Frequently Asked Questions / Troubleshooting

I'm experiencing deadlocks using PyO3 with lazy_static or once_cell!

lazy_static and once_cell::sync both use locks to ensure that initialization is performed only by a single thread. Because the Python GIL is an additional lock this can lead to deadlocks in the following way:

1. A thread (thread A) which has acquired the Python GIL starts initialization of a lazy_static value.
2. The initialization code calls some Python API which temporarily releases the GIL e.g. Python::import.
3. Another thread (thread B) acquires the Python GIL and attempts to access the same lazy_static value.
4. Thread B is blocked, because it waits for lazy_static's initialization to lock to release.
5. Thread A is blocked, because it waits to re-aquire the GIL which thread B still holds.
6. Deadlock.

PyO3 provides a struct GILOnceCell which works equivalently to OnceCell but relies solely on the Python GIL for thread safety. This means it can be used in place of lazy_static or once_cell where you are experiencing the deadlock described above. See the documentation for GILOnceCell for an example how to use it.

I can't run cargo test: I'm having linker issues like "Symbol not found" or "Undefined reference to _PyExc_SystemError"!

Currently, #340 causes cargo test to fail with linking errors when the extension-module feature is activated. For now you can work around this by making the extension-module feature optional and running the tests with cargo test --no-default-features:

[dependencies.pyo3]
version = "version = "0.14.4""

[features]
extension-module = ["pyo3/extension-module"]
default = ["extension-module"]

I can't run cargo test: my crate cannot be found for tests in tests/ directory!

The Rust book suggests to put integration tests inside a tests/ directory.

For a PyO3 extension-module project where the crate-type is set to "cdylib" in your Cargo.toml, the compiler won't be able to find your crate and will display errors such as E0432 or E0463:

error[E0432]: unresolved import `my_crate`
 --> tests/test_my_crate.rs:1:5
  |
1 | use my_crate;
  |     ^^^^^^^^^^^^ no external crate `my_crate`

The best solution is to make your crate types include both rlib and cdylib:

# Cargo.toml
[lib]
crate-type = ["cdylib", "rlib"]

Ctrl-C doesn't do anything while my Rust code is executing!

This is because Ctrl-C raises a SIGINT signal, which is handled by the calling Python process by simply setting a flag to action upon later. This flag isn't checked while Rust code called from Python is executing, only once control returns to the Python interpreter.

You can give the Python interpreter a chance to process the signal properly by calling Python::check_signals. It's good practice to call this function regularly if you have a long-running Rust function so that your users can cancel it.

#[pyo3(get)] clones my field!

You may have a nested struct similar to this:

#![allow(unused)]
fn main() {
use pyo3::prelude::*;
#[pyclass]
#[derive(Clone)]
struct Inner { /* fields omitted */ }

#[pyclass]
struct Outer {
    #[pyo3(get)]
    inner: Inner,
}

#[pymethods]
impl Outer {
    #[new]
    fn __new__() -> Self {
        Self { inner: Inner {} }
    }
}
}

When Python code accesses Outer's field, PyO3 will return a new object on every access (note that their addresses are different):

outer = Outer()

a = outer.inner
b = outer.inner

assert a is b, f"a: {a}\nb: {b}"

AssertionError: a: <builtins.Inner object at 0x00000238FFB9C7B0>
b: <builtins.Inner object at 0x00000238FFB9C830>

This can be especially confusing if the field is mutable, as getting the field and then mutating it won't persist - you'll just get a fresh clone of the original on the next access. Unfortunately Python and Rust don't agree about ownership - if PyO3 gave out references to (possibly) temporary Rust objects to Python code, Python code could then keep that reference alive indefinitely. Therefore returning Rust objects requires cloning.

If you don't want that cloning to happen, a workaround is to allocate the field on the Python heap and store a reference to that, by using Py<...>:

#![allow(unused)]
fn main() {
use pyo3::prelude::*;
#[pyclass]
#[derive(Clone)]
struct Inner { /* fields omitted */ }

#[pyclass]
struct Outer {
    #[pyo3(get)]
    inner: Py<Inner>,
}

#[pymethods]
impl Outer {
    #[new]
    fn __new__(py: Python) -> PyResult<Self> {
        Ok(Self {
            inner: Py::new(py, Inner {})?,
        })
    }
}
}

This time a and b are the same object:

outer = Outer()

a = outer.inner
b = outer.inner

assert a is b, f"a: {a}\nb: {b}"
print(f"a: {a}\nb: {b}")

a: <builtins.Inner object at 0x0000020044FCC670>
b: <builtins.Inner object at 0x0000020044FCC670>

The downside to this approach is that any Rust code working on the Outer struct now has to acquire the GIL to do anything with its field.