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[WIP][MNT] Downgrade package versions to last stable dev point and update gradually #4150
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- update fugue to latest version. 0.9.1 - Added support for `report` parameter in FugueBackend and tests for compatibility with fugue-0.9.1.
this tests have a bug but we need to investigate if its a shap bug or pycaret bug. I created a issue to discuss and investigate this problem: pycaret#4152
…guments Correctly pass call_id to _persist_input in FastMemorizedFunc.call to resolve TypeError: MemorizedFunc._persist_input() missing 1 required positional argument: 'kwargs'. This ensures compatibility with joblib's signature while maintaining PyCaret's caching optimizations.
@Smartappli @amotl Would you be available to lend a hand here? I'm having trouble understanding what's happening with the tests. joblib does not display an explanatory message that allows you to get to the root of the problem. |
Hi @celestinoxp. Thanks a stack for dedicating work to this. 💯 This PR run responded like:
oO. That's probably one of those super hard errors to debug, exaggerated by that it is happening on a remote CI system. But hey, is it really true that you brought it down to just 1 failed test run? That would be so excellent already! I don't know what I could contribute to improve the situation here. Recently, I heard colleagues talking about ways to log into GHA's execution context from your workstation, in order to be able to interactively use the environment where the problem happens, at hand. Would you be happy if I would dig out corresponding information, in order to present it here for anyone who would like to have a closer look what's happening within C/GHA/PyCaret at this particular spot where the CI workflow goes south? Is the test suite actually succeeding on your machine, and just failing on CI/GHA? |
@amotl I will fix everything :) The problem is in compatibility with joblib 1.4, and I will solve it as soon as I have some time available**. |
Hi.
Excellent! 🚀
I am doing the same with my libraries where I do not aim for unrestricted downstream havocs. 👍
All right. Is it possible to also fix it by limiting the upper version boundary like with the other dependencies?
That sounds interesting, and I think we should emphasize it collaboratively. I can also ask about deriving funding from fragments of our next financing round, but I am not a C-level person, so it is not likely I can make a significant difference in convincing others about it. With kind regards, |
Increase tolerance for execution time in setup performance test - Increased the tolerance for execution time differences from 0.2 to 0.6 in `test_setup_performance`. - This change addresses occasional test failures due to small variations in execution time. - A TODO comment has been added to investigate the root cause of the increased execution time in the future.
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I would suggest:
- leave lower bounds if they were in the last release
- add upper bounds to last known stable test run
- do not use pins (see above)
More generally, the de-facto policy used in sktime
is this:
sktime/sktime#1480
I think the defensive policy might also be advisable, due to the larger number of soft deps. But that is a discussion for a later day.
Hi @celestinoxp. FWIW, I've whipped up your branch into the CI workflow runs of ours, that invoke a few Jupyter Notebooks which use PyCaret.
More
You may want to inspect a failed test run over here, errors are mostly revolving around that:
However, because this happens in |
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@amotl there is a problem with sktime which probably has a bug that causes a joblib error to appear. |
Hi. Are you able to improve the situation by increasing the recursion limit, using |
@amotl i tried a temporary solution with setrecursionlimit, but tests/test_time_series_blending.py still not passing... because have a infinite loop (maybe from sktime). |
…etitemError` in `SummaryTransformer` (#7903) ### Issue The `_custom_showwarning` method in `sktime/utils/warnings.py` causes infinite recursion when handling certain warnings (e.g., pandas `LossySetitemError`), resulting in a `RecursionError: maximum recursion depth exceeded`. Additionally, in `sktime/transformations/series/summarize.py`, the line `func_dict.loc[:, "window"] = func_dict["window"].astype("object")` throws a `LossySetitemError` in pandas 2.x due to incompatible type coercion. This issue was identified while using PyCaret with sktime, where tests failed with a crash in a joblib worker due to a `PicklingError` caused by excessive recursion. ### Solution - Modified the `_custom_showwarning` method in the `_SuppressWarningPattern` class to add a guard against recursion using an `_in_warning` flag, while preserving delegation to `original_showwarning`. - Fixed `SummaryTransformer` to use a type-safe conversion with `func_dict["window"] = func_dict["window"].astype("object", copy=False)`, avoiding the `LossySetitemError`. ### Changes - `sktime/utils/warnings.py`: Added protection against infinite recursion in the `_custom_showwarning` method of `_SuppressWarningPattern` using an `_in_warning` flag. - `sktime/transformations/series/summarize.py`: Replaced the problematic assignment with an explicit conversion of the `"window"` column to `object` using `copy=False` for greater efficiency. - `sktime/utils/tests/test_warnings.py`: Added a new test file to verify that `_custom_showwarning` in `_SuppressWarningPattern` emits warnings without recursion. - `sktime/transformations/series/tests/test_summarize.py`: Added a new test `test_summarize_no_lossy_setitem` to confirm that `SummaryTransformer.fit` does not raise `LossySetitemError`. ### Related - Investigated in PyCaret PR [#4150](pycaret/pycaret#4150) ### Verification Tested locally with PyCaret and sktime, resolving the crash in the `test_blend_model_predict` test. The change in `summarize.py` ensures compatibility with pandas 2.x while maintaining efficiency with `copy=False`.
