The General Transit Feed Specification (GTFS) is a commonly used model to represent public transit data.

This crates brings serde structures of this model and helpers to read GTFS archives.

This crates has 2 main entry-points.

The most common one is to create a gtfs_structures::Gtfs:

// Gtfs::new will try to guess if you provide a path, a local zip file or a remote zip file.
// You can also use Gtfs::from_path or Gtfs::from_url
let gtfs = gtfs_structures::Gtfs::new("path_of_a_zip_or_directory_or_url")?;
println!("there are {} stops in the gtfs", gtfs.stops.len());

// This structure is the easiest to use as the collections are `HashMap`,
// thus you can access an object by its id.
let route_1 = gtfs.routes.get("1").expect("no route 1");
println!("{}: {:?}", route_1.short_name, route_1);

If you want a lower level model, you can use gtfs_structures::RawGtfs:

let raw_gtfs = RawGtfs::new("fixtures/basic").expect("impossible to read gtfs");
for stop in raw_gtfs.stops.expect("impossible to read stops.txt") {
    println!("stop: {}", stop.name);
}

Instead of easy to use HashMap, each collection is a Result with an error if something went wrong during the reading.

This makes it possible for example for a GTFS validator to display better error messages.

By default the feature 'read-url' is activated. It makes it possible to read a Gtfs from an url.

let gtfs = gtfs_structures::Gtfs::new("http://www.metromobilite.fr/data/Horaires/SEM-GTFS.zip")?;

Or you can use the explicit constructor:

let gtfs = gtfs_structures::Gtfs::from_url("http://www.metromobilite.fr/data/Horaires/SEM-GTFS.zip")?;

If you don't want the dependency to reqwest, you can remove this feature.

You need an up to date rust tool-chain (commonly installed with rustup).

Building is done with:

cargo build

You can also run the unit tests:

cargo test

And run the examples by giving their names:

cargo run --example gtfs_reading

If you are interested in transit data, you can also use the really nice crate transit_model that can also handle GTFS data.

The price to pay is a steeper learning curve (and a documentation that could be improved 🙄), but this crate provides very nice ergonomics to handle transit data and lots of utilities like data format conversions, datasets merge, ...