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Merged
eriknw merged 1 commit intopython-graphblas:mainfromeriknw:spec0
Feb 18, 2024
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2 changes: 1 addition & 1 deletion.github/workflows/debug.yml
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Expand Up@@ -15,7 +15,7 @@ jobs:
strategy:
fail-fast: false
matrix:
pyver: [3.9]
pyver: [3.10]
testopts:
- "--blocking"
# - "--non-blocking --record --runslow"
Expand Down
4 changes: 1 addition & 3 deletions.github/workflows/imports.yml
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Expand Up@@ -30,22 +30,20 @@ jobs:
id: pyver
with:
contents: |
3.9
3.10
3.11
3.12
weights: |
1
1
1
1
test_imports:
needs: rngs
runs-on: ${{ needs.rngs.outputs.os }}
# runs-on: ${{ matrix.os }}
# strategy:
# matrix:
# python-version: ["3.9", "3.10", "3.11", "3.12"]
# python-version: ["3.10", "3.11", "3.12"]
# os: ["ubuntu-latest", "macos-latest", "windows-latest"]
steps:
- uses: actions/checkout@v4
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2 changes: 1 addition & 1 deletion.github/workflows/publish_pypi.yml
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Expand Up@@ -20,7 +20,7 @@ jobs:
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.9"
python-version: "3.10"
- name: Install build dependencies
run: |
python -m pip install --upgrade pip
Expand Down
23 changes: 6 additions & 17 deletions.github/workflows/test_and_build.yml
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Expand Up@@ -105,19 +105,17 @@ jobs:
uses: ddradar/choose-random-action@v2.0.2
id: pyver
with:
# We should support major Python versions for at least 36-42 months
# We should support major Python versions for at least 36 months as per SPEC 0
# We may be able to support pypy if anybody asks for it
# 3.9.16 0_73_pypy
contents: |
3.9
3.10
3.11
3.12
weights: |
1
1
1
1
- name: RNG for source of python-suitesparse-graphblas
uses: ddradar/choose-random-action@v2.0.2
id: sourcetype
Expand DownExpand Up@@ -166,20 +164,13 @@ jobs:
#
# First let's randomly get versions of dependencies to install.
# Consider removing old versions when they become problematic or very old (>=2 years).
nxver=$(python -c 'import random ; print(random.choice(["=2.7", "=2.8", "=3.0", "=3.1", "=3.2", ""]))')
sparsever=$(python -c 'import random ; print(random.choice(["=0.13", "=0.14", "=0.15", ""]))')
nxver=$(python -c 'import random ; print(random.choice(["=2.8", "=3.0", "=3.1", "=3.2", ""]))')
sparsever=$(python -c 'import random ; print(random.choice(["=0.14", "=0.15", ""]))')
# Randomly choosing versions of dependencies based on Python version works surprisingly well...
if [[ ${{ startsWith(steps.pyver.outputs.selected, '3.9') }} == true ]]; then
npver=$(python -c 'import random ; print(random.choice(["=1.22", "=1.23", "=1.24", "=1.25", "=1.26", ""]))')
spver=$(python -c 'import random ; print(random.choice(["=1.9", "=1.10", "=1.11", "=1.12", ""]))')
pdver=$(python -c 'import random ; print(random.choice(["=1.2", "=1.3", "=1.4", "=1.5", "=2.0", "=2.1", "=2.2", ""]))')
akver=$(python -c 'import random ; print(random.choice(["=1.9", "=1.10", "=2.0", "=2.1", "=2.2", "=2.3", "=2.4", "=2.5", ""]))')
fmmver=$(python -c 'import random ; print(random.choice(["=1.4", "=1.5", "=1.6", "=1.7", ""]))')
yamlver=$(python -c 'import random ; print(random.choice(["=5.4", "=6.0", ""]))')
elif [[ ${{ startsWith(steps.pyver.outputs.selected, '3.10') }} == true ]]; then
npver=$(python -c 'import random ; print(random.choice(["=1.22", "=1.23", "=1.24", "=1.25", "=1.26", ""]))')
if [[ ${{ startsWith(steps.pyver.outputs.selected, '3.10') }} == true ]]; then
npver=$(python -c 'import random ; print(random.choice(["=1.23", "=1.24", "=1.25", "=1.26", ""]))')
spver=$(python -c 'import random ; print(random.choice(["=1.9", "=1.10", "=1.11", "=1.12", ""]))')
pdver=$(python -c 'import random ; print(random.choice(["=1.3", "=1.4", "=1.5", "=2.0", "=2.1", "=2.2", ""]))')
pdver=$(python -c 'import random ; print(random.choice(["=1.5", "=2.0", "=2.1", "=2.2", ""]))')
akver=$(python -c 'import random ; print(random.choice(["=1.9", "=1.10", "=2.0", "=2.1", "=2.2", "=2.3", "=2.4", "=2.5", ""]))')
fmmver=$(python -c 'import random ; print(random.choice(["=1.4", "=1.5", "=1.6", "=1.7", ""]))')
yamlver=$(python -c 'import random ; print(random.choice(["=5.4", "=6.0", ""]))')
Expand DownExpand Up@@ -237,8 +228,6 @@ jobs:
numbaver=$(python -c 'import random ; print(random.choice(["=0.58", "=0.59", ""]))')
elif [[ ${npver} == "=1.24" || ${{ startsWith(steps.pyver.outputs.selected, '3.11') }} == true ]] ; then
numbaver=$(python -c 'import random ; print(random.choice(["=0.57", "=0.58", "=0.59", ""]))')
elif [[ ${npver} == "=1.21" ]] ; then
numbaver=$(python -c 'import random ; print(random.choice(["=0.55", "=0.56", "=0.57", ""]))')
else
numbaver=$(python -c 'import random ; print(random.choice(["=0.56", "=0.57", "=0.58", "=0.59", ""]))')
fi
Expand Down
2 changes: 1 addition & 1 deletion.pre-commit-config.yaml
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Expand Up@@ -54,7 +54,7 @@ repos:
rev: v3.15.0
hooks:
- id: pyupgrade
args: [--py39-plus]
args: [--py310-plus]
- repo: https://github.com/MarcoGorelli/auto-walrus
rev: v0.2.2
hooks:
Expand Down
5 changes: 2 additions & 3 deletionsdocs/getting_started/faq.rst
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Expand Up@@ -101,11 +101,10 @@ Bugs are not considered deprecations and may be fixed immediately.
What is the version support policy?
+++++++++++++++++++++++++++++++++++

