# Parallelism
CPython has an infamous GIL(Global Interpreter Lock) prevents developers
getting true parallelism. With `pyo3` you can release GIL when executing
Rust code to achieve true parallelism.
The [`Python::allow_threads`](https://docs.rs/pyo3/0.2.7/struct.Python.html#method.allow_threads)
method temporarily releases the GIL, thus allowing other Python threads to run.
```rust,ignore
impl Python {
pub fn allow_threads<T, F>(self, f: F) -> T where F: Send + FnOnce() -> T {}
}
```
Let's take a look at our [word-count](https://github.com/PyO3/pyo3/blob/master/examples/word-count/src/lib.rs) example,
we have a `wc_parallel` function utilize the [rayon](https://github.com/nikomatsakis/rayon) crate to count words in parallel.
```rust,ignore
fn wc_parallel(lines: &str, search: &str) -> i32 {
lines.par_lines()
.map(|line| wc_line(line, search))
.sum()
}
```
Then in the Python bridge, we have a function `search` exposed to Python runtime which calls `wc_parallel` inside
`Python::allow_threads` method to enable true parallelism:
```rust,ignore
#[pymodinit]
fn word_count(py: Python, m: &PyModule) -> PyResult<()> {
#[pyfn(m, "search")]
fn search(py: Python, path: String, search: String) -> PyResult<i32> {
let mut file = File::open(path)?;
let mut contents = String::new();
file.read_to_string(&mut contents)?;
let count = py.allow_threads(move || wc_parallel(&contents, &search));
Ok(count)
}
Ok(())
}
```
## Benchmark
Let's benchmark the `word-count` example to verify that we did unlock true parallelism with `pyo3`.
We are using `pytest-benchmark` to benchmark three word count functions:
1. [Pure Python version](https://github.com/PyO3/pyo3/blob/master/examples/word-count/word_count/__init__.py#L9)
2. [Rust sequential version](https://github.com/PyO3/pyo3/blob/master/examples/word-count/src/lib.rs#L64)
3. [Rust parallel version](https://github.com/PyO3/pyo3/blob/master/examples/word-count/src/lib.rs#L54)
Benchmark script can be found [here](https://github.com/PyO3/pyo3/blob/master/examples/word-count/tests/test_word_count.py),
then we can run `pytest tests` to benchmark them.
On MacBook Pro (Retina, 15-inch, Mid 2015) the benchmark gives:
