Affects: PythonCall
Describe the bug
I am trying to use PythonCall.jl to call the Python interface to CP-SAT, which is a popular constraint programming library from Google's OR-Tools toolkit. The problem is that the memory that gets allocated when creating a Python object from that interface is never automatically freed.
A function createmodel() is used to create a CpModel object`, which goes out of scope after the function terminates. Each time the function is executed, the memory gets fuller, until eventually the Julia process gets killed. The expected behavior is that at some point before Julia gets killed, the memory that was allocated for objects that are out of scope should get released.
Here are the steps to reproduce a MWE, assuming the environment already has PythonCall.jl and CondaPkg.jl:
Add OR-Tools to the environment and import it:
using PythonCall, CondaPkg
] conda pip_add ortools
cp_model = pyimport("ortools.sat.python.cp_model")
Define the function that will create and initialize a CpModel object:
createmodel() = let
model = cp_model.CpModel() # create model
variables = [model.new_int_var(0,1, "x_" * string(i)) for i in 1:100] # add variables to the model
model.add_allowed_assignments(variables, [rand(0:1, 100) for _ in 1:200000]) # add constraints over those variables
return nothing
end
Repeatedly call createmodel() and observe that the memory usage keeps going up until the Julia process gets killed.
createmodel()
createmodel()
createmodel()
# ... if you keep calling createmodel(), eventually the memory gets full
Your system
Please provide detailed information about your system:
Additional context
- Calling
PythonCall.pydel!(model) and/or for v in variables PythonCall.pydel!(v) end inside the body of the function does not have any visible effect
- Executing
GC.gc() after the function calls has the effect that at least part of the allocated memory gets freed, but sometimes this does not happen if it is executed only once.
- Calling the equivalent code directly from Python works as expected, i.e. the memory gets freed after the function terminates. Here is the Python version:
from ortools.sat.python import cp_model
import random
def createmodel():
model = cp_model.CpModel()
variables = [model.new_int_var(0,1, f"x_{i}") for i in range(100)]
model.add_allowed_assignments(variables, [[random.randint(0,1) for _ in range(100)] for _ in range(200000)])
return None
createmodel()
createmodel()
createmodel()
# ... if you keep calling createmodel(), the memory never gets full
Affects: PythonCall
Describe the bug
I am trying to use PythonCall.jl to call the Python interface to CP-SAT, which is a popular constraint programming library from Google's OR-Tools toolkit. The problem is that the memory that gets allocated when creating a Python object from that interface is never automatically freed.
A function
createmodel()is used to create aCpModelobject`, which goes out of scope after the function terminates. Each time the function is executed, the memory gets fuller, until eventually the Julia process gets killed. The expected behavior is that at some point before Julia gets killed, the memory that was allocated for objects that are out of scope should get released.Here are the steps to reproduce a MWE, assuming the environment already has PythonCall.jl and CondaPkg.jl:
Add OR-Tools to the environment and import it:
Define the function that will create and initialize a
CpModelobject:Repeatedly call
createmodel()and observe that the memory usage keeps going up until the Julia process gets killed.Your system
Please provide detailed information about your system:
Operating System: Fedora Linux 43
Python version: 3.14.3
versioninfo()Additional context
PythonCall.pydel!(model)and/orfor v in variables PythonCall.pydel!(v) endinside the body of the function does not have any visible effectGC.gc()after the function calls has the effect that at least part of the allocated memory gets freed, but sometimes this does not happen if it is executed only once.