter can no longer find the necessary modules, leading to the ModuleNotFoundError. Understanding this behavior is crucial for devising a fix. The solution needs to ensure that the Python path remains intact or is correctly restored after the call to Py_InitializeFromConfig.

DEBUG 1: JHG sys.path AFTER Py_InitializeFromConfig
['/nrit/ral/met-python3.10/lib/python310.zip',
'/nrit/ral/met-python3.10/lib/python3.10',
'/nrit/ral/met-python3.10/lib/python3.10/lib-dynload']

Python 3.12 to the Rescue? Not Quite

Now, here’s the kicker: when compiled using Python 3.12, the behavior is totally different. The path setting magically remains untouched by the call to Py_InitializeFromConfig. So, the met module is found, and Python embedding works just fine. This discrepancy between Python versions is a key clue in understanding the root cause of the issue. The fact that Python 3.12 does not exhibit the same behavior suggests that there are version-specific differences in how Py_InitializeFromConfig interacts with the Python environment. This could be due to changes in the Python C API or in the way Python handles path configurations. Investigating these differences is essential for developing a fix that works across all supported Python versions.

The Python 3.11 Twist

There's an important note in the Python documentation about PyConfig_Read (link here) that sheds some light on this: "Fields for path configuration are no longer calculated or modified when calling this function, as of Python 3.11." This tidbit suggests that the behavior change we're seeing is likely tied to how Python handles path configurations in different versions. This documentation note confirms that the behavior of PyConfig_Read and, by extension, Py_InitializeFromConfig, changed significantly between Python 3.10 and later versions. This change directly impacts how Python paths are managed during initialization, which explains why the issue is observed in Python 3.10 but not in 3.12. This insight is crucial for formulating a solution that addresses the underlying cause and ensures compatibility with different Python versions.

Recommendation

Our mission, should we choose to accept it, is to make Python embedding work seamlessly for MET version 12.1.0, no matter if you're rocking Python 3.10 or 3.12. This involves finding a way to preserve the Python path or correctly restore it after the call to Py_InitializeFromConfig. Ensuring consistent functionality across Python versions is critical for maintaining the reliability and usability of MET. The solution needs to be robust and adaptable, accommodating the differences in how Python handles path configurations. This may involve conditional logic based on the Python version or a more fundamental change in how MET initializes the Python interpreter.

A Temporary Workaround

For those of you in a pinch, explicitly setting PYTHONPATH before calling MET does the trick: The PYTHONPATH environment variable is a standard way to specify additional directories for Python to search for modules. By setting this variable, you can ensure that the 'met' module is found, even if the default Python path is not correctly configured. However, this is not an ideal solution, as it requires users to manually configure their environment, which can be cumbersome and error-prone. A proper fix would eliminate the need for this manual step and ensure that Python embedding works out-of-the-box.

export PYTHONPATH=/d1/personal/johnhg/MET/MET_development/MET-main_v12.1/share/met/python:/nrit/ral/met-python3.10/lib/python310.zip:/nrit/ral/met-python3.10/lib/python3.10:/nrit/ral/met-python3.10/lib/python3.10/lib-dynload:/home/johnhg/.local/lib/python3.10/site-packages:/nrit/ral/met-python3.10/lib/python3.10/site-packages:/d1/personal/johnhg/MET/MET_development/MET-main_v12.1/internal/test_unit/../../share/met/wrappers:/d1/personal/johnhg/MET/MET_development/MET-main_v12.1/internal/test_unit/../../share/met/python:/d1/personal/johnhg/MET/MET_development/MET-main_v12.1/internal/test_unit/../../share/met/python/examples

But let's be honest, that's not a great solution. We need something cleaner and more permanent!

Key Takeaways and Solutions

The root cause of the issue lies in the change in how Python 3.11 and later versions handle path configurations with Py_InitializeFromConfig. The function resets the Python path in Python 3.10, causing the met module to be unfindable, while Python 3.12 does not exhibit this behavior due to changes in how path configurations are managed. This inconsistency leads to Python embedding failures in MET 12.1.0 when compiled with Python 3.10.

Potential Solutions:

  1. Conditional Path Handling: Implement conditional logic in MET to handle Python path configurations differently based on the Python version. For Python 3.10, ensure the necessary paths are added after the call to Py_InitializeFromConfig. This approach ensures that the Python path is correctly configured regardless of the Python version being used.
  2. Manual Path Restoration: After calling Py_InitializeFromConfig, manually restore the necessary paths to the Python path. This could involve saving the original path before the call and then re-appending it afterward. This method provides a more direct way to manage the Python path and ensure that the 'met' module remains accessible.
  3. Alternative Initialization Method: Explore alternative methods for initializing the Python interpreter that do not exhibit this path-resetting behavior. This might involve using a different function from the Python C API or a different approach to embedding Python within MET. This is a more fundamental solution that could prevent similar issues in the future.

Prioritizing the Fix

Given the impact on usability and the importance of Python embedding in MET, addressing this bug should be a high priority. A robust solution will ensure that MET remains a reliable tool for meteorological analysis across different environments and Python versions.

Metadata and Issue Tracking

Relevant Deadlines

List relevant project deadlines here or state NONE.

Funding Source

Define the source of funding and account keys here or state NONE.

Assignee

  • [x] Select engineer(s) or no engineer required
  • [ ] Select scientist(s) or no scientist required

Labels

  • [x] Review default alert labels
  • [x] Select component(s)
  • [x] Select priority
  • [x] Select requestor(s)

Milestone and Projects

  • [x] Select Milestone as the next bugfix version
  • [x] Select METplus-X.Y Support project for support of the current coordinated release
  • [x] Select MET-X.Y Development project for development toward the next coordinated release

Define Related Issue(s)

Consider the impact to the other METplus components.

Bugfix Checklist

METplus Workflow

See the METplus Workflow for details.

  • [ ] Complete the issue definition above, including the Time Estimate and Funding Source.
  • [ ] Fork this repository or create a branch of **main_". Branch name: bugfix__main__
  • [ ] Fix the bug and test your changes.
  • [ ] Add/update log messages for easier debugging.
  • [ ] Add/update unit tests.
  • [ ] Add/update documentation.
  • [ ] Push local changes to GitHub.
  • [ ] Submit a pull request to merge into **main_". Pull request: bugfix main_
  • [ ] Define the pull request metadata, as permissions allow. Select: Reviewer(s) and Development issue Select: Milestone as the next bugfix version Select: METplus-X.Y Support project for support of the current coordinated release
  • [ ] Iterate until the reviewer(s) accept and merge your changes.
  • [ ] Delete your fork or branch.
  • [ ] Complete the steps above to fix the bug on the develop branch. Branch name: bugfix__develop_ Pull request: bugfix develop Select: Reviewer(s) and Development issue Select: Milestone as the next official version Select: MET-X.Y Development project for development toward the next coordinated release
  • [ ] Close this issue.

Conclusion

So, there you have it! We've walked through the Python embedding bug in MET 12.1.0, dissected its causes, and explored potential solutions. By understanding the intricacies of how Python initializes and manages paths, we can develop a robust fix that ensures MET works seamlessly across different Python versions. Addressing this issue is crucial for maintaining the reliability and usability of MET, empowering users to leverage Python embedding for their meteorological analyses. Let’s get this fixed and keep MET running smoothly for everyone!