pygrok
A Python library to parse strings and extract information from structured/unstructured data
Decision gist · record as of 2026-08-14
No. The package is dormant (last release 2016-09-24, no activity since 2023-11-22) and has high install friction due to the regex module dependency. While it solves a real problem, the lack of maintenance and Python version uncertainty make it risky for new projects. Consider active alternatives like regex-based parsing libraries or modern log-parsing frameworks.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- The regex module must be installed and may require a C compiler on some platforms; Python version compatibility is unspecified.
- High install friction: the package is dormant (last release 2016-09-24, no commits since 2023-11-22) and requires the regex module as a runtime dependency, which may have compilation requirements on some systems.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you can use, modify, and distribute this package freely with minimal restrictions.
last release 2016-09-24 (3611 days) · last repo commit 2023-11-22 · 286 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 98,424 downloads/mo, #13,085 on PyPI
Alternatives
Verify before relying
pip install pygrok
from pygrok import Grok
text = 'gary is male, 25 years old and weighs 68.5 kilograms'
pattern = '%{WORD:name} is %{WORD:gender}, %{NUMBER:age:int} years old and weighs %{NUMBER:weight:float} kilograms'
grok = Grok(pattern)
result = grok.match(text)
print(result) # {'name': 'gary', 'gender': 'male', 'age': 25, 'weight': 68.5}- Whether the regex module dependency is pre-compiled or requires a C compiler on your platform.
- Python version compatibility: requires_python is unspecified in the fact sheet.
- Whether dormancy affects real-world reliability for production log parsing workloads.
What it is and what it does
pygrok is a Python library that implements Grok-style pattern matching for parsing and extracting data from strings. Instead of writing complex regular expressions, you define patterns using named capture groups like `%{WORD:name}` and `%{NUMBER:age:int}`, and the library handles the underlying regex matching. It comes with a library of pre-built patterns for common data types (IP addresses, timestamps, log formats, etc.) and supports type conversion during extraction.
The package is built on top of the regex module (not Python's built-in re) because it needs atomic grouping syntax that the standard library doesn't support. It's most useful for log parsing, structured data extraction from semi-formatted text, and situations where you want readable, maintainable pattern definitions instead of dense regex strings.
Use it for
- Parse application or system logs to extract fields like timestamps, log levels, and messages into structured records.
- Extract key-value pairs from semi-structured text (e.g., 'name is gary, age 25') without hand-writing regex.
- Convert matched string values to specific types (int, float) during extraction in a single step.
- Build data pipelines that need to normalize and structure incoming text data before storage or analysis.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No.
The package is dormant (last release 2016-09-24, no activity since 2023-11-22) and has high install friction due to the regex module dependency. While it solves a real problem, the lack of maintenance and Python version uncertainty make it risky for new projects. Consider active alternatives like regex-based parsing libraries or modern log-parsing frameworks.
Install
pygrok on PyPI
Before you install
High install friction: the package is dormant (last release 2016-09-24, no commits since 2023-11-22) and requires the regex module as a runtime dependency, which may have compilation requirements on some systems.
The regex module must be installed and may require a C compiler on some platforms; Python version compatibility is unspecified.
License in practice
MIT license is permissive; you can use, modify, and distribute this package freely with minimal restrictions.
Quickstart
pip install pygrok
from pygrok import Grok
text = 'gary is male, 25 years old and weighs 68.5 kilograms'
pattern = '%{WORD:name} is %{WORD:gender}, %{NUMBER:age:int} years old and weighs %{NUMBER:weight:float} kilograms'
grok = Grok(pattern)
result = grok.match(text)
print(result) # {'name': 'gary', 'gender': 'male', 'age': 25, 'weight': 68.5}Verify before relying
- Whether the regex module dependency is pre-compiled or requires a C compiler on your platform.
- Python version compatibility: requires_python is unspecified in the fact sheet.
- Whether dormancy affects real-world reliability for production log parsing workloads.
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | High. Source build required |
| Runtime dependencies | None |
| Maintenance | Dormant 3,611 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 98,424 / month, #13,085 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: pygrok-1.0.0.tar.gz
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