Each major Python version will be supported for at least 36 to 42 months.
Each major Python version will be supported for at least 36.
Major dependencies such as NumPy should be supported for at least 24 months.
This is motivated by these guidelines:
We aim to follow SPEC 0:

- https://numpy.org/neps/nep-0029-deprecation_policy.html
- https://scientific-python.org/specs/spec-0000/

``python-graphblas`` itself follows a "single trunk" versioning strategy.
Expand Down
2 changes: 1 addition & 1 deletiongraphblas/core/formatting.py
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Expand Up@@ -630,7 +630,7 @@ def create_header(type_name, keys, vals, *, lower_border=False, name="", quote=T
name = f'"{name}"'
key_text = []
val_text = []
for key, val in zip(keys, vals):
for key, val in zip(keys, vals, strict=True):
width = max(len(key), len(val)) + 2
key_text.append(key.rjust(width))
val_text.append(val.rjust(width))
Expand Down
7 changes: 4 additions & 3 deletionsgraphblas/core/matrix.py
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Expand Up@@ -360,7 +360,7 @@ def __contains__(self, index):
def __iter__(self):
"""Iterate over (row, col) indices which are present in the matrix."""
rows, columns, _ = self.to_coo(values=False)
return zip(rows.flat, columns.flat)
return zip(rows.flat, columns.flat, strict=True)

