# mahmoud/glom

☄️ Python's nested data operator (and CLI), for all your declarative restructuring needs. Got data? Glom it! ☄️

Repository: https://github.com/mahmoud/glom
Canonical: https://ross.abutalabs.com/products/glom
Homepage: https://glom.readthedocs.io
Language: Python
License: NOASSERTION
License Family: other
Topics: declarative, data, recursion, python, utilities, cli, nested-structures, data-transformation, apis, dictionaries
Last push: 2026-07-17T18:49:45+00:00

## Health v2 (maintenance only)
Score: 74/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 93, release rhythm 35, longevity 100
- inputs: {"age_days": 3059, "days_push": 47, "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 2163, forks 77 (observed 2026-08-28T04:06:21.164076+00:00)

## What it is
glom is a Python library and CLI for declaratively accessing, transforming, and restructuring nested data structures like dicts, lists, and objects. It provides path-based access with readable error messages and a command-line tool for working with JSON, YAML, TOML, and Python data.

## Use cases
- extract nested fields from  api responses
- transform deeply nested dictionaries in python
- query  files from the command line
- restructure nested data declaratively
- get better error messages when accessing missing nested keys
- flatten and reshape nested config data
- debug and explore nested data structures interactively

## When to choose
- you frequently access or reshape deeply nested dicts, lists, or objects in Python
- you want declarative, reusable data transformation specs instead of chained indexing
- you need a quick CLI to query and transform JSON/YAML/TOML files
- unclear errors from nested key access are slowing you down

## When to avoid
- your data is flat or only one level deep - plain dict access is simpler
- you need high-performance bulk ETL over huge datasets
- you prefer schema validation libraries like pydantic for structuring data
- you're working outside the Python ecosystem

## Facets
- artifact type: library
- maturity: active
- function: serialization, cli, developer-tools
- domain: developer-tools, apis
- platform: python, cli, cross-platform
- tags: nested-data, data-transformation, declarative, path-access, yaml, toml, data-engineering, command-line

## Member repositories
- mahmoud/glom (main) score 74

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:21.164076+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 2026-08-30T02:50:12.274458+00:00, confidence not recorded.
  - readme: https://github.com/mahmoud/glom (fetched 2026-08-28T04:06:21.164076+00:00, sha 297644ae10a5)
  - registry_pypi: https://pypi.org/pypi/glom/json (fetched 2026-08-29T10:30:25.001364+00:00, sha 3372e83d542d)
- Data as of 2026-08-30T08:39:29.467469+00:00.