pyproject.toml

[build-system]
# setup.py imports only setuptools, so the build needs no JPype. A build-time jpype1 was compiled from
# source on a Python without a JPype wheel (3.15, until JPype > 1.7.1) and failed there. `build` is a
# frontend, not a backend requirement.
# setuptools 70.1 is the first release with its own bdist_wheel command, which setup.py subclasses to
# tag the wheel py3-none-<platform>.
requires = ["setuptools>=70.1", "wheel"]
build-backend = "setuptools.build_meta"

# This file defines the package metadata for arcadedb.
# During build, the version is overwritten from the bundled ArcadeDB engine jar via
# scripts/extract_version.py

[project]
name = "arcadedb-jvm"
version = "0.0.0"
description = "ArcadeDB embedded multi-model database, JVM build with a bundled JRE (no Java installation needed). The native build is the package arcadedb; both import as arcadedb"
readme = "README.md"
# The upper bound is JPype: jpype1 1.7.1 has wheels for CPython 3.11 to 3.14 and none for 3.15 (JPype
# merged 3.15 support in jpype-project/jpype#1501, not released yet). The wheels of this package are
# py3-none-<platform>, so the wheel tag no longer keeps an installer off an interpreter: without this cap an installer
# would put the wheel on 3.15 and then try to build JPype from source.
# REMOVE THE CAP when jpype1 ships cp315 wheels: then add the 3.15 classifier below, 3.15 to PYTHONS in
# scripts/select_matrix.py and the cap in tests/test_select_matrix.py.
requires-python = ">=3.11,<3.15"
license = { text = "Apache-2.0" }
authors = [
    { name = "Taewoon Kim", email = "taewoon@humem.ai" }
]
keywords = ["database", "graph", "document", "multi-model", "nosql", "arcadedb", "embedded", "jre", "java", "jvm"]
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Developers",
    "License :: OSI Approved :: Apache Software License",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Programming Language :: Python :: 3.13",
    "Programming Language :: Python :: 3.14",
    "Topic :: Database",
    "Topic :: Software Development :: Libraries :: Python Modules",
]

dependencies = [
    "jpype1>=1.5.0",
]

[tool.uv]
# This pyproject is the *package definition* consumed by the wheel build
# (scripts/build.sh). It is not a uv project: tests run against the built wheel,
# with its `test` extra, in a throwaway `uv run --no-project --with` environment
# (see README, Testing). `managed = false` makes uv skip it during project
# discovery, so `uv run` never tries to sync this package.
managed = false

