pyproject.toml

[build-system]
requires = ["setuptools>=67.0", "wheel", "setuptools_scm[toml]>=6.2"]
build-backend = "setuptools.build_meta"

[tool.setuptools.package-data]
"vectordb_bench.results" = ["*.json"]

[project]
name = "vectordb-bench"
authors = [
  {name="XuanYang-cn", email="xuan.yang@zilliz.com"},
]
description = "VectorDBBench is not just an offering of benchmark results for mainstream vector databases and cloud services, it's your go-to tool for the ultimate performance and cost-effectiveness comparison. Designed with ease-of-use in mind, VectorDBBench is devised to help users, even non-professionals, reproduce results or test new systems, making the hunt for the optimal choice amongst a plethora of cloud services and open-source vector databases a breeze."

readme = "README.md"
requires-python = ">=3.11"
classifiers = [
    "Programming Language :: Python :: 3",
    "License :: OSI Approved :: MIT License",
    "Operating System :: OS Independent",
]
dependencies = [
    "pytz",
    "streamlit-autorefresh",
    "streamlit>=1.23.0",
    "streamlit_extras",
    "tqdm",
    "s3fs",
    "psutil",
    "polars",
    "plotly",
    "environs",
    "pydantic<v2",
    "scikit-learn",
    "pymilvus", # with pandas, numpy, ujson
]
dynamic = ["version"]

[project.optional-dependencies]
test = [
    "ruff",
    "pytest",
]

all = [
    "grpcio==1.53.0", # for qdrant-client and pymilvus
    "grpcio-tools==1.53.0", # for qdrant-client and pymilvus
    "qdrant-client",
    "pinecone-client",
    "weaviate-client",
    "elasticsearch",
    "pgvector",
    "sqlalchemy",
    "redis",
    "chromadb",
]

qdrant = [ "qdrant-client" ]
pinecone = [ "pinecone-client" ]
weaviate = [ "weaviate-client" ]
elastic = [ "elasticsearch" ]
pgvector = [ "pgvector", "sqlalchemy" ]
redis = [ "redis" ]
chromadb = [ "chromadb" ]

[project.urls]
"repository" = "https://github.com/zilliztech/VectorDBBench"

[project.scripts]
init_bench = "vectordb_bench.__main__:main"

[tool.setuptools_scm]