murr-python

Async Python client for murr, a RocksDB-based NVMe/S3 cache for AI inference workloads.

The client is pure Python: it talks to a murr server over HTTP, with Arrow IPC for data and JSON for schemas. Version 0.3.x of the client needs a 0.3.x server.

Install

pip install murr

Quickstart

Start a server:

docker run -p 8080:8080 ghcr.io/murrdb/murr:0.3.0

and then:

import asyncio

import pyarrow as pa
from murr.client import Client, ColumnSchema, DType, TableSchema


async def main():
    async with Client("http://localhost:8080") as db:
        await db.create_table("docs", TableSchema(columns={
            "id":       ColumnSchema(dtype=DType.UTF8, nullable=False, key=True),
            "score":    ColumnSchema(dtype=DType.FLOAT32),
            "category": ColumnSchema(dtype=DType.UTF8),
        }))

        await db.write("docs", pa.table({
            "id":       ["doc_1", "doc_2", "doc_3"],
            "score":    pa.array([0.95, 0.72, 0.68], pa.float32()),
            "category": ["ml", "infra", "ops"],
        }))

        result = await db.read("docs", {"id": ["doc_3", "doc_1"]}, columns=["score", "category"])
        print(result.to_pandas())


asyncio.run(main())

read returns a pyarrow.Table with the requested columns. Row i answers key i, and a key which is not in the table gives a row of nulls.

API

All methods are coroutines. There is no blocking client: wrap a call in asyncio.run if you need one.

Schemas

A column has a dtype, and optional nullable (default True), key (default False) and strict (default True) flags. Supported dtypes are utf8, bool, int8 to int64, uint8 to uint64, float32 and float64.

A table needs at least one key column. Key columns must be nullable=False and of a utf8 or integer dtype. Several key columns form a compound key:

schema = TableSchema(columns={
    "user":  ColumnSchema(dtype=DType.UTF8,  nullable=False, key=True),
    "item":  ColumnSchema(dtype=DType.INT64, nullable=False, key=True),
    "score": ColumnSchema(dtype=DType.FLOAT64),
})

await db.create_table("ratings", schema)
await db.read("ratings", {"user": ["u1", "u2"], "item": [1, 7]}, columns=["score"])

Keys

Keys go to the server as an Arrow table with one column per key column. Pass a pa.Table, a pa.RecordBatch, or a {name: values} mapping which is turned into a table with pa.table().

The server widens types (an int32 array is fine for an int64 key) but never narrows them. Python ints become int64, so a narrower key column needs a typed array:

await db.read("events", {"id": pa.array([1, 2], pa.int32())}, columns=["flag"])

The same holds for writes, with one addition: writing float64 values into a float32 column rounds them, and is only accepted for a column created with strict=False.

Errors

Server errors are raised as subclasses of MurrError, which carries the HTTP status_code and the server message:

Development

uv sync --extra dev
uv run pytest tests/ -v

The tests start ghcr.io/murrdb/murr:0.3.0 in Docker through testcontainers. Set MURR_IMAGE to test against another image, or MURR_ENDPOINT to use a server which is already running.

Releases

Set version in pyproject.toml and push a matching v<version> tag, like v0.3.0. The release workflow runs the tests, checks that the tag matches the package version, publishes the sdist and wheel to PyPI, and then creates a GitHub release.

License

Apache-2.0.