firefrost-gaming/skill-seekers-reference
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style: Format all Python files with ruff

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- Formatted 103 files to comply with ruff format requirements
- No code logic changes, only formatting/whitespace
- Fixes CI formatting check failures
This commit is contained in:
yusyus
2026-02-08 14:42:27 +03:00
parent 6e4f623b9d
commit 0265de5816
103 changed files with 2241 additions and 2627 deletions
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10
src/skill_seekers/benchmark/__init__.py
View File

@@ -33,9 +33,9 @@ from .runner import BenchmarkRunner
from .models import BenchmarkReport, Metric
__all__ = [
'Benchmark',
'BenchmarkResult',
'BenchmarkRunner',
'BenchmarkReport',
'Metric',
"Benchmark",
"BenchmarkResult",
"BenchmarkRunner",
"BenchmarkReport",
"Metric",
]

43
src/skill_seekers/benchmark/framework.py
View File

@@ -11,12 +11,7 @@ from typing import Any
from collections.abc import Callable
from pathlib import Path
from .models import (
Metric,
TimingResult,
MemoryUsage,
BenchmarkReport
)
from .models import Metric, TimingResult, MemoryUsage, BenchmarkReport
class BenchmarkResult:
@@ -97,7 +92,7 @@ class BenchmarkResult:
memory=self.memory,
metrics=self.metrics,
system_info=self.system_info,
recommendations=self.recommendations
recommendations=self.recommendations,
)
@@ -161,7 +156,7 @@ class Benchmark:
operation=operation,
duration=duration,
iterations=iterations,
avg_duration=duration / iterations if iterations > 1 else duration
avg_duration=duration / iterations if iterations > 1 else duration,
)
self.result.add_timing(timing)
@@ -201,7 +196,7 @@ class Benchmark:
before_mb=mem_before,
after_mb=mem_after,
peak_mb=peak_memory,
allocated_mb=mem_after - mem_before
allocated_mb=mem_after - mem_before,
)
self.result.add_memory(usage)
@@ -212,7 +207,7 @@ class Benchmark:
*args,
operation: str | None = None,
track_memory: bool = False,
**kwargs
**kwargs,
) -> Any:
"""
Measure function execution.
@@ -260,17 +255,16 @@ class Benchmark:
def load_config(path):
return json.load(open(path))
"""
def decorator(func: Callable) -> Callable:
@functools.wraps(func)
def wrapper(*args, **kwargs):
return self.measure(
func,
*args,
operation=operation,
track_memory=track_memory,
**kwargs
func, *args, operation=operation, track_memory=track_memory, **kwargs
)
return wrapper
return decorator
def metric(self, name: str, value: float, unit: str):
@@ -285,11 +279,7 @@ class Benchmark:
Examples:
benchmark.metric("pages_per_sec", 12.5, "pages/sec")
"""
metric = Metric(
name=name,
value=value,
unit=unit
)
metric = Metric(name=name, value=value, unit=unit)
self.result.add_metric(metric)
def recommend(self, text: str):
@@ -328,7 +318,7 @@ class Benchmark:
path.parent.mkdir(parents=True, exist_ok=True)
with open(path, 'w') as f:
with open(path, "w") as f:
f.write(report.model_dump_json(indent=2))
def analyze(self):
@@ -339,11 +329,7 @@ class Benchmark:
"""
# Analyze timing bottlenecks
if self.result.timings:
sorted_timings = sorted(
self.result.timings,
key=lambda t: t.duration,
reverse=True
)
sorted_timings = sorted(self.result.timings, key=lambda t: t.duration, reverse=True)
slowest = sorted_timings[0]
total_time = sum(t.duration for t in self.result.timings)
@@ -351,7 +337,7 @@ class Benchmark:
if slowest.duration > total_time * 0.5:
self.recommend(
f"Bottleneck: '{slowest.operation}' takes "
f"{slowest.duration:.1f}s ({slowest.duration/total_time*100:.0f}% of total)"
f"{slowest.duration:.1f}s ({slowest.duration / total_time * 100:.0f}% of total)"
)
# Analyze memory usage
@@ -360,8 +346,7 @@ class Benchmark:
if peak > 1000: # >1GB
self.recommend(
f"High memory usage: {peak:.0f}MB peak. "
"Consider processing in batches."
f"High memory usage: {peak:.0f}MB peak. Consider processing in batches."
)
# Check for memory leaks

