Feedback From Calling Rust From Python
In my previous post, comments mentioned pyo3 and how I should use it. In this post, I explain what it is and how I migrated my code.
Join the DZone community and get the full member experience.
Join For FreeI got plenty of feedback on my post about Calling Rust from Python:
Many comments mentioned pyo3
, and I should use it instead of cooking my own. Thanks to the authors, I checked: in this post, I explain what it is and how I migrated my code.
What Is pyo3?
Rust bindings for Python, including tools for creating native Python extension modules. Running and interacting with Python code from a Rust binary is also supported.
Indeed, pyo3
fits my use case, calling Rust from Python. Even better, it handles converting Python types to Rust types and back again. Finally, it offers the maturin
utility to make the interaction between the Python project and the Rust project seamless.
Maturin
Build and publish crates with pyo3, rust-cpython, cffi and uniffi bindings as well as rust binaries as python packages.
maturin
is available via pip install
. It offers several commands:
new
: create a new Cargo project with maturin configuredbuild
: build the wheels and store them locallypublish
: build the crate into a Python package and publish it to pypidevelop
: build the crate as a Python module directly into the current virtual environment, making it available to Python
Note that Maturin started as a companion project to pyo3
but now offers rust-cpython, cffi and uniffi bindings.
Migrating the Project
The term migrating is a bit misleading here since we will start from scratch to fit Maturin's usage. However, we will achieve the same end state. I won't paraphrase the tutorial since it works seamlessly. Ultimately, we have a fully functional Rust project with a single sum_as_string()
function, which we can call in a Python shell. Note the dependency to pyo3
:
pyo3 = "0.20.0"
The second step is to re-use the material from the previous project. First, we add our compute()
function at the end of the lib.rs
file:
#[pyfunction] //1
fn compute(command: &str, a: Complex<f64>, b: Complex<f64>) -> PyResult<Complex<f64>> { //2-3
match command {
"add" => Ok(a + b),
"sub" => Ok(a - b),
"mul" => Ok(a * b),
_ => Err(PyValueError::new_err("Unknown command")), //4
}
}
- The
pyfunction
macro allows the use of the function in Python - Use regular Rust types for parameters;
pyo3
can convert them - We need to return a
PyResult
type, which is an alias overResult
- Return a specific Python error if the command doesn't match
pyo3
automatically handles conversion for most types. However, complex numbers require an additional feature. We also need to migrate from the num
crate to the num-complex
:
pyo3 = { version = "0.20.0" , features = ["num-complex"]}
num-complex = "0.4.4"
To convert custom types, you must implement traits FromPyObject
for parameters and ToPyObject
for return values.
Finally, we only need to add the function to the module:
#[pymodule]
fn rust_over_pyo3(_py: Python, m: &PyModule) -> PyResult<()> {
m.add_function(wrap_pyfunction!(sum_as_string, m)?)?;
m.add_function(wrap_pyfunction!(compute, m)?)?; //1
Ok(())
}
- Add the function to the module
At this point, we can use Maturin to test the project:
maturin develop
After the compilation finishes, we can start a Python shell in the virtual environment:
python
>>> from rust_over_pyo3 import compute
>>> compute('add',1+3j,-5j)
(1-2j)
>>> compute('sub',1+3j,-5j)
(1+8j)
Finishing Touch
The above setup allows us to use Rust from a Python shell but not in a Python file. To leverage the default, we must create a Python project inside the Rust project, whose name matches the Rust module name. Since I named my lib rust_over_pyo3
, here's the overall structure:
my-project ├── Cargo.toml ├── rust_over_pyo3 │ └── main.py ├── pyproject.toml └── src └── lib.rs
To use the Rust library in Python, we need first to build the library.
maturin build --release
We manually move the artifact from /target/release/maturin/librust_over_pyo3.dylib
to rust_over_pyo3.so
under the Python package. We can also run cargo build --release
instead; in this case, the source file is directly under /target/release
.
At this point, we can use the library as any other Python module:
from typing import Optional
from click import command, option
from rust_over_pyo3 import compute #1
@command()
@option('--add', 'command', flag_value='add')
@option('--sub', 'command', flag_value='sub')
@option('--mul', 'command', flag_value='mul')
@option('--arg1', help='First complex number in the form x+yj')
@option('--arg2', help='Second complex number in the form x\'+y\'j')
def cli(command: Optional[str], arg1: Optional[str], arg2: Optional[str]) -> None:
n1: complex = complex(arg1)
n2: complex = complex(arg2)
result: complex = compute(command, n1, n2) #2
print(result)
if __name__ == '__main__':
cli()
- Regular Python import
- Look, ma, it works!
Conclusion
In this post, I improved the low-level integration with ctypes
to the generic ready-to-use pyo3
library. I barely scratched the surface, though; pyo3
is a powerful, well-maintained library with plenty of features.
I want to thank everyone who pointed me in this direction.
The complete source code for this post can be found on GitHub.
To Go Further
Published at DZone with permission of Nicolas Fränkel, DZone MVB. See the original article here.
Opinions expressed by DZone contributors are their own.
Comments