scnr2 Python Bindings
Python bindings for the scnr2 high-performance scanner generator crate, powered by PyO3.
Installation
You can install scnr2 directly from PyPI:
pip install scnr2
Local Development
To build and install it from source in your local environment, use maturin:
cd scnr2-python
uv run maturin develop
Basic Usage
The scnr2 module allows you to define a scanner using a declarative syntax similar to the Rust scanner! macro.
import scnr2
# Define your scanner
definition = """
MyScanner {
mode INITIAL {
token r"\d+" => 1; // Match digits (Token Type 1)
token r"[a-zA-Z_]\w*" => 2; // Match identifiers (Token Type 2)
token r"\s+" => 3; // Match whitespace (Token Type 3)
}
}
"""
scanner = scnr2.Scanner(definition)
# Scans the input and returns a list of matches
input_text = "123 abc_456"
matches = scanner.find_matches(input_text)
for m in matches:
print(f"Token {m.token_type}: '{m.text}' at [{m.start}:{m.end}]")
# With position information (line, column)
matches_pos = scanner.find_matches_with_position(input_text)
for m in matches_pos:
print(f"Token {m.token_type} at {m.start_line}:{m.start_column}")
Advanced Usage
scnr2 supports advanced features like Lookahead (positive and negative) to handle complex lexical structures.
Lookahead Example
import scnr2
definition = """
AdvancedScanner {
mode INITIAL {
// Match 'a' only if followed by 'b'
token r"a" followed by r"b" => 1;
// Match 'b' only if NOT followed by 'c'
token r"b" not followed by r"c" => 2;
token r"a" => 3;
token r"b" => 4;
token r"c" => 5;
}
}
"""
scanner = scnr2.Scanner(definition)
# Scans for patterns with lookahead constraints
text = "abc"
matches = scanner.find_matches(text)
# Token 1 will match 'a' in 'ab'
# Token 4 will match 'b' (because it IS followed by 'c', so Token 2 fails)
# Token 5 will match 'c'
Memory Management Note
The current version of the Python bindings uses Box::leak for runtime-generated DFA tables and matching logic to satisfy internal Rust lifetime requirements. While highly efficient for long-lived scanner instances, creating an extremely large number of unique Scanner objects in a single long-running process may result in memory growth. It is recommended to reuse Scanner instances whenever possible.
1 maintainer
Metadata
1 maintainer
Release files for scnr2 0.5.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| scnr2-0.5.3.tar.gz | 76.1 kB | With provenance | Details |
Built distributions (wheels)
Total release size: 177.3 MB
Release files / scnr2-0.5.3.tar.gz
| Download URL | scnr2-0.5.3.tar.gz |
|---|---|
| Size | 76.1 kB |
| Tags | Source |
|
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| Size | 583.1 kB |
| Tags | CPython 3.14 Windows x86-64 |
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| Tags | CPython 3.14 Linux glibc 2.17+ x86-64 |
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Transparency logRelease files / scnr2-0.5.3-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl
| Download URL | scnr2-0.5.3-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl |
|---|---|
| Size | 3.9 MB |
| Tags | CPython 3.8 Linux glibc 2.5+ x86-32 |
|
SHA-256 checksum How to use checksums |
bc7e27496f88fd27b254f3a156106b59ee06dcffb927f984d9b9ad0cc63df27e
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BLAKE2b-256 checksum How to use checksums |
54b661ae3aeddc8c01b563152fc6779235d175e2d36a5ba21d7d035d28f3c53e
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Transparency logSecurity for scnr2 0.5.3
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Attestation for scnr2-0.5.3.tar.gz
PyPI Publish Attestation
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Signed by GitHub Actions, verified by PyPI on Sep 7, 2026.
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