def __sizeof__(self):
if backend == "suitesparse":
Expand DownExpand Up@@ -961,7 +961,7 @@ def from_edgelist(
rows = edgelist[:, 0]
cols = edgelist[:, 1]
else:
unzipped = list(zip(*edgelist))
unzipped = list(zip(*edgelist, strict=True))
if len(unzipped) == 2:
rows, cols = unzipped
elif len(unzipped) == 3:
Expand DownExpand Up@@ -1826,10 +1826,11 @@ def to_dicts(self, order="rowwise"):
cols = cols.tolist()
values = values.tolist()
return {
row: dict(zip(cols[start:stop], values[start:stop]))
row: dict(zip(cols[start:stop], values[start:stop], strict=True))
for row, (start, stop) in zip(
compressed_rows.tolist(),
np.lib.stride_tricks.sliding_window_view(indptr, 2).tolist(),
strict=True,
)
}
# Alternative
Expand Down
2 changes: 1 addition & 1 deletiongraphblas/core/ss/matrix.py
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Expand Up@@ -58,7 +58,7 @@ def head(matrix, n=10, dtype=None, *, sort=False):
dtype = matrix.dtype
else:
dtype = lookup_dtype(dtype)
rows, cols, vals = zip(*itertools.islice(matrix.ss.iteritems(), n))
rows, cols, vals = zip(*itertools.islice(matrix.ss.iteritems(), n), strict=True)
return np.array(rows, np.uint64), np.array(cols, np.uint64), np.array(vals, dtype.np_type)


Expand Down
2 changes: 1 addition & 1 deletiongraphblas/core/ss/vector.py
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Expand Up@@ -43,7 +43,7 @@ def head(vector, n=10, dtype=None, *, sort=False):
dtype = vector.dtype
else:
dtype = lookup_dtype(dtype)
indices, vals = zip(*itertools.islice(vector.ss.iteritems(), n))
indices, vals = zip(*itertools.islice(vector.ss.iteritems(), n), strict=True)
return np.array(indices, np.uint64), np.array(vals, dtype.np_type)


Expand Down
2 changes: 1 addition & 1 deletiongraphblas/core/utils.py
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Expand Up@@ -202,7 +202,7 @@ def normalize_chunks(chunks, shape):
f"chunks argument must be of length {len(shape)} (one for each dimension of a {typ})"
)
chunksizes = []
for size, chunk in zip(shape, chunks):
for size, chunk in zip(shape, chunks, strict=True):
if chunk is None:
cur_chunks = [size]
elif (c := maybe_integral(chunk)) is not None:
Expand Down
4 changes: 2 additions & 2 deletionsgraphblas/core/vector.py
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Expand Up@@ -772,7 +772,7 @@ def from_pairs(cls, pairs, dtype=None, *, size=None, dup_op=None, name=None):
"""
if isinstance(pairs, np.ndarray):
raise TypeError("pairs as NumPy array is not supported; use `Vector.from_coo` instead")
unzipped = list(zip(*pairs))
unzipped = list(zip(*pairs, strict=True))
if len(unzipped) == 2:
indices, values = unzipped
elif not unzipped:
Expand DownExpand Up@@ -2105,7 +2105,7 @@ def to_dict(self):

"""
indices, values = self.to_coo(sort=False)
return dict(zip(indices.tolist(), values.tolist()))
return dict(zip(indices.tolist(), values.tolist(), strict=True))


if backend == "suitesparse":
Expand Down
6 changes: 4 additions & 2 deletionsgraphblas/io/_networkx.py
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Expand Up@@ -55,7 +55,9 @@ def to_networkx(m, edge_attribute="weight"):
cols = cols.tolist()
G = nx.DiGraph()
if edge_attribute is None:
G.add_edges_from(zip(rows, cols))
G.add_edges_from(zip(rows, cols, strict=True))
else:
G.add_weighted_edges_from(zip(rows, cols, vals.tolist()), weight=edge_attribute)
G.add_weighted_edges_from(
zip(rows, cols, vals.tolist(), strict=True), weight=edge_attribute
)
return G
2 changes: 1 addition & 1 deletiongraphblas/tests/test_io.py
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Expand Up@@ -146,7 +146,7 @@ def test_matrix_to_from_networkx():
M = gb.io.from_networkx(G, nodelist=range(7))
if suitesparse:
assert M.ss.is_iso
rows, cols = zip(*edges)
rows, cols = zip(*edges, strict=True)
expected = gb.Matrix.from_coo(rows, cols, 1)
assert expected.isequal(M)
# Test empty
Expand Down
14 changes: 8 additions & 6 deletionsgraphblas/tests/test_matrix.py
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Expand Up@@ -2603,12 +2603,14 @@ def test_iter(A):
zip(
[3, 0, 3, 5, 6, 0, 6, 1, 6, 2, 4, 1],
[0, 1, 2, 2, 2, 3, 3, 4, 4, 5, 5, 6],
strict=True,
)
)
assert set(A.T) == set(
zip(
[0, 1, 2, 2, 2, 3, 3, 4, 4, 5, 5, 6],
[3, 0, 3, 5, 6, 0, 6, 1, 6, 2, 4, 1],
strict=True,
)
)

