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pcarbonn
pyDatalog
Python2019–2025
pcarbonn / pyDatalog

pyDatalog

a datalog implementation in Python

3Distinct people
3Mentions
0Explicit recommenders
328GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

a datalog implementation in Python

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, 5:04:57 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 year3 dated mentions

Observed mentions: 2019-03-19 04:21:43 UTC to 2025-08-12 20:53:53 UTC.

012019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20192020-01-01 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 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20222023-01-01 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): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 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
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101
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 UTC000
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101

What Hacker News says

3 sources
> Datalog/Prolog as a sub-language > And I’d like to be able to call into this pure declarative logic from an imperative shell that handles all the messy stuff. Is that too much to ask? There is at least one pure Python implementation of Datalog sitting on PIP, pyDatalog[1][2]. It's not part of the standard library, but it's one PIP install and one import away. So this item is one of the lowest hanging fruit in the wishlist, at least for Python. [1] https://github.com/pcarbonn/pyDatalog [2] https://pypi.org/project/pyDatalog
In A few programming language features I'd like to see (2023)
With RDF* and SPARQL* ("RDF-star" and "SPARQL-star") how are triple (or quad) stores still distinct from property graphs? RDFS and SHACL (and OWL) are optional in a triple store, which expects the subject and predicate to be string URIs, and there is an object datatype and optional language: (?s ?p ?o <datatype> [lang]) (?subject:URI, ?predicate:URI, ?object:datatype, object_datatype, [object_language]) RDFS introduces rdfs:domain and rdfs:range type restrictions for Properties, and rdfs:Class and rdfs:subClassOf. `a` means `rdf:type`; which does not require RDFS: ("#xyz", a, "https://schema.org/Thing") ("#xyz", rdf:type, "https://schema.org/Thing") Quad stores have a graph_id string URI "?g" for Named Graphs: (?g ?s ?p ?o) ("https://example.org/ns/graphs/0", "#xyz", a, "https://schema.org/Thing") ("https://examp
Read the rest
le.org/ns/graphs/1", "#xyz", a, "https://schema.org/ScholarlyArticle") There's a W3C CG (Community Group) revising very many of the W3C Linked Data specs to support RDF-star: https://www.w3.org/groups/wg/rdf-star Looks like they ended up needing to update basically most of the current specs: https://www.w3.org/groups/wg/rdf-star/tools "RDF-star and SPARQL-star" (Draft Community Group Report; 08 December 2022) https://w3c.github.io/rdf-star/cg-spec/editors_draft.html GH topics: rdf-star, rdfstar: https://github.com/topics/rdf-star, https://github.com/topics/rdfstar pyDatalog does datalog with SQLAlchemy and e.g. just the SQLite database: https://github.com/pcarbonn/pyDatalog ; and it is apparently superseded by IDP-Z3: https://gitlab.com/krr/IDP-Z3/ From https://twitter.com/westurner/status/1000516851984723968 : > A feature comparison of SQL w/ EAV, SPARQL/SPARUL, [SPARQL12 SPARQL-star, [T-SPARQL, SPARQLMT,]], Cypher, Gremlin, GraphQL, and Datalog would be a useful resource for evaluating graph query languages. > I'd probably use unstructured text search to identify the relevant resources first.
In Introduction to Datalog

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