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Add more lints to Ruff for better code quality. #621

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merged 6 commits into from
Jan 8, 2024
Merged

Add more lints to Ruff for better code quality. #621

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ea54dd5
Add more lints to Ruff for better code quality.
hameerabbasi Jan 5, 2024
ce82530
Add more lints.
hameerabbasi Jan 8, 2024
a407d2e
Merge branch 'master' into moar-lints
hameerabbasi Jan 8, 2024
f2f4a4d
Avoid generator instantiation.
hameerabbasi Jan 8, 2024
92da4eb
Replace all instances of `np.int_` with `np.int64`.
hameerabbasi Jan 8, 2024
f403a0f
Merge remote-tracking branch 'origin/master' into moar-lints
hameerabbasi Jan 8, 2024
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2 changes: 1 addition & 1 deletion .pre-commit-config.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@ repos:
args: ["--autofix", "--no-ensure-ascii"]

- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.1.9
rev: v0.1.11
hooks:
- id: ruff
args: ["--fix"]
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24 changes: 12 additions & 12 deletions benchmarks/benchmark_coo.py
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Expand Up @@ -5,9 +5,9 @@

class MatrixMultiplySuite:
def setup(self):
np.random.seed(0)
self.x = sparse.random((100, 100), density=0.01)
self.y = sparse.random((100, 100), density=0.01)
rng = np.random.default_rng(0)
self.x = sparse.random((100, 100), density=0.01, random_state=rng)
self.y = sparse.random((100, 100), density=0.01, random_state=rng)

self.x @ self.y # Numba compilation

Expand All @@ -17,9 +17,9 @@ def time_matmul(self):

class ElemwiseSuite:
def setup(self):
np.random.seed(0)
self.x = sparse.random((100, 100, 100), density=0.01)
self.y = sparse.random((100, 100, 100), density=0.01)
rng = np.random.default_rng(0)
self.x = sparse.random((100, 100, 100), density=0.01, random_state=rng)
self.y = sparse.random((100, 100, 100), density=0.01, random_state=rng)

self.x + self.y # Numba compilation

Expand All @@ -32,9 +32,9 @@ def time_mul(self):

class ElemwiseBroadcastingSuite:
def setup(self):
np.random.seed(0)
self.x = sparse.random((100, 1, 100), density=0.01)
self.y = sparse.random((100, 100), density=0.01)
rng = np.random.default_rng(0)
self.x = sparse.random((100, 1, 100), density=0.01, random_state=rng)
self.y = sparse.random((100, 100), density=0.01, random_state=rng)

def time_add(self):
self.x + self.y
Expand All @@ -45,9 +45,9 @@ def time_mul(self):

class IndexingSuite:
def setup(self):
np.random.seed(0)
self.index = np.random.randint(0, 100, 50)
self.x = sparse.random((100, 100, 100), density=0.01)
rng = np.random.default_rng(0)
self.index = rng.integers(0, 100, 50)
self.x = sparse.random((100, 100, 100), density=0.01, random_state=rng)

# Numba compilation
self.x[5]
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24 changes: 12 additions & 12 deletions benchmarks/benchmark_gcxs.py
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Expand Up @@ -5,9 +5,9 @@

class MatrixMultiplySuite:
def setup(self):
np.random.seed(0)
self.x = sparse.random((100, 100), density=0.01, format="gcxs")
self.y = sparse.random((100, 100), density=0.01, format="gcxs")
rng = np.random.default_rng(0)
self.x = sparse.random((100, 100), density=0.01, format="gcxs", random_state=rng)
self.y = sparse.random((100, 100), density=0.01, format="gcxs", random_state=rng)

self.x @ self.y # Numba compilation

Expand All @@ -17,9 +17,9 @@ def time_matmul(self):

class ElemwiseSuite:
def setup(self):
np.random.seed(0)
self.x = sparse.random((100, 100, 100), density=0.01, format="gcxs")
self.y = sparse.random((100, 100, 100), density=0.01, format="gcxs")
rng = np.random.default_rng(0)
self.x = sparse.random((100, 100, 100), density=0.01, format="gcxs", random_state=rng)
self.y = sparse.random((100, 100, 100), density=0.01, format="gcxs", random_state=rng)

self.x + self.y # Numba compilation

Expand All @@ -32,9 +32,9 @@ def time_mul(self):

