# VerbalExpressions/PythonVerbalExpressions

Python regular expressions made easy

Repository: https://github.com/VerbalExpressions/PythonVerbalExpressions
Canonical: https://ross.abutalabs.com/products/pythonverbalexpressions
Language: Python
License Family: other
Last push: 2024-04-28T16:22:05+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4787, "days_push": 857, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1633, forks 111 (observed 2026-08-28T04:05:14.235061+00:00)

## What it is
A Python library providing a fluent, chainable API for building regular expressions without writing raw regex syntax. It is part of the multi-language VerbalExpressions family and compiles to standard Python re patterns.

## Use cases
- build regex patterns without writing regex syntax
- validate URLs with readable code
- find and replace text using chainable expressions
- compile verbal expressions into standard re regex objects
- teach regular expressions to beginners

## When to choose
- you want readable, maintainable pattern matching instead of cryptic regex strings
- you need to construct simple to moderate regexes programmatically
- you are teaching or learning how regular expressions work

## When to avoid
- you need complex regex features like lookaheads, backreferences, or named groups
- performance-critical matching where raw compiled regex is preferable
- you already are comfortable writing raw regular expressions

## Facets
- artifact type: library
- maturity: maintenance
- function: parser, developer-tools
- domain: developer-tools, programming-languages, text-editors
- platform: python, cross-platform
- tags: regex, fluent-api, regular-expressions, string-matching, pattern-building

## Member repositories
- VerbalExpressions/PythonVerbalExpressions (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:14.235061+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:47:19.756262+00:00, confidence not recorded.
  - readme: https://github.com/VerbalExpressions/PythonVerbalExpressions (fetched 2026-08-28T04:05:14.235061+00:00, sha 3bbf77da9bf5)
- Data as of 2026-08-30T08:39:29.467469+00:00.