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mahmoud
glom
Python2018–2025
mahmoud / glom

glom

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

4Distinct people
4Mentions
0Explicit recommenders
2.2KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

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

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year4 dated mentions

Observed mentions: 2018-05-09 23:51:35 UTC to 2025-02-26 05:39:21 UTC.

012018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC101
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC110

What Hacker News says

4 sources
Reminds me of glom[1], another Python library that allows for traversing dicts using dot notation. >>> data = {'a': {'b': {'c': 'd'}}} >>> glom(data, 'a.b.c') 'd' Box uses a slightly different approach. >>> data = Box({'a': {'b': {'c': 'd'}}}) >>> data.a.b.c 'd' I didn't see anything in the README about type inference, which would make the later example more desirable in my opinion. Otherwise I would prefer not to introduce a new container class to my code (Box) if avoidable. [1] https://github.com/mahmoud/glom
In Box: Python dictionaries with advanced dot notation access
This is great recommendation, you can get very far by reading well written code. These have very well written Python, exposing much of the language expressiveness: - https://github.com/python-attrs/attrs - https://github.com/mahmoud/glom - https://github.com/pytoolz/toolz - https://github.com/Suor/funcy - https://github.com/dabeaz/curio ps: dabaez has great educational content on writing idiomatic python, definitely worth checking out An honorable mention of norvig's classic essays, which got me into python while I was in college, over 12y ago: https://norvig.com/spell-correct.html. Aside from reading code, _writing_ something that you know it exist (e.g glom) and then comparing it to how others have done it is also a great learning experience.
In Ask HN: How can I get better at writing production-level Python?

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