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chore: import upstream snapshot with attribution
2026-07-13 13:25:42 +08:00

124 lines
4.4 KiB
Python

import argparse
import json
from pathlib import Path
from tabulate import tabulate
def get_resolved(path: Path) -> set[str]:
data = json.loads(path.read_text())
if "resolved" in data:
data["resolved_ids"] = data["resolved"]
return set(data["resolved_ids"])
def get_submitted(path: Path) -> set[str]:
return set(json.loads(path.read_text())["submitted_ids"])
def stats_single(path: Path) -> None:
evaluated_ids = sorted(get_submitted(path))
resolved_ids = sorted(get_resolved(path))
print(f"Total evaluated: {len(evaluated_ids)}")
print(f"Total resolved: {len(resolved_ids)}")
def compare_many(paths: list[Path]) -> None:
evaluated_ids = {}
resolved_ids = {}
for path in paths:
evaluated_ids[path] = sorted(get_submitted(path))
resolved_ids[path] = sorted(get_resolved(path))
header: list[str] = ["ID"] + [str(i) for i in range(len(paths))] + ["Success rate"]
table: list[list[str | float | int]] = []
def get_emoji(id: str, path: Path) -> str:
if id not in evaluated_ids[path]:
return "❓"
if id in resolved_ids[path]:
return "✅"
return "❌"
ids_to_compare = set(evaluated_ids[paths[0]])
for id in sorted(ids_to_compare):
row = [id] + [get_emoji(id, path) for path in paths]
n_success = sum(id in resolved_ids[path] for path in paths)
n_evaluated = sum(id in evaluated_ids[path] for path in paths)
row.append(f"{n_success / n_evaluated:.2f}")
table.append(row)
successes: list[str | float] = ["Successes"]
success_rates: list[str | float] = ["Success rates"]
for path in paths:
n_success = sum(id in resolved_ids[path] for id in ids_to_compare)
n_evaluated = sum(id in evaluated_ids[path] for id in ids_to_compare)
successes.append(n_success)
success_rates.append(f"{n_success / n_evaluated:.2f}")
table.append(successes)
table.append(success_rates)
print(tabulate(table, headers=header))
print()
header: list[str] = ["#", "ID", "Successes", "Success rate"]
table: list[list[str | float | int]] = []
for i, path in enumerate(paths):
row = [i, path.parent.name, successes[i + 1], success_rates[i + 1]]
table.append(row)
print(tabulate(table, headers=header))
def compare_pair(new_path: Path, old_path: Path, *, show_same=False) -> None:
evaluated_ids = sorted(get_submitted(new_path))
resolved_ids = sorted(get_resolved(new_path))
old_evaluated_ids = sorted(get_submitted(old_path))
old_resolved_ids = sorted(get_resolved(old_path))
print(f"Total evaluated: new {len(evaluated_ids)}, old {len(old_evaluated_ids)}")
print(f"Total resolved: new {len(resolved_ids)}, old {len(old_resolved_ids)}")
print("-" * 80)
print("Emoji legend:")
print("❓: Not evaluated in old version, so guessing it's either 😀 or 👾")
print("😀: Newly resolved in new version")
print("✅: Resolved in both")
print("❌: Resolved in old, not in new")
print("👾: Unresolved in both")
print("-" * 80)
for id in evaluated_ids:
resolved_now = id in resolved_ids
resolved_before = id in old_resolved_ids
if id not in old_evaluated_ids and resolved_now:
emoji = "😀❓"
elif id not in old_evaluated_ids and not resolved_now:
emoji = "👾❓"
elif resolved_now and not resolved_before:
emoji = "😀"
elif resolved_now and resolved_before:
emoji = "✅"
if not show_same:
continue
elif not resolved_now and resolved_before:
emoji = "❌"
else:
emoji = "👾"
if not show_same:
continue
print(f"{emoji} {id}")
def run_from_cli(_args: list[str] | None = None) -> None:
def get_preds_path(path: Path) -> Path:
if path.is_dir():
return path / "results.json"
return path
parser = argparse.ArgumentParser()
parser.add_argument("paths", type=Path, nargs="+")
parser.add_argument("--show-same", action="store_true")
args = parser.parse_args(_args)
args.paths = [get_preds_path(path) for path in args.paths]
if len(args.paths) == 1:
stats_single(args.paths[0])
elif len(args.paths) == 2:
compare_pair(args.paths[0], args.paths[1], show_same=args.show_same)
else:
compare_many(args.paths)