Installer fst avec Homebrew

Liens du projet

• Page d'accueil

Commandes et alias

• fst

Historique du projet

The public repository was created in 2015. The README describes fst as a fast implementation of ordered sets and maps using finite state machines, specifically finite state transducers that map keys to values as the machine is executed.

The crate documentation emphasizes very large key sets and maps, including billions of byte-string keys, with a design focus on memory-efficient operations and searchable compact storage.

Historique d'adoption

fst became part of the Rust package ecosystem through crates.io and docs.rs documentation, while the supplied package data records downstream operating-system packaging in Homebrew, Debian, Ubuntu, and Nix.

The README documents normal Rust dependency usage through Cargo.toml and points to docs.rs for examples and API reference, making it usable as a library as well as through the packaged fst executable.

Modes d'utilisation

The library builds ordered sets or maps and supports fast search operations over the resulting automata. The README example builds an in-memory set and runs a Levenshtein fuzzy query.

The documentation also connects fst to regex-automata through implementations of the fst::Automata trait, allowing deterministic automata to search transducers produced by the crate.

Pourquoi les passionnés de paquets s'y intéressent

fst is significant because it turned a specialized data structure into a reusable Rust package with practical package-manager reach. It is especially interesting to search, indexing, and CLI-data users who care about memory-mapped, compact dictionaries rather than database-sized dependencies.

Chronologie

• 2015: Public GitHub repository created.
• 2015: README documented the project as a Rust implementation of compact ordered sets and maps using finite state transducers.
• 2026: docs.rs listed fst 0.4.7 with full crate documentation.

Related projects

• The README links to regex-automata as an integration point for automata-based search.
• The README also points to the author's transducers article for background, examples, and experiments around large automata-backed indexes.

Sources

• https://api.github.com/repos/BurntSushi/fst
• https://docs.rs/fst
• https://docs.rs/fst/latest/fst/
• https://github.com/BurntSushi/fst
• https://raw.githubusercontent.com/BurntSushi/fst/master/README.md