class ElemwiseBroadcastingSuite:
def setup(self):
np.random.seed(0)
self.x = sparse.random((100, 1, 100), density=0.01, format="gcxs")
self.y = sparse.random((100, 100), density=0.01, format="gcxs")
rng = np.random.default_rng(0)
self.x = sparse.random((100, 1, 100), density=0.01, format="gcxs", random_state=rng)
self.y = sparse.random((100, 100), density=0.01, format="gcxs", random_state=rng)

def time_add(self):
self.x + self.y
Expand All @@ -45,9 +45,9 @@ def time_mul(self):

class IndexingSuite:
def setup(self):
np.random.seed(0)
self.index = np.random.randint(0, 100, 50)
self.x = sparse.random((100, 100, 100), density=0.01, format="gcxs")
rng = np.random.default_rng(0)
self.index = rng.integers(0, 100, 50)
self.x = sparse.random((100, 100, 100), density=0.01, format="gcxs", random_state=rng)

# Numba compilation
self.x[5]
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6 changes: 3 additions & 3 deletions benchmarks/benchmark_matmul.py
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Expand Up @@ -7,9 +7,9 @@ class Matmul_Sparse:
params = (["coo", "gcxs"], [0, 1, None])

def setup(self, p, dens_arg):
np.random.seed(0)
self.x = sparse.random((100, 100), density=0.01, format=p)
self.y = sparse.random((100, 100), density=0.01, format=p)
rng = np.random.default_rng(0)
self.x = sparse.random((100, 100), density=0.01, format=p, random_state=rng)
self.y = sparse.random((100, 100), density=0.01, format=p, random_state=rng)

if dens_arg == 0:
self.x = self.x.todense()
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18 changes: 9 additions & 9 deletions benchmarks/benchmark_tensordot.py
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Expand Up @@ -10,9 +10,9 @@ class TensordotSuiteDenseSparse:
"""

def setup(self):
np.random.seed(0)
self.n = np.random.random((100, 100))
self.s = sparse.random((100, 100, 100, 100), density=0.01)
rng = np.random.default_rng(0)
self.n = rng.random((100, 100))
self.s = sparse.random((100, 100, 100, 100), density=0.01, random_state=rng)

def time_dense(self):
sparse.tensordot(self.n, self.s, axes=([0, 1], [0, 2]))
Expand All @@ -28,9 +28,9 @@ class TensordotSuiteSparseSparse:
"""

def setup(self):
np.random.seed(0)
self.s1 = sparse.random((100, 100), density=0.01)
self.s2 = sparse.random((100, 100, 100, 100), density=0.01)
rng = np.random.default_rng(0)
self.s1 = sparse.random((100, 100), density=0.01, random_state=rng)
self.s2 = sparse.random((100, 100, 100, 100), density=0.01, random_state=rng)

def time_dense(self):
sparse.tensordot(self.s1, self.s2, axes=([0, 1], [0, 2]), return_type=np.ndarray)
Expand All @@ -46,9 +46,9 @@ class TensordotSuiteSparseDense:
"""

def setup(self):
np.random.seed(0)
self.s = sparse.random((100, 100, 100, 100), density=0.01)
self.n = np.random.random((100, 100))
rng = np.random.default_rng(0)
self.s = sparse.random((100, 100, 100, 100), density=0.01, random_state=rng)
self.n = rng.random((100, 100))

def time_dense(self):
sparse.tensordot(self.s, self.n, axes=([0, 1], [0, 1]))
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6 changes: 5 additions & 1 deletion pyproject.toml
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Expand Up @@ -55,13 +55,17 @@ include = ["sparse", "sparse.*"]
version_file = "sparse/_version.py"

[tool.ruff]
select = ["F", "E", "W", "I", "B", "UP"]
select = ["F", "E", "W", "I", "B", "UP", "YTT", "BLE", "C4", "T10", "ISC", "ICN", "PIE", "PYI", "RSE", "RET", "SIM", "PGH", "FLY", "NPY", "PERF"]
exclude = ["sparse/_version.py"]
line-length = 120

[tool.ruff.lint.isort.sections]
numpy = ["numpy", "numpy.*", "scipy", "scipy.*"]

[tool.ruff.format]
quote-style = "double"
docstring-code-format = true

[tool.ruff.lint.isort]
section-order = [
"future",
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