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[pre-commit.ci] pre-commit autoupdate #201

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github-actions merged 2 commits into from
Aug 3, 2026
Merged

[pre-commit.ci] pre-commit autoupdate #201

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2f1af88
[pre-commit.ci] pre-commit autoupdate
pre-commit-ci[bot] Aug 3, 2026
9e23b9d
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Aug 3, 2026
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6 changes: 3 additions & 3 deletions .pre-commit-config.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@ ci:
repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
# Ruff version.
rev: v0.15.20
rev: v0.16.1
hooks:
# Run the linter.
- id: ruff
Expand All @@ -25,15 +25,15 @@ repos:
- id: check-toml
- id: check-yaml
- repo: https://github.com/codespell-project/codespell
rev: v2.4.2
rev: v2.4.3
hooks:
- id: codespell
args: [
"--ignore-words",
".codespellignore",
]
- repo: https://github.com/DavidAnson/markdownlint-cli2 # For formatting markdown for documentation
rev: v0.23.0
rev: v0.23.2
hooks:
- id: markdownlint-cli2
args: [
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12 changes: 6 additions & 6 deletions docs/general/tutorials/3_advanced_tutorial.py
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Expand Up @@ -388,12 +388,12 @@ def __init__(
self.datacollector = DataCollector(
model=self,
model_reporters={
"mean_sugar": lambda m: 0.0
if len(m.sets[0]) == 0
else float(m.sets[0].df["sugar"].mean()),
"total_sugar": lambda m: float(m.sets[0].df["sugar"].sum())
if len(m.sets[0])
else 0.0,
"mean_sugar": lambda m: (
0.0 if len(m.sets[0]) == 0 else float(m.sets[0].df["sugar"].mean())
),
"total_sugar": lambda m: (
float(m.sets[0].df["sugar"].sum()) if len(m.sets[0]) else 0.0
),
"agents_alive": lambda m: float(len(m.sets[0])) if len(m.sets) else 0.0,
"gini": gini,
"corr_sugar_metabolism": corr_sugar_metabolism,
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5 changes: 3 additions & 2 deletions docs/general/tutorials/4_datacollector.py
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Expand Up @@ -56,8 +56,9 @@ def __init__(self, n: int):
},
storage="memory", # we'll switch this per example
storage_uri=None,
trigger=lambda m: m.steps % 2
== 0, # collect every 2 steps via conditional_collect
trigger=lambda m: (
m.steps % 2 == 0
), # collect every 2 steps via conditional_collect
reset_memory=True,
)

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12 changes: 6 additions & 6 deletions examples/sugarscape_ig/backend_frames/model.py
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Expand Up @@ -254,12 +254,12 @@ def __init__(
self.datacollector = DataCollector(
model=self,
model_reporters={
"mean_sugar": lambda m: 0.0
if len(m.sets[0]) == 0
else float(m.sets[0].df["sugar"].mean()),
"total_sugar": lambda m: float(m.sets[0].df["sugar"].sum())
if len(m.sets[0])
else 0.0,
"mean_sugar": lambda m: (
0.0 if len(m.sets[0]) == 0 else float(m.sets[0].df["sugar"].mean())
),
"total_sugar": lambda m: (
float(m.sets[0].df["sugar"].sum()) if len(m.sets[0]) else 0.0
),
"agents_alive": lambda m: float(len(m.sets[0])) if len(m.sets) else 0.0,
"gini": gini,
"corr_sugar_metabolism": corr_sugar_metabolism,
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14 changes: 8 additions & 6 deletions examples/sugarscape_ig/backend_mesa/model.py
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Expand Up @@ -120,12 +120,14 @@ def __init__(
# are comparable across backends.
self.datacollector = DataCollector(
model_reporters={
"mean_sugar": lambda m: float(np.mean([a.sugar for a in m.agent_list]))
if m.agent_list
else 0.0,
"total_sugar": lambda m: float(sum(a.sugar for a in m.agent_list))
if m.agent_list
else 0.0,
"mean_sugar": lambda m: (
float(np.mean([a.sugar for a in m.agent_list]))
if m.agent_list
else 0.0
),
"total_sugar": lambda m: (
float(sum(a.sugar for a in m.agent_list)) if m.agent_list else 0.0
),
"agents_alive": lambda m: float(len(m.agent_list)),
"gini": lambda m: gini(a.sugar for a in m.agent_list),
"corr_sugar_metabolism": lambda m: corr_sugar_metabolism(m),
Expand Down
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