Expand description
Conversions to and from indexmap’s
IndexMap
.
[indexmap::IndexMap
] is a hash table that is closely compatible with the standard std::collections::HashMap
,
with the difference that it preserves the insertion order when iterating over keys. It was inspired
by Python’s 3.6+ dict implementation.
Dictionary order is guaranteed to be insertion order in Python, hence IndexMap is a good candidate for maintaining an equivalent behaviour in Rust.
§Setup
To use this feature, add this to your Cargo.toml
:
[dependencies]
# change * to the latest versions
indexmap = "*"
pyo3 = { version = "0.23.0-dev", features = ["indexmap"] }
Note that you must use compatible versions of indexmap and PyO3. The required indexmap version may vary based on the version of PyO3.
§Examples
Using indexmap to return a dictionary with some statistics about a list of numbers. Because of the insertion order guarantees, the Python code will always print the same result, matching users’ expectations about Python’s dict.
use indexmap::{indexmap, IndexMap};
use pyo3::prelude::*;
fn median(data: &Vec<i32>) -> f32 {
let sorted_data = data.clone().sort();
let mid = data.len() / 2;
if data.len() % 2 == 0 {
data[mid] as f32
}
else {
(data[mid] + data[mid - 1]) as f32 / 2.0
}
}
fn mean(data: &Vec<i32>) -> f32 {
data.iter().sum::<i32>() as f32 / data.len() as f32
}
fn mode(data: &Vec<i32>) -> f32 {
let mut frequency = IndexMap::new(); // we can use IndexMap as any hash table
for &element in data {
*frequency.entry(element).or_insert(0) += 1;
}
frequency
.iter()
.max_by(|a, b| a.1.cmp(&b.1))
.map(|(k, _v)| *k)
.unwrap() as f32
}
#[pyfunction]
fn calculate_statistics(data: Vec<i32>) -> IndexMap<&'static str, f32> {
indexmap! {
"median" => median(&data),
"mean" => mean(&data),
"mode" => mode(&data),
}
}
#[pymodule]
fn my_module(m: &Bound<'_, PyModule>) -> PyResult<()> {
m.add_function(wrap_pyfunction!(calculate_statistics, m)?)?;
Ok(())
}
Python code:
from my_module import calculate_statistics
data = [1, 1, 1, 3, 4, 5]
print(calculate_statistics(data))
# always prints {"median": 2.0, "mean": 2.5, "mode": 1.0} in the same order
# if another hash table was used, the order could be random