JuliaPy / JuliaPy/PythonCall.jl

Compatibility Issue with Python 3.12.6

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Description

Compatibility Issue with Python 3.12.6

I encountered a JuliaError when trying to fit the PySRRegressor model using the PythonCall package. The error seems to be related to the compatibility of the PythonCall package with Python version 3.12.6.

Steps to Reproduce:
1- Install Python 3.12.6.
2- Install the pysr package using pip install pysr.
3- Run the following code:

import numpy as np
from pysr import PySRRegressor

# Sample data
X = np.random.rand(100, 1) # 100 samples, 1 feature
y = 3.0 * X[:, 0] + 2.0 # Example target

# Initialize PySR model
model = PySRRegressor(
niterations=100, # Number of iterations
binary_operators=["+", "-", "*", "/"], # Allowed binary operators
unary_operators=["sin", "exp", "log"], # Allowed unary operators
loss="L2", # Loss function (mean squared error)
populations=10, # Number of populations
procs=4, # Number of CPU cores to use
parsimony=0.01, # Encourages simpler equations
maxsize=20, # Maximum size of the equation
)

# Fit the model
model.fit(X, y)

# View the best equation
print("Best equation:", model.sympy())

# View the Hall of Fame (top equations)
print(model)
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Expected Behavior: The PySRRegressor model should fit the data without any errors, and the best equation should be printed.

Actual Behavior: The following error occurs:
JuliaError Traceback (most recent call last)
Cell In[34], [line 22](vscode-notebook-cell:?execution_count=34&line=22)
[10](vscode-notebook-cell:?execution_count=34&line=10) model = PySRRegressor(
[11](vscode-notebook-cell:?execution_count=34&line=11) niterations=100, # Number of iterations
[12](vscode-notebook-cell:?execution_count=34&line=12) binary_operators=["+", "-", "*", "/"], # Allowed binary operators
(...)
[18](vscode-notebook-cell:?execution_count=34&line=18) maxsize=20, # Maximum size of the equation
[19](vscode-notebook-cell:?execution_count=34&line=19) )
[21](vscode-notebook-cell:?execution_count=34&line=21) # Fit the model
---> [22](vscode-notebook-cell:?execution_count=34&line=22) model.fit(X, y)
[24](vscode-notebook-cell:?execution_count=34&line=24) # View the best equation
[25](vscode-notebook-cell:?execution_count=34&line=25) print("Best equation:", model.sympy())

File c:\Users\Administrator\AppData\Local\Programs\Python\Python312\Lib\site-packages\pysr\sr.py:2279, in PySRRegressor.fit(self, X, y, Xresampled, weights, variable_names, complexity_of_variables, X_units, y_units, category)
[2276](file:///C:/Users/Administrator/AppData/Local/Programs/Python/Python312/Lib/site-packages/pysr/sr.py:2276) self._checkpoint()
[2278](file:///C:/Users/Administrator/AppData/Local/Programs/Python/Python312/Lib/site-packages/pysr/sr.py:2278) # Perform the search:
-> [2279](file:///C:/Users/Administrator/AppData/Local/Programs/Python/Python312/Lib/site-packages/pysr/sr.py:2279) self._run(X, y, runtime_params, weights=weights, seed=seed, category=category)
[2281](file:///C:/Users/Administrator/AppData/Local/Programs/Python/Python312/Lib/site-packages/pysr/sr.py:2281) # Then, after fit, we save again, so the pickle file contains
[2282](file:///C:/Users/Administrator/AppData/Local/Programs/Python/Python312/Lib/site-packages/pysr/sr.py:2282) # the equations:
[2283](file:///C:/Users/Administrator/AppData/Local/Programs/Python/Python312/Lib/site-packages/pysr/sr.py:2283) if not self.temp_equation_file:

File c:\Users\Administrator\AppData\Local\Programs\Python\Python312\Lib\site-packages\pysr\sr.py:1889, in PySRRegressor._run(self, X, y, runtime_params, weights, category, seed)
[1886](file:///C:/Users/Administrator/AppData/Local/Programs/Python/Python312/Lib/site-packages/pysr/sr.py:1886) if isinstance(complexity_of_variables, list):
[1887](file:///C:/Users/Administrator/AppData/Local/Programs/Python/Python312/Lib/site-packages/pysr/sr.py:1887) complexity_of_variables = jl_array(complexity_of_variables)
...
@ PythonCall.JlWrap C:\Users\Administrator\.julia\packages\PythonCall\Nr75f\src\JlWrap\module.jl:13
[5] _pyjl_callmethod(f::Any, self_::Ptr{PythonCall.C.PyObject}, args_::Ptr{PythonCall.C.PyObject}, nargs::Int64)
@ PythonCall.JlWrap C:\Users\Administrator\.julia\packages\PythonCall\Nr75f\src\JlWrap\base.jl:67
[6] _pyjl_callmethod(o::Ptr{PythonCall.C.PyObject}, args::Ptr{PythonCall.C.PyObject})
@ PythonCall.JlWrap.Cjl C:\Users\Administrator\.julia\packages\PythonCall\Nr75f\src\JlWrap\C.jl:63
.
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Environment:
-Python version: 3.12.6
-julia version: 1.11.2
-pysr version: 1.3.1
-juliacall version: 0.9.23
-Operating System: [Windows 11 64-bit]
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.
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julia> Base.versioninfo()
ERROR: UndefVarError: `versioninfo` not defined in `Base`
Suggestion: check for spelling errors or missing imports.
Stacktrace:
[1] getproperty(x::Module, f::Symbol)
@ Base .\Base.jl:42
[2] top-level scope
@ REPL[1]:1
.
.
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julia> Pkg.status()
ERROR: UndefVarError: `Pkg` not defined in `Main`
Suggestion: check for spelling errors or missing imports.
Stacktrace:
[1] top-level scope
@ REPL[2]:1
.
.
.
julia> versioninfo()
Julia Version 1.11.2
Commit 5e9a32e7af (2024-12-01 20:02 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: Windows (x86_64-w64-mingw32)
CPU: 16 × AMD Ryzen 7 4800H with Radeon Graphics
WORD_SIZE: 64
LLVM: libLLVM-16.0.6 (ORCJIT, znver2)
Threads: 1 default, 0 interactive, 1 GC (on 16 virtual cores)
Environment:
JULIA_PATH = "D:\Backup\Downloads\julia-1.11.2-win64.exe"
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Additional Information: I have verified that the JULIA_PATH environment variable is set correctly and that Julia is accessible from the command line. The issue seems to be specific to the compatibility of the PythonCall package with Python 3.12.6.

Guide de contribution

Aucun guide de contribution indexé pour ce dépôt

Piste de recherche

Start by reproducing the supplied PySRRegressor example with the listed Python, Julia, PySR, and juliacall versions on Windows 11, then inspect the PythonCall traceback and compatibility information. Done means the example completes model.fit and prints the best equation without the reported JuliaError, with the relevant compatibility behavior documented or covered by an appropriate test.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Évaluation

Stack technique
julia, python
Domaine
tooling
Type d'issue
Bug
Difficulté
4/5
Temps estimé
3-5 jours
Activité
À l'abandon
Clarté
À clarifier
Accessibilité débutants
30/100

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