[project.optional-dependencies]
test = [
    "pytest>=9.0.3",
    "pytest-cov",
    "numpy>=1.26.4",
    "requests>=2.33.0",  # HTTP API / docs-example tests
    # Real clients for the bundled wire protocols. Test-only: none of these
    # reaches an end user's install, and without them three shipped protocols
    # are covered by nothing but the jars being present in the archive.
    "psycopg[binary]>=3.1",  # Postgres wire
    "adbc-driver-postgresql>=1.12",  # Postgres wire, Arrow ADBC (26.10.1+)
    "redis>=5.0",            # Redis wire
    "neo4j>=5.0",            # Bolt
    "pyarrow>=23.0.1",       # ResultSet.to_arrow(); <23.0.1 has PYSEC-2026-113
    "polars>=1.0",           # ResultSet.to_polars(), insert_dataframe() with a Polars frame
    # ResultSet.to_dataframe(). Absent until 2026-08-04, which meant its two
    # tests called importorskip("pandas") and skipped in every CI run this
    # package has ever had: a public, documented method with no executed
    # coverage. Same shape as the arrow gap, but in the extras DEFINITION
    # rather than an install command, so no amount of care at install time
    # would have caught it.
    "pandas>=2.2.0",
    # Reference engines for tests/test_equivalence.py (humemai/arcadedb-embedded-python#347): the same question asked
    # of a second engine over the same data. All three have wheels for every CI platform, so the file never skips.
    "duckdb>=1.4.2",
    "ladybug>=0.21.2",
    "networkx>=3.4",
    # tests/test_wheel_packages.py runs `setup.py build_py` on a copy of the sources to prove the JVM wheel ships every
    # subpackage; Python 3.12+ venvs have no setuptools, so without it here the test fails on those legs instead of running.
    # Floor 84.1.0: the dependency-floor audit resolves the lowest version; pip-audit (2026-10-24) finds no known
    # vulnerability in 84.1.0, while 78.1.1 still has PYSEC-2026-3447 and GHSA-xmj3-9gf7-h52w.
    "setuptools>=84.1.0",
]
dev = [
    "black",
    "isort",
    "mypy",
    "pytest>=9.0.3",
    "pytest-cov",
    "numpy>=1.26.4",
    "requests>=2.33.0",  # HTTP API / docs-example tests
    "bandit>=1.9.1",
]
vector = [
    "numpy>=1.26.4",
]
# Optional: ResultSet.to_arrow(). The columnar bridge already emits packed
# columns with a null bitmap, so this adds no Java and no jars to the wheel;
# pyarrow is only needed to wrap those buffers. Without it to_arrow() returns
# None and callers fall back to to_columns().
arrow = [
    "pyarrow>=23.0.1",
    "numpy>=1.26.4",
]
# Optional: ResultSet.to_dataframe(). Shipped and documented long before this
# extra existed, so the only way to discover the dependency was to call the
# method and read the ImportError. `arrow` had an extra and `pandas` did not,
# for two methods on the same class doing the same kind of thing.
#
# Note the two differ in how they FAIL, and that is deliberate on to_arrow's
# side rather than an oversight here: to_arrow() returns None so callers can
# fall back to to_columns(), while to_dataframe() raises ImportError. Changing
# to_dataframe to match would break callers relying on the exception, so it
# stays as it is and is documented rather than quietly aligned.
pandas = [
    "pandas>=2.2.0",
    "numpy>=1.26.4",
]
# Optional: ResultSet.to_polars() and insert_dataframe() with a Polars frame. Both go
# through Arrow, so pyarrow comes with it. insert_dataframe() with a pandas frame needs
# `uv add 'arcadedb-jvm[arrow,pandas]'` (the pandas extra alone has no pyarrow,
# because to_dataframe() does not need it).
polars = [
    "polars>=1.0",
    "pyarrow>=23.0.1",
    "numpy>=1.26.4",
]
examples = [
    "py7zr>=1.1.3",  # Required for Stack Exchange data downloads
]

[project.urls]
Homepage = "https://github.com/ArcadeData/arcadedb-python"
Documentation = "https://docs.arcadedb.com/arcadedb-python/"
Repository = "https://github.com/ArcadeData/arcadedb-python"
"Bug Tracker" = "https://github.com/ArcadeData/arcadedb-python/issues"
"ArcadeDB Upstream" = "https://github.com/ArcadeData/arcadedb"

[tool.setuptools]
packages = ["arcadedb", "arcadedb._native"]
package-dir = { "" = "src" }
include-package-data = true

[tool.setuptools.package-data]
arcadedb = [
    "jars/*.jar",
    "jre/**/*",
]

[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = ["test_*.py"]
python_classes = ["Test*"]
python_functions = ["test_*"]
addopts = "-v --tb=short"
# A test still running after 10 minutes dumps every thread's stack, so a hang
# explains itself instead of ending as a silent CI step timeout (one Windows
# job sat 25 minutes in test_per_index_cache_params on 2026-09-27; its rerun
# passed). The whole suite takes about four minutes.
faulthandler_timeout = 600
markers = [
    "server: tests that require server/studio support",
    "server_wire: speaks a bundled wire protocol with its real client",
    "integration: tests that require external components",
]

[tool.bandit]
# Skip recursion into test data and build artifacts.
# Patterns are matched as substrings, so anchor with leading "/" to avoid
# accidentally excluding files like examples/11_vector_index_build.py.
exclude_dirs = ["/tests/.cache/", "/build/", "/dist/"]
# B101 (assert_used) is the standard pytest idiom and the production source
# (src/) intentionally contains no assert statements - so we skip it globally
# rather than maintaining a per-file glob list.
skips = ["B101"]