Rustine

High-performance Gel syntax parser that transforms unstructured text into JSON, XML, or YAML. A complete Rust rewrite of Python Gelatin, usable as a native Python module, a Rust library, or a standalone CLI tool.

Why Rustine?

Gelatin has been a reliable tool for converting network device output and other semi-structured text into structured data. However, its core dependency — SimpleParse — has not been updated for Python 3.12+ and is no longer maintained. This made Gelatin incompatible with modern Python versions.

Rustine solves this by reimplementing the entire Gelatin engine in Rust:

• Drop-in replacement — same Gel grammar language, same output format
• 10–19× faster than Python Gelatin (depending on workload and platform)
• 3–4× less memory on large inputs
• Works on Python 3.9–3.13+ via PyO3 — no C extension dependency
• 100% feature parity with the original Python implementation

Quick Start

Python

pip install rustine

from Rustine import rustine

grammar = r"""
define nl /\r?\n/
define ws /\s+/

grammar input:
    match 'Name:' ws /[^\r\n,]+/ /(?:\r?\n|,) */:
        out.open('user')
        out.add_attribute('.', 'name', '$2')
    match /[\w ]+/ ':' ws /[^\r\n,]+/ /(?:\r?\n|,) */:
        out.add('$0', '$3')
    match nl:
        do.return()
"""

input_text = "Name: Alice\nAge: 30\nOffice: 1st Ave\n"
print(rustine.parse_to_json(grammar, input_text))

Rust

cargo add rustine --no-default-features

use rustine::exec::{execute, serialize_execution, RuntimeFormat};

let result = execute(grammar_source, input_text);
let json = serialize_execution(&result, RuntimeFormat::Json);

CLI

cargo install rustine --features cli

rgel -s syntax.gel -f json input.txt
rgel -s syntax.gel -f xml  input.txt
rgel -s syntax.gel -f yaml input.txt

Performance

Benchmarked on 20.9 MB real-world IOS XR configuration (263 grammars, 113 regex patterns, 899 757 output nodes):

Tool / Platform	Time	Throughput	Peak RSS
Python Gelatin (Win)	66.3 s	0.33 MB/s	3 075 MB
Rustine (Win)	4.10 s	5.1 MB/s	496 MB
Rustine (jemalloc)	2.31 s	9.1 MB/s	456 MB

Comparison	Speedup
Rustine vs Python Gelatin (scale)	17–19×
Rustine vs Python Gelatin (CLI)	11–13×
Rustine vs textfsm (25 MB)	1.6×

See BENCHMARKS.md for full cross-platform results (Windows, Linux glibc, Linux jemalloc), serialization timings, and reproduction instructions.

Alternatives

Tool	Approach	Output	vs Rustine
textfsm	Line-by-line FSM templates	Flat tables (list of dicts)	Simpler for quick extraction; no hierarchy, no nesting, pure Python
TTP	Template-based parsing	Nested dicts	Flexible templates; Python-only, slower on large inputs
Napalm	Device abstraction + textfsm	Flat dicts per getter	Higher-level (device drivers); not a general text parser
PyATS/Genie	Model-driven parsing	Structured models	Cisco ecosystem; heavy dependencies, not general-purpose
nom / pest	Rust parser combinators / PEG	Custom AST	Maximum flexibility; requires writing a parser in code, no DSL file

Rustine's niche: a grammar-driven text→tree transformer with a concise DSL (.gel files), hierarchical output, and native performance. It sits between simple template extractors (textfsm) and full parser generators (nom/pest).

Feature Highlights

• Gel grammar language — match, imatch, when, skip, define, grammar inheritance
• Rich output actions — create, add, replace, add_attribute, open, enter, leave, set_root_name
• Trigger system — enqueue_before/after/on_add/on_leave (single-shot and persistent)
• Captures — positional ($1, $2) and named ($name) with interpolation in paths and values
• Three output formats — JSON, XML, YAML
• Streaming execution — feed chunks incrementally via StreamingRunner
• Structured errors — GelError with source spans (line, column, offset)
• Semantic validation — regex pre-validation, inheritance checks, undefined grammar/variable warnings
• Python bindings — PyO3 + maturin, installable via pip
• CLI tool — rgel binary for shell pipelines

Cargo Features (compile-time)

Features are selected at build time via --features and control which capabilities are compiled into the binary. See Getting Started → Cargo Features for the full table and usage examples.

Key features: cli, jemalloc (default in Linux wheels), mimalloc, mmap, parallel, python (default).

Documentation

Document	Description
Getting Started	Installation, first steps, Python/Rust/CLI usage
Gel Syntax Reference	Grammar language, statements, actions, triggers
Architecture	Parser pipeline, module layout, design decisions
Performance	Optimization techniques, benchmark overview
BENCHMARKS.md	Raw benchmark data for all platforms
Migration from Gelatin	Drop-in replacement guide, parity notes
Contributing	Development setup, coding guidelines, PR process
Changelog	Version history

License

Dual-licensed under MIT or Apache-2.0.