Expand DownExpand Up@@ -2731,8 +2733,8 @@ def test_ss_split(A):
for results in [A.ss.split([4, 3]), A.ss.split([[4, None], 3], name="split")]:
row_boundaries = [0, 4, 7]
col_boundaries = [0, 3, 6, 7]
for i, (i1, i2) in enumerate(zip(row_boundaries[:-1], row_boundaries[1:])):
for j, (j1, j2) in enumerate(zip(col_boundaries[:-1], col_boundaries[1:])):
for i, (i1, i2) in enumerate(itertools.pairwise(row_boundaries)):
for j, (j1, j2) in enumerate(itertools.pairwise(col_boundaries)):
expected = A[i1:i2, j1:j2].new()
assert expected.isequal(results[i][j])
with pytest.raises(DimensionMismatch):
Expand DownExpand Up@@ -3068,7 +3070,7 @@ def test_ss_flatten(A):
[3, 2, 3, 1, 5, 3, 7, 8, 3, 1, 7, 4],
]
# row-wise
indices = [row * A.ncols + col for row, col in zip(data[0], data[1])]
indices = [row * A.ncols + col for row, col in zip(data[0], data[1], strict=True)]
expected = Vector.from_coo(indices, data[2], size=A.nrows * A.ncols)
for fmt in ["csr", "hypercsr", "bitmapr"]:
B = Matrix.ss.import_any(**A.ss.export(format=fmt))
Expand All@@ -3087,7 +3089,7 @@ def test_ss_flatten(A):
assert C.isequal(B)

# column-wise
indices = [col * A.nrows + row for row, col in zip(data[0], data[1])]
indices = [col * A.nrows + row for row, col in zip(data[0], data[1], strict=True)]
expected = Vector.from_coo(indices, data[2], size=A.nrows * A.ncols)
for fmt in ["csc", "hypercsc", "bitmapc"]:
B = Matrix.ss.import_any(**A.ss.export(format=fmt))
Expand DownExpand Up@@ -3626,9 +3628,9 @@ def test_ss_iteration(A):
assert not list(B.ss.itervalues())
assert not list(B.ss.iteritems())
rows, columns, values = A.to_coo()
assert sorted(zip(rows, columns)) == sorted(A.ss.iterkeys())
assert sorted(zip(rows, columns, strict=True)) == sorted(A.ss.iterkeys())
assert sorted(values) == sorted(A.ss.itervalues())
assert sorted(zip(rows, columns, values)) == sorted(A.ss.iteritems())
assert sorted(zip(rows, columns, values, strict=True)) == sorted(A.ss.iteritems())
N = rows.size

A = Matrix.ss.import_bitmapr(**A.ss.export("bitmapr"))
Expand Down
2 changes: 1 addition & 1 deletiongraphblas/tests/test_vector.py
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Expand Up@@ -2270,7 +2270,7 @@ def test_ss_iteration(v):
# This is what I would expect
assert sorted(indices) == sorted(v.ss.iterkeys())
assert sorted(values) == sorted(v.ss.itervalues())
assert sorted(zip(indices, values)) == sorted(v.ss.iteritems())
assert sorted(zip(indices, values, strict=True)) == sorted(v.ss.iteritems())