36
src/skill_seekers/benchmark/models.py
View File

@@ -14,8 +14,7 @@ class Metric(BaseModel):
value: float = Field(..., description="Metric value")
unit: str = Field(..., description="Unit (seconds, bytes, pages/sec, etc.)")
timestamp: datetime = Field(
default_factory=datetime.utcnow,
description="When metric was recorded"
default_factory=datetime.utcnow, description="When metric was recorded"
)
@@ -48,26 +47,13 @@ class BenchmarkReport(BaseModel):
finished_at: datetime = Field(..., description="Finish time")
total_duration: float = Field(..., description="Total duration in seconds")
timings: list[TimingResult] = Field(
default_factory=list,
description="Timing results"
)
memory: list[MemoryUsage] = Field(
default_factory=list,
description="Memory usage results"
)
metrics: list[Metric] = Field(
default_factory=list,
description="Additional metrics"
)
timings: list[TimingResult] = Field(default_factory=list, description="Timing results")
memory: list[MemoryUsage] = Field(default_factory=list, description="Memory usage results")
metrics: list[Metric] = Field(default_factory=list, description="Additional metrics")
system_info: dict[str, Any] = Field(
default_factory=dict,
description="System information"
)
system_info: dict[str, Any] = Field(default_factory=dict, description="System information")
recommendations: list[str] = Field(
default_factory=list,
description="Optimization recommendations"
default_factory=list, description="Optimization recommendations"
)
@property
@@ -89,14 +75,8 @@ class ComparisonReport(BaseModel):
baseline: BenchmarkReport = Field(..., description="Baseline benchmark")
current: BenchmarkReport = Field(..., description="Current benchmark")
improvements: list[str] = Field(
default_factory=list,
description="Performance improvements"
)
regressions: list[str] = Field(
default_factory=list,
description="Performance regressions"
)
improvements: list[str] = Field(default_factory=list, description="Performance improvements")
regressions: list[str] = Field(default_factory=list, description="Performance regressions")
speedup_factor: float = Field(..., description="Overall speedup factor")
memory_change_mb: float = Field(..., description="Memory usage change (MB)")

35
src/skill_seekers/benchmark/runner.py
View File

@@ -46,10 +46,7 @@ class BenchmarkRunner:
self.output_dir.mkdir(parents=True, exist_ok=True)
def run(
self,
name: str,
benchmark_func: Callable[[Benchmark], None],
save: bool = True
self, name: str, benchmark_func: Callable[[Benchmark], None], save: bool = True
) -> BenchmarkReport:
"""
Run single benchmark.
@@ -83,7 +80,7 @@ class BenchmarkRunner:
filename = f"{name}_{timestamp}.json"
path = self.output_dir / filename
with open(path, 'w') as f:
with open(path, "w") as f:
f.write(report.model_dump_json(indent=2))
print(f"📊 Saved benchmark: {path}")
@@ -91,9 +88,7 @@ class BenchmarkRunner:
return report
def run_suite(
self,
benchmarks: dict[str, Callable[[Benchmark], None]],
save: bool = True
self, benchmarks: dict[str, Callable[[Benchmark], None]], save: bool = True
) -> dict[str, BenchmarkReport]:
"""
Run multiple benchmarks.
@@ -122,11 +117,7 @@ class BenchmarkRunner:
return reports
def compare(
self,
baseline_path: Path,
current_path: Path
) -> ComparisonReport:
def compare(self, baseline_path: Path, current_path: Path) -> ComparisonReport:
"""
Compare two benchmark reports.
@@ -215,7 +206,7 @@ class BenchmarkRunner:
improvements=improvements,
regressions=regressions,
speedup_factor=speedup_factor,
memory_change_mb=memory_change_mb
memory_change_mb=memory_change_mb,
)
def list_benchmarks(self) -> list[dict[str, Any]]:
@@ -237,13 +228,15 @@ class BenchmarkRunner:
with open(path) as f:
data = json.load(f)
benchmarks.append({
"name": data["name"],
"path": str(path),
"started_at": data["started_at"],
"duration": data["total_duration"],
"operations": len(data.get("timings", []))
})
benchmarks.append(
{
"name": data["name"],
"path": str(path),
"started_at": data["started_at"],
"duration": data["total_duration"],
"operations": len(data.get("timings", [])),
}
)
except Exception:
# Skip invalid files
continue