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NOTICE

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These contents may have been developed with support from one or more Intel-operated generative artificial intelligence solutions.

pyproject.toml

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[project]
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name = "svsbench"
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version = "0.1.0"
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description = "Benchmarking for Scalable Vector Search"
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readme = "README.md"
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authors = [
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{ name = "Mihai Capotă", email = "[email protected]" }
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]
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requires-python = ">=3.12"
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dependencies = [
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"hnswlib>=0.8.0",
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"numpy>=1.10",
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"pandas>=2",
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"scalable-vs>=0.0.6",
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"tqdm>=4.67",
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]
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classifiers = ["Private :: Do Not Upload"]
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[dependency-groups]
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dev = [
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"pytest>=8.3",
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"pytest-cov>=6.0.0",
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"ruff>=0.9.6",
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]
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[tool.ruff]
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line-length = 79

requirements.txt

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# This file was autogenerated by uv via the following command:
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# uv pip compile pyproject.toml -o requirements.txt
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archspec==0.2.5
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# via scalable-vs
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hnswlib==0.8.0
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# via svsbench (pyproject.toml)
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numpy==1.26.4
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# via
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# svsbench (pyproject.toml)
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# hnswlib
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# pandas
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# scalable-vs
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pandas==2.2.3
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# via svsbench (pyproject.toml)
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python-dateutil==2.9.0.post0
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# via pandas
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pytz==2025.1
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# via pandas
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scalable-vs==0.0.6
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# via svsbench (pyproject.toml)
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six==1.17.0
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# via python-dateutil
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toml==0.10.2
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# via scalable-vs
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tqdm==4.67.1
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# via svsbench (pyproject.toml)
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tzdata==2025.1
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# via pandas

src/svsbench/__init__.py

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