Alopex Python バインディング

Python から AlopexDB を操作するためのバインディングです。
Database/Transaction の基本機能に加え、ベクトル検索（numpy）と Unity Catalog 互換の Catalog API（polars）を提供します。

インストール

pip install alopex

Catalog API (polars) を使う場合:

pip install alopex[polars]

開発中は maturin を利用できます。

maturin develop -m crates/alopex-py/pyproject.toml

オプション依存:

  • numpy を使う場合: pip install alopex[numpy]
  • polars を使う場合: pip install alopex[polars]

対応バージョン

依存関係 対応バージョン
Python 3.8+
Polars 0.20+ (Catalog API)
NumPy 1.20+ (Vector API)

基本的な使い方

Database / Transaction

from alopex import Database, TxnMode

db = Database.new()

with db.begin(TxnMode.READ_WRITE) as txn:
    txn.put(b"user:1", b"alice")
    txn.commit()

with db.begin(TxnMode.READ_ONLY) as txn:
    value = txn.get(b"user:1")
    print(value)

db.close()

ベクトル検索（numpy 必須）

import numpy as np
from alopex import Database, Metric, TxnMode

db = Database.new()
with db.begin(TxnMode.READ_WRITE) as txn:
    vec = np.array([1.0, 0.0, 0.0], dtype=np.float32)
    txn.upsert_vector(b"k1", None, vec, Metric.COSINE)
    results = txn.search_similar(vec, Metric.COSINE, 1, return_vectors=True)
    print(results[0].key, results[0].score)
    if results[0].vector is not None:
        print(results[0].vector.dtype, results[0].vector.shape)

NumPy 入出力とゼロコピー条件（v0.3.5）

入力（Python → Rust）:

  • dtype: float32 が優先。float64 は float32 に変換して処理します。
  • layout: C-contiguous が優先。非連続（strided/Fortran order 等）は C-contiguous に変換して処理します。
  • ゼロコピー入力: float32 かつ C-contiguous の場合は Rust 側でコピーなしに参照します。

出力（Rust → Python）:

  • Transaction.search_similar(..., return_vectors=True) の場合、SearchResult.vector に numpy.ndarray[float32] を含められます。
  • Transaction.search_similar(..., zero_copy_return=True) / Transaction.get_vector(..., zero_copy_return=True) の場合、可能なら所有権移譲によるゼロコピー返却を行います（False の場合はコピー）。

GIL:

  • upsert_vector / search_similar / search_hnsw は重い処理中に GIL を解放します。

HNSW インデックス（numpy 必須）

import numpy as np
from alopex import Database, HnswConfig, TxnMode

db = Database.new()
db.create_hnsw_index("idx", HnswConfig(2))

with db.begin(TxnMode.READ_WRITE) as txn:
    vec = np.array([1.0, 0.0], dtype=np.float32)
    txn.upsert_to_hnsw("idx", b"k1", vec, None)
    txn.commit()

results, stats = db.search_hnsw("idx", np.array([1.0, 0.0], dtype=np.float32), 1)
print(stats.node_count)

Catalog API（polars 必須）

import polars as pl
from alopex import Catalog, ColumnInfo

Catalog.create_catalog("main")
Catalog.create_namespace("main", "default")

columns = [ColumnInfo("id", "int", 0, False)]
Catalog.create_table("main", "default", "users", columns, "/tmp/users.parquet")

df = pl.DataFrame({"id": [1, 2], "name": ["a", "b"]})
Catalog.write_table(
    df,
    "main",
    "default",
    "users",
    delta_mode="overwrite",
    storage_location="/tmp/users.parquet",
)

lazy_frame = Catalog.scan_table("main", "default", "users")
print(lazy_frame.collect())

注意事項

  • numpy / polars が未インストールの場合、対応 API は AlopexError を返します。
  • Phase 1 では Parquet のみ対応しています。

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.8.13)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for asopitech from gravatar.com asopitech

License

Apache Software License (Apache-2.0)

Requires

Python >=3.8

Provides Extra

dev full numpy polars

Tags

database vector bindings

Classifiers

Report project as malware

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