kumo_relational_engine
The Kumo Relational driver for the kumo-relational-client client.
This distribution provides the heavy, client-side machinery a Kumo Relational prediction
needs before a request reaches a NIM: the relational Graph/Table abstractions,
the neighbor samplers (local native relationallib, plus DuckDB / SQLite / Snowflake /
Databricks / PostgreSQL backends), the PQL parser, and the HTTP client that talks to a Universal
TFM NIM.
It is imported as kumo_relational_engine and is normally installed transitively via the client's
relational extra rather than on its own:
pip install kumo-relational-client[relational] # pulls the kumo_relational_engine driver
It can also be installed on its own, for the graph, sampler and PQL machinery.
Predicting is not available that way: the engine's entry points refuse a direct
call, so a prediction has to go through kumo-relational-client.
pip install kumo-relational-engine
# optional data backends:
pip install "kumo-relational-engine[duckdb]" # or [sqlite] / [snowflake] / [databricks] / [postgres]
# optional features:
pip install "kumo-relational-engine[explain]" # natural-language explanation summaries
pip install "kumo-relational-engine[relbench]" # Graph.from_relbench() dataset loading
pip install "kumo-relational-engine[codegen]" # regenerate the TFM API client (see scripts/)
Graph.from_postgres() reads existing PostgreSQL tables:
import psycopg
from kumo_relational_client import relational
connection = psycopg.connect(
host=host,
dbname=database,
user=user,
password=credential,
sslmode='require',
)
graph = relational.Graph.from_postgres(connection, schema='public')
schema is the table namespace; omit it to use current_schema() (public is
the usual default). connection may instead be a PostgreSQL URI/libpq string
or a dictionary of psycopg arguments; if omitted, psycopg uses PG* environment
variables. See postgres.py. Lakebase uses this same
API through its PostgreSQL endpoint with TLS and either an OAuth token or an
enabled native Postgres password. It reads existing tables directly—without
Unity Catalog registration, copying data, or DDL.
Temporal sampling returns at most the requested latest N rows at or before each
anchor, ordered by time descending then primary key ascending. For large fact
tables, an index on (foreign_key, time_column DESC, primary_key) improves this
pushed-down query; the SDK never creates indexes or modifies source tables.
Release wheels are built for CPython 3.10, 3.11, 3.12 and 3.13 on Linux
x86-64 and ARM64 (manylinux_2_28), macOS 11 and later on Intel and Apple
silicon, and Windows x64. Windows on ARM64 has no wheel, and no source
distribution is published.
Application code should import the client's neutral surface, not this package directly:
from kumo_relational_client import RelationalClient, relational
graph = relational.Graph.from_data({'users': df1, 'items': df2, 'orders': df3})
with RelationalClient(url='http://localhost:8000') as client:
result = client.relational(graph).predict(
'PREDICT SUM(orders.price, 0, 30, days) FOR items.item_id=1'
)
Local development
pip install -e ".[test,databricks]"
pytest tests -m "not live_nim"
The live-NIM suite (scripts/run_rfm_nim_live_tests.sh --full) includes durable,
ticket-free rejection regressions for fixed NIM defects; every rejection probe is
followed by a known-good prediction to detect service degradation.
The native neighbor sampler (kumo_relational_engine.relationallib) is built from
src/kumo_relational_engine/csrc/neighbor_sampler.cpp via CMake/scikit-build-core. Set
WITH_RELATIONALLIB=0 to skip the native build for a pure-Python editable install.
1 maintainer
Metadata
1 maintainer
Release files for kumo-relational-engine 1.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 28.5 MB
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| Size | 1.4 MB |
| Tags | CPython 3.10 Linux glibc 2.26+ ARM64 Linux glibc 2.28+ ARM64 |
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| Tags | CPython 3.10 macOS 11.0+ x86-64 |
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| Size | 1.4 MB |
| Tags | CPython 3.10 macOS 11.0+ ARM64 |
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