N = indices.size
v = Vector.ss.import_bitmap(**v.ss.export("bitmap"))
Expand Down
25 changes: 13 additions & 12 deletionspyproject.toml
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Expand Up@@ -10,7 +10,7 @@ name = "python-graphblas"
dynamic = ["version"]
description = "Python library for GraphBLAS: high-performance sparse linear algebra for scalable graph analytics"
readme = "README.md"
requires-python = ">=3.9"
requires-python = ">=3.10"
license = {file = "LICENSE"}
authors = [
{name = "Erik Welch", email = "erik.n.welch@gmail.com"},
Expand DownExpand Up@@ -44,7 +44,6 @@ classifiers = [
"Operating System :: Microsoft :: Windows",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
Expand All@@ -58,7 +57,7 @@ classifiers = [
"Topic :: Software Development :: Libraries :: Python Modules",
]
dependencies = [
"numpy >=1.22",
"numpy >=1.23",
"donfig >=0.6",
"pyyaml >=5.4",
# These won't be installed by default after 2024.3.0
Expand All@@ -84,7 +83,7 @@ numba = [
"numba >=0.55",
]
pandas = [
"pandas >=1.2",
"pandas >=1.5",
]
scipy = [
"scipy >=1.9",
Expand All@@ -99,17 +98,17 @@ io = [
"python-graphblas[networkx,scipy]",
"python-graphblas[numba]; python_version<'3.13'",
"awkward >=1.9",
"sparse >=0.13; python_version<'3.13'", # make optional, b/c sparse needs numba
"sparse >=0.14; python_version<'3.13'", # make optional, b/c sparse needs numba
"fast-matrix-market >=1.4.5",
]
viz = [
"python-graphblas[networkx,scipy]",
"matplotlib >=3.5",
"matplotlib >=3.6",
]
datashade = [ # datashade requires numba
"python-graphblas[numba,pandas,scipy]",
"datashader >=0.12",
"hvplot >=0.7",
"datashader >=0.14",
"hvplot >=0.8",
]
test = [
"python-graphblas[suitesparse,pandas,scipy]",
Expand DownExpand Up@@ -157,7 +156,7 @@ dirty_template = "{tag}+{ccount}.g{sha}.dirty"

[tool.black]
line-length = 100
target-version = ["py39", "py310", "py311", "py312"]
target-version = ["py310", "py311", "py312"]

[tool.isort]
sections = ["FUTURE", "STDLIB", "THIRDPARTY", "FIRSTPARTY", "LOCALFOLDER"]
Expand DownExpand Up@@ -241,10 +240,11 @@ ignore-words-list = "coo,ba"
[tool.ruff]
# https://github.com/charliermarsh/ruff/
line-length = 100
target-version = "py39"
target-version = "py310"
[tool.ruff.lint]
unfixable = [
"F841" # unused-variable (Note: can leave useless expression)
"F841", # unused-variable (Note: can leave useless expression)
"B905", # zip-without-explicit-strict (Note: prefer `zip(x, y, strict=True)`)
]
select = [
# Have we enabled too many checks that they'll become a nuisance? We'll see...
Expand DownExpand Up@@ -360,6 +360,7 @@ ignore = [
"SIM105", # Use contextlib.suppress(...) instead of try-except-pass (Note: try-except-pass is much faster)
"SIM108", # Use ternary operator ... instead of if-else-block (Note: if-else better for coverage and sometimes clearer)
"TRY003", # Avoid specifying long messages outside the exception class (Note: why?)
"UP038", # Use `X | Y` in `isinstance` call instead of `(X, Y)` (Note: using `|` is slower atm)

# Ignored categories
"C90", # mccabe (Too strict, but maybe we should make things less complex)
Expand DownExpand Up@@ -409,7 +410,7 @@ convention = "numpy"
[tool.pylint.messages_control]
# To run a single check, do: pylint graphblas --disable E,W,R,C,I --enable assignment-from-no-return
max-line-length = 100
py-version = "3.9"
py-version = "3.10"
enable = ["I"]
disable = [
# Error
Expand Down
2 changes: 1 addition & 1 deletionscripts/check_versions.sh
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Expand Up@@ -14,4 +14,4 @@ conda search 'sparse[channel=conda-forge]>=0.15.1'
conda search 'fast_matrix_market[channel=conda-forge]>=1.7.6'
conda search 'numba[channel=conda-forge]>=0.59.0'
conda search 'pyyaml[channel=conda-forge]>=6.0.1'
# conda search 'python[channel=conda-forge]>=3.9 *pypy*'
# conda search 'python[channel=conda-forge]>=3.10 *pypy*'
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