# Pons
[](https://github.com/jdh8/pons)
[](https://crates.io/crates/pons)
[](https://docs.rs/pons)
This library provides tools for analyzing and simulating hands in the card
game contract bridge. It is named after [an anatomical part of the
brainstem][pons] and also "bridge" in Latin.
[pons]: https://en.wikipedia.org/wiki/Pons
## Modules
- [`bidding`](https://docs.rs/pons/latest/pons/bidding/) — [`Call`], [`Auction`], and a [`Trie`]-based representation of a bidding system.
- [`deck`](https://docs.rs/pons/latest/pons/deck/) — card sets, shuffling, and iterators that fill in partial deals.
- [`eval`](https://docs.rs/pons/latest/pons/eval/) — hand-evaluation kernels (HCP, shortness, LTC, NLTC, BUM-RAP, Fifths, Zar).
- [`stats`](https://docs.rs/pons/latest/pons/stats/) — numerically stable accumulators and double-dummy par scoring over histograms.
## Feature flags
- `serde` — derive `Serialize`/`Deserialize` for the library's value types. Off by default.
## Quick start
Deal 10 random hands and evaluate the North hand with several point counts:
```rust
use pons::{full_deal, eval};
use pons::eval::HandEvaluator;
use dds_bridge::Seat;
let mut rng = rand::rng();
for _ in 0..10 {
let deal = full_deal(&mut rng);
let north = deal[Seat::North];
let hcp: u8 = eval::SimpleEvaluator(eval::hcp).eval(north);
let nltc: f64 = eval::NLTC.eval(north);
let zar: u8 = eval::zar(north);
println!("{} HCP={hcp} NLTC={nltc} Zar={zar}", deal.display(Seat::North));
}
```
Estimate NS par from random fill-in deals (requires `dds-bridge`'s solver,
linked via `dds-bridge-sys` in `dev-dependencies`; see
[`examples/average-ns-par`](examples/average-ns-par/main.rs)):
```rust
use pons::{deck, stats};
use dds_bridge::{Builder, Hand, Seat};
use dds_bridge::solver::{self, NonEmptyStrainFlags, Vulnerability};
# let north_hand: Hand = "T9762.AT54.JT75.".parse().unwrap();
# let south_hand: Hand = "A.KQ962.A86.Q642".parse().unwrap();
let cards = Builder::new()
.north(north_hand)
.south(south_hand)
.build_partial()
.expect("north and south hands are disjoint and ≤13 each");
let solutions = solver::Solver::lock().solve_deals(
&deck::fill_deals(&mut rand::rng(), cards).take(90).collect::<Vec<_>>(),
NonEmptyStrainFlags::ALL,
);
let par = stats::average_ns_par(
solutions.into_iter().collect(),
Vulnerability::NONE,
Seat::North,
);
```
## Examples
The [`examples/`](examples/) directory has runnable programs:
- `generate-deals` — stream random deals to stdout.
- `notrump-tricks` — average tricks taken in notrump per hand feature.
- `check-nltc` and `check-zar` — validate hand-evaluation methods against double-dummy results.
- `average-ns-par` — Monte-Carlo NS par score for a partial deal.
Run any of them with `cargo run --example <name>`.
## MSRV
Pons currently requires Rust **1.93**. The CI matrix builds and tests on the
MSRV toolchain on Ubuntu, macOS, and Windows.
[`Call`]: https://docs.rs/pons/latest/pons/bidding/enum.Call.html
[`Auction`]: https://docs.rs/pons/latest/pons/bidding/struct.Auction.html
[`Trie`]: https://docs.rs/pons/latest/pons/bidding/trie/struct.Trie.html