kraph
The python client for kraph, the Arkitekt knowledge graph service built around Apache AGE: recording claims about entities, events, measurements and metrics, backed by the structures (images, tables, …) that are evidence for them, and drawing them into graphs.
Installation
pip install kraph
With arkitekt, pip install "arkitekt[rekuest,kraph]" brings it in.
Concepts
- Claims — an entity exists, a structure measures it, two things are related — are recorded under a term, a word your organization owns, never under a graph. Retracting a claim records a position rather than deleting anything.
- Graphs are views. A graph declares categories (entity, relation, measurement, event, …) that say what its words mean, and draws the claims made under those words.
Usage
Every kraph operation is a method of the Kraph client, in a blocking and an a-prefixed async
flavour (kraph.create_graph(...), await kraph.acreate_graph(...)). What a call returns remembers
the client, so follow-ups from a result go through the same client.
In an arkitekt app
Add the service to your app and ask for kraph: Kraph; the client is injected by annotation.
Graphs, categories, structures, metrics, terms and more travel between actions by id
(@kraph/graph, @kraph/entitycategory, @kraph/structure, @kraph/term, …), so an action can
take and return them directly:
from arkitekt import App, run
from kraph import Kraph, kraph_service
app = App("neuron-claims", "0.1.0", services=[kraph_service])
@app.action
def claim_neuron(kraph: Kraph) -> str:
"""Claim Neuron
Records that a neuron exists.
"""
asserted = kraph.assert_entity_exists(
term="Neuron", supporting_evidence=[], derived_from=[], same_as=[]
)
return asserted.instance.id
if __name__ == "__main__":
run(app)
From a script
from arkitekt import easy
from kraph import kraph_service
with easy("my-script", kraph_service) as kraph:
graph = kraph.create_graph(name="Neurons", backfill=False)
kraph.create_entity_category(
key="Neuron",
ontology_references=[],
property_definitions=[],
graph=graph.id,
backfill=True,
)
asserted = kraph.assert_entity_exists(
term="Neuron", supporting_evidence=[], derived_from=[], same_as=[]
)
print(asserted.is_drawn) # True: the graph declares "Neuron", so it draws the claim
Testing
uv run pytest -m "not integration" # no server needed
uv run pytest -m integration # a real kraph via dokker
See RELEASING.md for how versions are cut.
1 maintainer
Metadata
1 maintainer
Release files for kraph 4.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| kraph-4.1.0.tar.gz | 109.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| kraph-4.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 224.5 kB
Release files / kraph-4.1.0.tar.gz
| Download URL | kraph-4.1.0.tar.gz |
|---|---|
| Size | 109.8 kB |
| Tags | Source |
|
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Release files / kraph-4.1.0-py3-none-any.whl
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| Tags | Python 3 |
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