# google/textfsm

Python module for parsing semi-structured text into python tables.

Repository: https://github.com/google/textfsm
Canonical: https://ross.abutalabs.com/products/textfsm
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2025-04-17T04:16:34+00:00

## Health v2 (maintenance only)
Score: 42/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 17, release rhythm 40, longevity 100
- inputs: {"age_days": 4090, "days_push": 503, "days_rel": 503, "gap_med": 26, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1246, forks 195 (observed 2026-08-28T04:04:07.220858+00:00)

## What it is
TextFSM is a Python module implementing a template-based state machine for parsing semi-structured text into Python tables. It was originally developed at Google to programmatically access information from networking device CLI output.

## Use cases
- parse cli output from network devices
- convert semi-structured text into tables
- extract fields from command responses
- parse router and switch command output
- build reusable text parsing templates
- scrape structured data from plain text logs

## When to choose
- you need to parse repetitive, semi-structured text like network device CLI output
- you want template-driven parsing with reusable rule files
- you need tabular records from unstructured command responses

## When to avoid
- you need to parse well-structured formats like JSON, XML, or YAML
- you need full natural language parsing rather than pattern-based extraction
- your text formats vary wildly with no consistent structure

## Facets
- artifact type: library
- maturity: active
- function: parser, developer-tools
- domain: parsers, developer-tools, networking
- platform: python, cross-platform
- tags: text-parsing, state-machine, network-automation, template-based, cli-output-parsing

## Member repositories
- google/textfsm (main) score 42

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:07.220858+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 2026-08-30T05:08:03.439195+00:00, confidence not recorded.
  - readme: https://github.com/google/textfsm (fetched 2026-08-28T04:04:07.220858+00:00, sha 91580fe6659f)
  - registry_pypi: https://pypi.org/pypi/textfsm/json (fetched 2026-08-29T12:19:21.925444+00:00, sha 7ed91c0b65c1)
- Data as of 2026-08-30T08:39:29.467469+00:00.