Fix editable install failure: migrate packaging metadata to PEP 621 (pyproject.toml)

pyproject.toml

@@ -1,6 +1,168 @@
 [build-system]
 requires = ["setuptools>=64", "wheel"]
-build-backend = "setuptools.build_meta:__legacy__"
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "FLAML"
+dynamic = ["version"]
+description = "A fast library for automated machine learning and tuning"
+readme = "README.md"
+requires-python = ">=3.10"
+license = {text = "MIT"}
+authors = [
+    {name = "Microsoft Corporation", email = "hpo@microsoft.com"},
+]
+classifiers = [
+    "License :: OSI Approved :: MIT License",
+    "Operating System :: OS Independent",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
+]
+dependencies = [
+    "NumPy>=1.17",
+]
+
+[project.urls]
+Homepage = "https://github.com/microsoft/FLAML"
+
+[project.optional-dependencies]
+automl = [
+    "lightgbm>=2.3.1",
+    "xgboost>=0.90,<3.0.0",
+    "scipy>=1.4.1",
+    "pandas>=1.1.4",
+    "scikit-learn>=1.0.0",
+]
+notebook = [
+    "jupyter",
+]
+spark = [
+    "pyspark>=3.2.0",
+    "pandas<3",
+    "joblibspark>=0.5.0",
+    "joblib<=1.3.2",
+]
+test = [
+    "numpy>=1.17,<2.0.0; python_version<'3.13'",
+    "numpy>=1.17; python_version>='3.13'",
+    "jupyter",
+    "lightgbm>=2.3.1",
+    "xgboost>=0.90,<2.0.0; python_version<'3.11'",
+    "xgboost>=2.0.0; python_version>='3.11'",
+    "scipy>=1.4.1",
+    "pandas>=1.1.4",
+    "scikit-learn>=1.2.0",
+    "thop",
+    "pytest>=6.1.1",
+    "pytest-rerunfailures>=13.0",
+    "coverage>=5.3",
+    "pre-commit",
+    "torch",
+    "torchvision",
+    "catboost>=0.26",
+    "rgf-python",
+    "optuna>=2.8.0,<=3.6.1",
+    "openml",
+    "statsmodels>=0.12.2",
+    "psutil",
+    "transformers[torch]",
+    "datasets",
+    "evaluate",
+    "nltk!=3.8.2",
+    "rouge_score",
+    "hcrystalball",
+    "seqeval",
+    "pytorch-forecasting",
+    "mlflow-skinny<=2.22.1",
+    "joblibspark>=0.5.0",
+    "joblib<=1.3.2",
+    "nbconvert",
+    "nbformat",
+    "ipykernel",
+    "pytorch-lightning",
+    "tensorboardX",
+    "requests",
+    "packaging",
+    "dill",
+]
+catboost = [
+    "catboost>=0.26",
+]
+blendsearch = [
+    "optuna>=2.8.0,<=3.6.1",
+    "packaging",
+]
+ray = [
+    "ray[tune]>=1.13,<2.5.0",
+]
+azureml = [
+    "azureml-mlflow",
+]
+nni = [
+    "nni",
+]
+vw = [
+    "vowpalwabbit>=8.10.0, <9.0.0",
+    "scikit-learn",
+]
+hf = [
+    "transformers[torch]>=4.26",
+    "datasets",
+    "nltk<=3.8.1",
+    "rouge_score",
+    "seqeval",
+]
+nlp = [
+    "transformers[torch]>=4.26",
+    "datasets",
+    "nltk<=3.8.1",
+    "rouge_score",
+    "seqeval",
+]
+ts_forecast = [
+    "holidays",
+    "prophet>=1.1.5",
+    "statsmodels>=0.12.2",
+    "hcrystalball>=0.1.10",
+]
+forecast = [
+    "holidays",
+    "prophet>=1.1.5",
+    "statsmodels>=0.12.2",
+    "hcrystalball>=0.1.10",
+    "pytorch-forecasting>=0.10.4",
+    "pytorch-lightning>=1.9.0",
+    "tensorboardX>=2.6",
+]
+benchmark = [
+    "catboost>=0.26",
+    "psutil==5.8.0",
+    "xgboost==1.3.3",
+    "pandas==1.1.4",
+]
+synapse = [
+    "joblibspark>=0.5.0",
+    "optuna>=2.8.0,<=3.6.1",
+    "pyspark>=3.2.0",
+]
+autozero = [
+    "scikit-learn",
+    "pandas",
+    "packaging",
+]
+
+[tool.setuptools.dynamic]
+version = {attr = "flaml.version.__version__"}
+
+[tool.setuptools.packages.find]
+include = ["flaml*"]
+
+[tool.setuptools.package-data]
+"flaml.default" = ["*/*.json"]
+flaml = ["py.typed"]
 
