Move packaging metadata to pyproject

.flake8

@@ -0,0 +1,10 @@
+[flake8]
+max-line-length = 120
+exclude = docs/src, build, dist
+ignore = F811,E121,E123,E126,E226,E24,E704,W503,W504,E203
+per-file-ignores =
+    test/examples/test_sensor_fusion.py:E128
+    funsor/ops/__init__.py:F401,F403
+    funsor/jax/distributions.py:F821
+    funsor/torch/distributions.py:F821
+    test/conftest.py:E402

funsor/__init__.py

@@ -53,7 +53,7 @@
     testing,
 )
 
-__version__ = "0.4.7"  # mirrored in setup.py
+__version__ = "0.4.7"  # used by pyproject.toml
 
 __all__ = [
     "__version__",

funsor/adjoint.py

@@ -224,7 +224,7 @@ def adjoint_contract_generic(
         sum_op,
         prod_op,
         reduced_vars,
-        *terms
+        *terms,
     )
 
 

funsor/cnf.py

@@ -184,7 +184,7 @@ def _sample(self, sampled_vars, sample_inputs, rng_key):
                         self.red_op,
                         self.bin_op,
                         self.reduced_vars,
-                        *(terms + sampled_terms)
+                        *(terms + sampled_terms),
                     )
                 else:
                     raise NotImplementedError(
@@ -431,7 +431,7 @@ def normalize_contraction_commute_joint(red_op, bin_op, reduced_vars, mixture, o
         mixture.red_op if red_op is ops.null else red_op,
         bin_op,
         reduced_vars | mixture.reduced_vars,
-        *(mixture.terms + (other,))
+        *(mixture.terms + (other,)),
     )
 
 
@@ -443,7 +443,7 @@ def normalize_contraction_commute_joint(red_op, bin_op, reduced_vars, other, mix
         mixture.red_op if red_op is ops.null else red_op,
         bin_op,
         reduced_vars | mixture.reduced_vars,
-        *(mixture.terms + (other,))
+        *(mixture.terms + (other,)),
     )
 
 

funsor/optimizer.py

@@ -38,7 +38,7 @@ def unfold_contraction_generic_tuple(red_op, bin_op, reduced_vars, terms):
                     v.red_op,
                     bin_op,
                     v.reduced_vars,
-                    *(terms[:i] + (vt,) + terms[i + 1 :])
+                    *(terms[:i] + (vt,) + terms[i + 1 :]),
                 )
                 for vt in v.terms
             )

pyproject.toml

@@ -0,0 +1,107 @@
+[build-system]
+requires = ["setuptools>=77"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "funsor"
+description = "A tensor-like library for functions and distributions"
+readme = { file = "README.md", content-type = "text/markdown" }
+requires-python = ">=3.10"
+license = "Apache-2.0"
+license-files = ["LICENSE.md"]
+dynamic = ["version"]
+authors = [
+    { name = "Uber AI Labs" },
+]
+keywords = ["probabilistic", "machine learning", "bayesian statistics", "pytorch", "jax"]
+classifiers = [
+    "Intended Audience :: Developers",
+    "Intended Audience :: Education",
+    "Intended Audience :: Science/Research",
+    "Operating System :: POSIX :: Linux",
+    "Operating System :: MacOS :: MacOS X",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
+    "Programming Language :: Python :: 3.14",
+]
+dependencies = [
+    "makefun",
+    "multipledispatch",
+    "numpy>=1.7",
+    "opt_einsum>=2.3.2",
+    "typing_extensions",
+]
+
+[project.optional-dependencies]
+torch = [
+    "pyro-ppl>=1.8.0",
+    "torch>=1.11.0",
+    "torchvision>=0.12.0",
+]
+jax = [
+    "numpyro>=0.7.0",
+    "jax>=0.2.21",
+    "jaxlib>=0.1.71",
+]
+test = [
+    "black",
+    "flake8",
+    "isort>=5.0",
+    "pandas",
+    "pyro-api>=0.1.2",
+    "pytest>=7",
+    "pytest-xdist>=3",
+    "requests",
+    "scipy",
+]
+dev = [
+    "black",
+    "flake8",
+    "isort>=5.0",
+    "nbsphinx",
+    "pandas",
+    "pytest>=7",
+    "pytest-xdist>=3",
+    "scipy",
+    "sphinx>=2.0",
+    "sphinx-gallery",
+    "sphinx_rtd_theme",
+    "torchvision>=0.12.0",
+]
+
+[project.urls]
+Homepage = "https://github.com/pyro-ppl/funsor"
+Documentation = "https://funsor.pyro.ai"
+Repository = "https://github.com/pyro-ppl/funsor"
+Issues = "https://github.com/pyro-ppl/funsor/issues"
+
+[tool.setuptools.dynamic]
+version = { attr = "funsor.__version__" }
+
+[tool.setuptools.packages.find]
+include = ["funsor", "funsor.*"]
+
+[tool.isort]
+profile = "black"
+known_first_party = ["funsor", "test"]
+known_third_party = ["opt_einsum", "pyro", "pyroapi", "torch", "torchvision"]
+
+[tool.pytest.ini_options]
+filterwarnings = [
+    "error",
+    "ignore:numpy.ufunc size changed:RuntimeWarning",
+    "ignore:numpy.dtype size changed:RuntimeWarning",
+    "ignore:Mixed memory format:UserWarning",
+    "ignore:Cannot memoize Op:UserWarning",
+    "ignore::DeprecationWarning",
+    "ignore:CUDA initialization:UserWarning",
+    "ignore:floor_divide is deprecated:UserWarning",
+    "ignore:__floordiv__ is deprecated:UserWarning",
+    "ignore:__rfloordiv__ is deprecated:UserWarning",
+    "ignore:torch.cholesky is deprecated:UserWarning",
+    "ignore:torch.symeig is deprecated:UserWarning",
+    "once::DeprecationWarning",
+]
+doctest_optionflags = "ELLIPSIS NORMALIZE_WHITESPACE IGNORE_EXCEPTION_DETAIL"

test/test_distribution_generic.py

@@ -778,9 +778,10 @@ def test_generic_stats(case, statistic):
                 raw_dist, output=funsor.Real, dim_to_name=dim_to_name
             )
 
-    with xfail_if_not_implemented(
-        msg="entropy not implemented for some distributions"
-    ), xfail_if_not_found(msg="stats not implemented yet for TransformedDist"):
+    with (
+        xfail_if_not_implemented(msg="entropy not implemented for some distributions"),
+        xfail_if_not_found(msg="stats not implemented yet for TransformedDist"),
+    ):
         actual_stat = getattr(funsor_dist, statistic)()
 
     with xfail_if_not_implemented():

test/test_memoize.py

@@ -178,14 +178,14 @@ def test_nested_einsum_complete_sharing(
         output2_1 = einsum_impl2(
             outputs1[0] + "," + eqn2,
             *([output1_1] + funsor_operands2),
-            backend=backend2
+            backend=backend2,
         )
 
         output1_2 = einsum_impl1(eqn1, *funsor_operands1, backend=backend1)
         output2_2 = einsum_impl2(
             outputs1[0] + "," + eqn2,
             *([output1_2] + funsor_operands2),
-            backend=backend2
+            backend=backend2,
         )
 
     assert output1_1 is output1_2

test/test_optimizer.py

@@ -98,7 +98,7 @@ def test_nested_einsum(
         outputs1[0] + "," + eqn2,
         *([expected1] + operands2),
         backend=backend2,
-        modulo_total=True
+        modulo_total=True,
     )[0]
 
     with normalize: