RustPyNet is designed to bridge the gap between Python and Rust, offering a Python operations processing pool that integrates seamlessly with the PyO3 crate.
- You can see the crate in: https://crates.io/crates/RustPyNet/
- And the crate docs in: https://docs.rs/RustPyNet/0.1.3/RustPyNet/
The primary goal of RustPyNet is to address the limitations posed by Python's Global Interpreter Lock (GIL). By facilitating multi-threaded operations, RustPyNet allows for parallel execution of Python functions, even though it's bound to a single interpreter. This makes it particularly suitable for scenarios where the bulk of the workload is handled by Rust, but there's a need to execute smaller tasks in Python.
Key Features:
- Bypass GIL Mechanism: Enables parallel execution of Python code sections that would otherwise be limited by the GIL.
- Thread-Safe Python Object Transfer: Facilitates the transfer of Python objects between threads.
- Procedural Macros: Simplifies the integration of Python into Rust code with procedural macros that auto-index to the Python pool.
- Efficient for Medium-Small Tasks: Optimized for tasks that have a light Python workload but are heavy on the Rust side.
To get started with RustPyNet, you'll first need to import the necessary modules:
use RustPyNet::python_pool::pool::MyResult,
use RustPyNet::python_pool::pool::PythonTask;
use RustPyNet::python_pool::pool::PythonTaskResult;
use RustPyNet::python_pool::pool::PythonTaskContext;
use RustPyNet::python_pool::pool::PythonTaskQueue;
use RustPyNet::python_pool::pool::PythonTaskError;
use RustPyNet::run_with_py;
use std::sync::mpsc::Sender;Here's a basic multithreading example that demonstrates how to use RustPyNet:
#[run_with_py]
fn compute_sum(context: PythonTaskContext) -> Result<PythonTaskResult, PythonTaskError> {
// Sample Python code: compute the sum of 1 + 2
let sum: i32 = py.eval("1 + 2", None, None)?.extract()?;
Ok(PythonTaskResult::Int(sum))
}
fn main() {
// Initialize the Python interpreter
pyo3::prepare_freethreaded_python();
// Start processing tasks in a separate thread
std::thread::spawn(move || {
start_processing_host_python_tasks();
});
std::thread::sleep(std::time::Duration::from_secs(2)); // Whait pool initialize!
const NUM_TESTS: usize = 10;
let (tx, rx) = std::sync::mpsc::channel();
let handles: Vec<_> = (0..NUM_TESTS)
.map(|_| {
let tx = tx.clone();
let context = PythonTaskContext::None;
std::thread::spawn(move || {
let result = compute_sum(&context);
tx.send(result).unwrap();
})
})
.collect();
let mut correct_responses = 0;
for _ in 0..NUM_TESTS {
let result = rx.recv().unwrap();
match result {
Ok(PythonTaskResult::Int(value)) => {
println!("The int is: {}", value);
if value == 3 {
correct_responses += 1;
}
}
Ok(PythonTaskResult::Float(value)) => {
println!("The float is: {}", value);
}
Ok(PythonTaskResult::Str(value)) => {
println!("The string is: {}", value);
}
Ok(PythonTaskResult::Map(value)) => {
println!("The map is: {:?}", value);
}
Ok(PythonTaskResult::List(value)) => {
println!("The list is: {:?}", value);
}
Ok(PythonTaskResult::Bool(value)) => {
println!("The bool is: {}", value);
}
Ok(PythonTaskResult::Error(value)) => {
println!("The Error is: {}", value);
}
Ok(PythonTaskResult::None) => {
println!("None");
}
Err(PythonTaskError::PythonError(err)) => println!("Python error: {}", err),
Err(PythonTaskError::UnsupportedNumberType) => {
println!("Error: Unsupported number type")
}
Err(PythonTaskError::UnsupportedValueType) => println!("Error: Unsupported value type"),
Err(PythonTaskError::OtherError(err)) => println!("Other error: {}", err),
// ... handle other variants of PythonTaskResult and error variants ...
}
}
for handle in handles {
handle.join().unwrap();
}
if correct_responses == NUM_TESTS {
println!("All responses are correct!");
} else {
println!(
"{} out of {} responses are correct",
correct_responses, NUM_TESTS
);
}
}In the above example, the compute_sum function is decorated with the #[run_with_py] attribute, allowing it to execute Python code within a Rust function. The function calculates the sum of two numbers using Python and returns the result.
For a more comprehensive example, including error handling and multi-threading, refer to the provided code snippet.
graph TD
C[Print: Start processing python calls!]
D[Send Results via Channel]
subgraph Global[Global]
style Global stroke:#FF4FFF, fill:#FF4FFF,fill-opacity:0.1
A[Static Def]
B[Tasks Global]
A --> B
end
subgraph SeparateThread[Separate Thread]
style SeparateThread stroke:#a14FFF, fill:#a14FFF ,fill-opacity:0.1
E[Acquire Python task queue]
F[Get Tasks]
G[Tasks in queue?]
H[Acquire GIL and get Python instance]
I[Execute task]
J[Print: Task successfully executed.]
K[Error]
L[Sleep for 100ms]
M[End]
C --> E
E --> F
F --> G
G --> |Yes| H
H --> I
I -->|Ok| J
I -->|Err| K
J --> G
J --> |response| D
K --> G
G --> |No| L
L --> E
E --> |try lock| B
B --> |lock| E
K --> |error| D
end
subgraph MainThread[Main Thread]
style MainThread stroke:#11B2FF, fill:#11B2FF, fill-opacity:0.1
O[Call Wrapped Fn]
P[Acquire Python task queue]
T[Receive Results via Channel] --> S
D --> |channel| T
O --> P
Q[Lock On Global Tasks] --> |try lock| B
P --> Q
B --> |lock| Q
Q --> |lock| R
R[Enqueue Task]
S[Wait Response]
R --> S
R --> |Taks| Q
S --> |Response| O
end
License RustPyNet is licensed under the Apache-2.0 license or the MIT license, at your option.
Python is licensed under the Python License.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in RustPyNet by you, as defined in the Apache License, shall be dual-licensed as above, without any additional terms or conditions.