 [tool.pytest.ini_options]
 addopts = '-m "not conda"'

setup.py

@@ -1,166 +1,3 @@
-import os
-
 import setuptools
 
-here = os.path.abspath(os.path.dirname(__file__))
-
-with open("README.md", encoding="UTF-8") as fh:
-    long_description = fh.read()
-
-
-# Get the code version
-version = {}
-with open(os.path.join(here, "flaml/version.py")) as fp:
-    exec(fp.read(), version)
-__version__ = version["__version__"]
-
-install_requires = [
-    "NumPy>=1.17",
-]
-
-
-setuptools.setup(
-    name="FLAML",
-    version=__version__,
-    author="Microsoft Corporation",
-    author_email="hpo@microsoft.com",
-    description="A fast library for automated machine learning and tuning",
-    long_description=long_description,
-    long_description_content_type="text/markdown",
-    url="https://github.com/microsoft/FLAML",
-    packages=setuptools.find_packages(include=["flaml*"]),
-    package_data={
-        "flaml.default": ["*/*.json"],
-    },
-    include_package_data=True,
-    install_requires=install_requires,
-    extras_require={
-        "automl": [
-            "lightgbm>=2.3.1",
-            "xgboost>=0.90,<3.0.0",
-            "scipy>=1.4.1",
-            "pandas>=1.1.4",
-            "scikit-learn>=1.0.0",
-        ],
-        "notebook": [
-            "jupyter",
-        ],
-        "spark": [
-            "pyspark>=3.2.0",
-            "pandas<3",
-            "joblibspark>=0.5.0",
-            "joblib<=1.3.2",
-        ],
-        "test": [
-            "numpy>=1.17,<2.0.0; python_version<'3.13'",
-            "numpy>=1.17; python_version>='3.13'",
-            "jupyter",
-            "lightgbm>=2.3.1",
-            "xgboost>=0.90,<2.0.0; python_version<'3.11'",
-            "xgboost>=2.0.0; python_version>='3.11'",
-            "scipy>=1.4.1",
-            "pandas>=1.1.4,<2.0.0; python_version<'3.10'",
-            "pandas>=1.1.4; python_version>='3.10'",
-            "scikit-learn>=1.2.0",
-            "thop",
-            "pytest>=6.1.1",
-            "pytest-rerunfailures>=13.0",
-            "coverage>=5.3",
-            "pre-commit",
-            "torch",
-            "torchvision",
-            "catboost>=0.26",
-            "rgf-python",
-            "optuna>=2.8.0,<=3.6.1",
-            "openml",
-            "statsmodels>=0.12.2",
-            "psutil",
-            "dataclasses",
-            "transformers[torch]",
-            "datasets",
-            "evaluate",
-            "nltk!=3.8.2",  # 3.8.2 doesn't work with mlflow
-            "rouge_score",
-            "hcrystalball",
-            "seqeval",
-            "pytorch-forecasting",
-            "mlflow-skinny<=2.22.1",  # Refer to https://mvnrepository.com/artifact/org.mlflow/mlflow-spark
-            "joblibspark>=0.5.0",
-            "joblib<=1.3.2",
-            "nbconvert",
-            "nbformat",
-            "ipykernel",
-            "pytorch-lightning",  # test_forecast_panel
-            "tensorboardX",  # test_forecast_panel
-            "requests",  # https://github.com/docker/docker-py/issues/3113
-            "packaging",
-            "dill",  # a drop in replacement of pickle
-        ],
-        "catboost": [
-            "catboost>=0.26",
-        ],
-        "blendsearch": [
-            "optuna>=2.8.0,<=3.6.1",
-            "packaging",
-        ],
-        "ray": [
-            "ray[tune]>=1.13,<2.5.0",
-        ],
-        "azureml": [
-            "azureml-mlflow",
-        ],
-        "nni": [
-            "nni",
-        ],
-        "vw": [
-            "vowpalwabbit>=8.10.0, <9.0.0",
-            "scikit-learn",
-        ],
-        "hf": [
-            "transformers[torch]>=4.26",
-            "datasets",
-            "nltk<=3.8.1",
-            "rouge_score",
-            "seqeval",
-        ],
-        "nlp": [  # for backward compatibility; hf is the new option name
-            "transformers[torch]>=4.26",
-            "datasets",
-            "nltk<=3.8.1",
-            "rouge_score",
-            "seqeval",
-        ],
-        "ts_forecast": [
-            "holidays",
-            "prophet>=1.1.5",
-            "statsmodels>=0.12.2",
-            "hcrystalball>=0.1.10",
-        ],
-        "forecast": [
-            "holidays",
-            "prophet>=1.1.5",
-            "statsmodels>=0.12.2",
-            "hcrystalball>=0.1.10",
-            "pytorch-forecasting>=0.10.4",
-            "pytorch-lightning>=1.9.0",
-            "tensorboardX>=2.6",
-        ],
-        "benchmark": ["catboost>=0.26", "psutil==5.8.0", "xgboost==1.3.3", "pandas==1.1.4"],
-        "synapse": [
-            "joblibspark>=0.5.0",
-            "optuna>=2.8.0,<=3.6.1",
-            "pyspark>=3.2.0",
-        ],
-        "autozero": ["scikit-learn", "pandas", "packaging"],
-    },
-    classifiers=[
-        "License :: OSI Approved :: MIT License",
-        "Operating System :: OS Independent",
-        # Specify the Python versions you support here.
-        "Programming Language :: Python :: 3",
-        "Programming Language :: Python :: 3.10",
-        "Programming Language :: Python :: 3.11",
-        "Programming Language :: Python :: 3.12",
-    ],
-    python_requires=">=3.10",
-)
+setuptools.setup()