match
Match tokenized words and phrases within the original, untokenized, often messy, text.
Decision gist · record as of 2026-08-14
Yes, if you need token-to-offset alignment and can tolerate an abandoned package. The core functionality is stable and no known vulnerabilities exist. However, consider maintenance risk: no updates since 2022-10-03, and any bugs in Unicode or edge-case handling will not be fixed. Suitable for one-off scripts or internal tools; risky for production systems requiring ongoing support.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires nltk and regex as runtime dependencies; Python >= 3.8 required.
- High install friction: the package is abandoned (last release 2022-10-03, last commit 2023-04-11) and depends on nltk and regex, which add non-trivial setup overhead.
- No maintenance activity for an extended period.
License · maintenance · safety
permissive license (permissive) — Licensed under Apache License 2.0 (permissive), allowing commercial and private use with minimal restrictions.
last release 2022-10-03 (1411 days) · last repo commit 2023-04-11 · 20 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,331,116 downloads/mo, #4,045 on PyPI
Alternatives
Verify before relying
pip install match
import match
result = match.match(original_text, ['token', 'sequence'])
# Returns: [(start_offset, end_offset, 'matched substring'), ...]- Whether nltk and regex versions have known incompatibilities or security issues affecting match's usability.
- Whether the abandoned status means critical bugs in Unicode or edge-case tokenization remain unfixed.
- Performance characteristics on very large texts or deeply nested tokenization structures.
What it is and what it does
Match is a utility for recovering the character offsets of tokenized words and phrases within their original, untokenized source text. Given a messy, whitespace-irregular, or Unicode-heavy source string and a sequence of tokens (or a single token), it returns all matching spans as (start, end, substring) tuples. This solves the alignment problem that arises when a tokenizer normalizes or splits text in ways that obscure the original character positions—essential for tasks like annotation, error correction, or mapping NLP pipeline outputs back to source documents.
The package handles common real-world messiness: irregular spacing, punctuation normalization (e.g., parentheses converted to -LRB- and -RRB-), and Unicode characters. It depends on nltk and regex for tokenization and pattern matching. The project is no longer actively maintained, with the last release in 2022-10-03 and no commits since 2023-04-11.
Use it for
- Recover source text spans for tokens output by an NLP tokenizer to annotate or highlight original text.
- Map named entity recognition or part-of-speech tags back to character offsets in messy source documents.
- Align corrected or normalized token sequences with their original positions for error analysis.
- Extract substring context around matched token sequences for debugging tokenization issues.
- Support document annotation workflows where token-level labels must be converted to character offsets.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need token-to-offset alignment and can tolerate an abandoned package.
The core functionality is stable and no known vulnerabilities exist. However, consider maintenance risk: no updates since 2022-10-03, and any bugs in Unicode or edge-case handling will not be fixed. Suitable for one-off scripts or internal tools; risky for production systems requiring ongoing support.
Install
match on PyPI
Before you install
High install friction: the package is abandoned (last release 2022-10-03, last commit 2023-04-11) and depends on nltk and regex, which add non-trivial setup overhead. No maintenance activity for an extended period.
Requires nltk and regex as runtime dependencies; Python >= 3.8 required.
License in practice
Licensed under Apache License 2.0 (permissive), allowing commercial and private use with minimal restrictions.
Quickstart
pip install match
import match
result = match.match(original_text, ['token', 'sequence'])
# Returns: [(start_offset, end_offset, 'matched substring'), ...]Verify before relying
- Whether nltk and regex versions have known incompatibilities or security issues affecting match's usability.
- Whether the abandoned status means critical bugs in Unicode or edge-case tokenization remain unfixed.
- Performance characteristics on very large texts or deeply nested tokenization structures.
Package facts
| License | permissive license permissive |
| Python support | Not specified |
| Install friction | High. Source build required |
| Runtime dependencies | None |
| Maintenance | Abandoned 1,411 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,331,116 / month, #4,045 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: Apache Software LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIXOperating System :: UnixProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Text Processing |
Evidence: match-0.3.2.tar.gz
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