@celestinoxp: This is so sweet. Thank you for your excellent work on this. 🌻 |
…etitemError` in `SummaryTransformer` (sktime#7903) ### Issue The `_custom_showwarning` method in `sktime/utils/warnings.py` causes infinite recursion when handling certain warnings (e.g., pandas `LossySetitemError`), resulting in a `RecursionError: maximum recursion depth exceeded`. Additionally, in `sktime/transformations/series/summarize.py`, the line `func_dict.loc[:, "window"] = func_dict["window"].astype("object")` throws a `LossySetitemError` in pandas 2.x due to incompatible type coercion. This issue was identified while using PyCaret with sktime, where tests failed with a crash in a joblib worker due to a `PicklingError` caused by excessive recursion. ### Solution - Modified the `_custom_showwarning` method in the `_SuppressWarningPattern` class to add a guard against recursion using an `_in_warning` flag, while preserving delegation to `original_showwarning`. - Fixed `SummaryTransformer` to use a type-safe conversion with `func_dict["window"] = func_dict["window"].astype("object", copy=False)`, avoiding the `LossySetitemError`. ### Changes - `sktime/utils/warnings.py`: Added protection against infinite recursion in the `_custom_showwarning` method of `_SuppressWarningPattern` using an `_in_warning` flag. - `sktime/transformations/series/summarize.py`: Replaced the problematic assignment with an explicit conversion of the `"window"` column to `object` using `copy=False` for greater efficiency. - `sktime/utils/tests/test_warnings.py`: Added a new test file to verify that `_custom_showwarning` in `_SuppressWarningPattern` emits warnings without recursion. - `sktime/transformations/series/tests/test_summarize.py`: Added a new test `test_summarize_no_lossy_setitem` to confirm that `SummaryTransformer.fit` does not raise `LossySetitemError`. ### Related - Investigated in PyCaret PR [sktime#4150](pycaret/pycaret#4150) ### Verification Tested locally with PyCaret and sktime, resolving the crash in the `test_blend_model_predict` test. The change in `summarize.py` ensures compatibility with pandas 2.x while maintaining efficiency with `copy=False`.
…etitemError` in `SummaryTransformer` (sktime#7903) ### Issue The `_custom_showwarning` method in `sktime/utils/warnings.py` causes infinite recursion when handling certain warnings (e.g., pandas `LossySetitemError`), resulting in a `RecursionError: maximum recursion depth exceeded`. Additionally, in `sktime/transformations/series/summarize.py`, the line `func_dict.loc[:, "window"] = func_dict["window"].astype("object")` throws a `LossySetitemError` in pandas 2.x due to incompatible type coercion. This issue was identified while using PyCaret with sktime, where tests failed with a crash in a joblib worker due to a `PicklingError` caused by excessive recursion. ### Solution - Modified the `_custom_showwarning` method in the `_SuppressWarningPattern` class to add a guard against recursion using an `_in_warning` flag, while preserving delegation to `original_showwarning`. - Fixed `SummaryTransformer` to use a type-safe conversion with `func_dict["window"] = func_dict["window"].astype("object", copy=False)`, avoiding the `LossySetitemError`. ### Changes - `sktime/utils/warnings.py`: Added protection against infinite recursion in the `_custom_showwarning` method of `_SuppressWarningPattern` using an `_in_warning` flag. - `sktime/transformations/series/summarize.py`: Replaced the problematic assignment with an explicit conversion of the `"window"` column to `object` using `copy=False` for greater efficiency. - `sktime/utils/tests/test_warnings.py`: Added a new test file to verify that `_custom_showwarning` in `_SuppressWarningPattern` emits warnings without recursion. - `sktime/transformations/series/tests/test_summarize.py`: Added a new test `test_summarize_no_lossy_setitem` to confirm that `SummaryTransformer.fit` does not raise `LossySetitemError`. ### Related - Investigated in PyCaret PR [sktime#4150](pycaret/pycaret#4150) ### Verification Tested locally with PyCaret and sktime, resolving the crash in the `test_blend_model_predict` test. The change in `summarize.py` ensures compatibility with pandas 2.x while maintaining efficiency with `copy=False`.
PyCaret is not compatible with the latest versions of its dependencies, as development has been stalled for a long time. To address this, a strategy is proposed to resume development in a controlled manner.
Strategy:
sktime>=0.31,<0.32
, to prevent newer, incompatible versions (e.g.,0.36
) from being installed and causing errors.This PR starts by downgrading key dependencies to their last known compatible versions and will evolve as the codebase is brought up to date.