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chore: reformat

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This commit is contained in:
can1357
2026-07-15 00:08:50 +02:00
parent 7d02778c60
commit 55f5ebec49
97 changed files with 12237 additions and 3179 deletions
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scripts/session-stats/plot_tools.py
+55 -19
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@@ -15,6 +15,7 @@ N by total tokens (default 10); override with --top N or --tools a,b,c.
Output: scripts/session-stats/out/tool-trends.png + standalone panels.
"""
from __future__ import annotations
import argparse
@@ -39,9 +40,18 @@ TOOL_ALIAS = {"grep": "search"}
# 10-class qualitative palette (tab10) — distinct hues for line + area work.
PALETTE = [
"#1f77b4", "#d62728", "#2ca02c", "#ff7f0e", "#9467bd",
"#8c564b", "#17becf", "#e377c2", "#bcbd22", "#7f7f7f",
"#393b79", "#637939",
"#1f77b4",
"#d62728",
"#2ca02c",
"#ff7f0e",
"#9467bd",
"#8c564b",
"#17becf",
"#e377c2",
"#bcbd22",
"#7f7f7f",
"#393b79",
"#637939",
]
@@ -56,6 +66,7 @@ def normalize_case_sql(col: str) -> str:
# --------------------------------------------------------------------------- #
# Data access
def _connect() -> sqlite3.Connection:
if not DB_PATH.exists():
sys.exit(f"db missing: {DB_PATH}")
@@ -148,7 +159,10 @@ def fetch_per_call(conn: sqlite3.Connection, tools: list[str]) -> dict[str, dict
out: dict[str, dict] = {}
for t, rows in by_tool.items():
if not rows:
out[t] = {"ts": np.array([], dtype=np.int64), "tok": np.array([], dtype=np.int64)}
out[t] = {
"ts": np.array([], dtype=np.int64),
"tok": np.array([], dtype=np.int64),
}
continue
ts = np.fromiter((r[0] for r in rows), dtype=np.int64, count=len(rows))
tok = np.fromiter((r[1] for r in rows), dtype=np.int64, count=len(rows))
@@ -160,6 +174,7 @@ def fetch_per_call(conn: sqlite3.Connection, tools: list[str]) -> dict[str, dict
# --------------------------------------------------------------------------- #
# Helpers
def smooth(y: np.ndarray, w: int = 7) -> np.ndarray:
if w <= 1 or len(y) < w:
return y.astype(float)
@@ -208,7 +223,10 @@ def weekly_median(ts_ms: np.ndarray, tok: np.ndarray) -> tuple[np.ndarray, np.nd
if hi > lo:
p50[i] = np.percentile(tok[lo:hi], 50)
week_dates = np.array(
[datetime.fromtimestamp(int(w) * WEEK_MS / 1000, tz=timezone.utc) for w in weeks]
[
datetime.fromtimestamp(int(w) * WEEK_MS / 1000, tz=timezone.utc)
for w in weeks
]
)
return week_dates, p50
@@ -216,10 +234,15 @@ def weekly_median(ts_ms: np.ndarray, tok: np.ndarray) -> tuple[np.ndarray, np.nd
# --------------------------------------------------------------------------- #
# Panels
def panel_total_tokens(ax: plt.Axes, daily: dict, tools: list[str], colors: dict) -> None:
def panel_total_tokens(
ax: plt.Axes, daily: dict, tools: list[str], colors: dict
) -> None:
dates = daily["dates"]
series = [smooth(daily[t]["args"] + daily[t]["results"]) for t in tools]
ax.stackplot(dates, series, labels=tools, colors=[colors[t] for t in tools], alpha=0.9)
ax.stackplot(
dates, series, labels=tools, colors=[colors[t] for t in tools], alpha=0.9
)
ax.set_title("Daily token volume (args + results, 7d MA)")
ax.set_ylabel("tokens / day")
ax.yaxis.set_major_formatter(plt.FuncFormatter(millions))
@@ -227,17 +250,23 @@ def panel_total_tokens(ax: plt.Axes, daily: dict, tools: list[str], colors: dict
style_time_axis(ax)
def panel_call_counts(ax: plt.Axes, daily: dict, tools: list[str], colors: dict) -> None:
def panel_call_counts(
ax: plt.Axes, daily: dict, tools: list[str], colors: dict
) -> None:
dates = daily["dates"]
for t in tools:
ax.plot(dates, smooth(daily[t]["calls"]), label=t, color=colors[t], linewidth=1.6)
ax.plot(
dates, smooth(daily[t]["calls"]), label=t, color=colors[t], linewidth=1.6
)
ax.set_title("Daily call count (7d MA)")
ax.set_ylabel("calls / day")
ax.legend(loc="upper left", frameon=False, ncol=2, fontsize=9)
style_time_axis(ax)
def panel_mean_per_call(ax: plt.Axes, daily: dict, tools: list[str], colors: dict) -> None:
def panel_mean_per_call(
ax: plt.Axes, daily: dict, tools: list[str], colors: dict
) -> None:
dates = daily["dates"]
for t in tools:
totals = daily[t]["args"] + daily[t]["results"]
@@ -265,7 +294,9 @@ def panel_cumulative(ax: plt.Axes, daily: dict, tools: list[str], colors: dict)
style_time_axis(ax)
def panel_weekly_median(ax: plt.Axes, per_call: dict, tools: list[str], colors: dict) -> None:
def panel_weekly_median(
ax: plt.Axes, per_call: dict, tools: list[str], colors: dict
) -> None:
for t in tools:
w, p50 = weekly_median(per_call[t]["ts"], per_call[t]["tok"])
if w.size == 0:
@@ -279,8 +310,12 @@ def panel_weekly_median(ax: plt.Axes, per_call: dict, tools: list[str], colors:
style_time_axis(ax)
def panel_histogram(ax: plt.Axes, per_call: dict, tools: list[str], colors: dict) -> None:
all_tok = np.concatenate([per_call[t]["tok"] for t in tools if per_call[t]["tok"].size])
def panel_histogram(
ax: plt.Axes, per_call: dict, tools: list[str], colors: dict
) -> None:
all_tok = np.concatenate(
[per_call[t]["tok"] for t in tools if per_call[t]["tok"].size]
)
if all_tok.size == 0:
return
hi = max(all_tok.max(), 10)
@@ -312,6 +347,7 @@ def panel_histogram(ax: plt.Axes, per_call: dict, tools: list[str], colors: dict
# --------------------------------------------------------------------------- #
# Entry
def main() -> int:
ap = argparse.ArgumentParser(description=__doc__.splitlines()[1])
ap.add_argument("--top", type=int, default=10, help="top N tools by total tokens")
@@ -364,12 +400,12 @@ def main() -> int:
print(f"wrote {combined}")
panels: tuple[tuple[str, Callable, dict], ...] = (
("daily-tokens", panel_total_tokens, daily),
("daily-calls", panel_call_counts, daily),
("tokens-per-call", panel_mean_per_call, daily),
("cumulative-tokens", panel_cumulative, daily),
("per-call-median", panel_weekly_median, per_call),
("per-call-histogram", panel_histogram, per_call),
("daily-tokens", panel_total_tokens, daily),
("daily-calls", panel_call_counts, daily),
("tokens-per-call", panel_mean_per_call, daily),
("cumulative-tokens", panel_cumulative, daily),
("per-call-median", panel_weekly_median, per_call),
("per-call-histogram", panel_histogram, per_call),
)
for name, fn, src in panels:
f2, ax = plt.subplots(figsize=(11, 5))