Files
climperor/web/fetch_pro_matches.py
T
vosonandCursor d9c7b4b7b1 Add star-player matches tab and watchlist-driven fetch.
Ship top-level #/matches with pro watchlist defaults, bump site to 0.5.71, and document the flow in AGENTS/README.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-07-29 16:03:45 +08:00

567 lines
17 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
"""Fetch recent league/tournament matches for OpenDota registered pros.
Default source: web/data/pro_player_watchlist.json (hand-curated star IDs).
Falls back to /proPlayers auto-pick only with --all-pros.
Per player: /players/{id}/matches (lobby practice + tournament), then
/matches/{id} for final items + skill builds.
Output: web/data/pro_matches.json (Climperor web only; not used by recommend).
Usage:
python web/fetch_pro_matches.py
python web/fetch_pro_matches.py --limit 12
python web/fetch_pro_matches.py --players 898754153,Ame
python web/fetch_pro_matches.py --all-pros --limit-pros 20 --with-team
"""
from __future__ import annotations
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
import argparse
import json
import time
import urllib.error
from datetime import datetime, timedelta, timezone
from shared.grid import hero_table
from shared.http_utils import http_json
from shared.paths import DATA
from fetch_hero_matches import (
collect_item_ids,
extract_player_row,
fetch_match,
load_ability_id_map,
)
from fetch_hero_items import load_item_catalog
from fetch_pro_builds import fetch_pro_index
OPENDOTA = "https://api.opendota.com/api"
OUT = DATA / "pro_matches.json"
WATCHLIST = DATA / "pro_player_watchlist.json"
DEFAULT_LIMIT = 8
DEFAULT_LIMIT_PROS = 40
# OpenDota lobby_type: 1=practice, 2=tournament (pro/league biased).
LOBBY_LEAGUE = (1, 2)
def _log(msg: str) -> None:
try:
print(msg, flush=True)
except UnicodeEncodeError:
print(msg.encode("ascii", "backslashreplace").decode("ascii"), flush=True)
def load_watchlist(path: Path) -> list[dict]:
"""Load hand-curated star players from pro_player_watchlist.json."""
if not path.is_file():
return []
try:
raw = json.loads(path.read_text(encoding="utf-8"))
except (OSError, json.JSONDecodeError) as e:
raise SystemExit(f"watchlist read failed: {path}: {e}") from e
players = raw.get("players") if isinstance(raw, dict) else None
if not isinstance(players, list):
raise SystemExit(f"watchlist missing players[]: {path}")
out: list[dict] = []
seen: set[int] = set()
for row in players:
if not isinstance(row, dict):
continue
try:
aid = int(row.get("account_id") or 0)
except (TypeError, ValueError):
continue
if aid <= 0 or aid in seen:
continue
seen.add(aid)
name = row.get("name")
if isinstance(name, str):
name = name.strip() or None
else:
name = None
team_tag = row.get("team_tag")
if isinstance(team_tag, str):
team_tag = team_tag.strip() or None
else:
team_tag = None
team_name = row.get("team_name")
if isinstance(team_name, str):
team_name = team_name.strip() or None
else:
team_name = None
region = row.get("region")
if isinstance(region, str):
region = region.strip().lower() or None
else:
region = None
out.append(
{
"account_id": aid,
"name": name,
"team_tag": team_tag,
"team_name": team_name,
"region": region,
}
)
return out
def parse_pro_filter(raw: str, pro_index: dict[int, dict]) -> list[int]:
"""Comma-separated account ids or registered pro names."""
if not raw.strip():
return []
name_to_id: dict[str, int] = {}
for aid, prof in pro_index.items():
val = prof.get("name")
if isinstance(val, str) and val.strip():
name_to_id[val.strip().lower()] = aid
out: list[int] = []
for part in raw.split(","):
token = part.strip()
if not token:
continue
if token.isdigit():
out.append(int(token))
continue
aid = name_to_id.get(token.lower())
if aid:
out.append(aid)
else:
_log(f" warn: unknown pro {token!r}")
return out
def merge_prof(aid: int, base: dict | None, override: dict | None = None) -> dict:
"""Prefer OpenDota live fields, keep watchlist name/team as fallback."""
out: dict = {
"account_id": aid,
"name": None,
"team_tag": None,
"team_name": None,
"country_code": None,
"last_match_time": None,
}
if isinstance(base, dict):
for key in out:
if key == "account_id":
continue
val = base.get(key)
if val is not None and val != "":
out[key] = val
if isinstance(override, dict):
for key in ("name", "team_tag", "team_name"):
if out.get(key):
continue
val = override.get(key)
if isinstance(val, str) and val.strip():
out[key] = val.strip()
elif val:
out[key] = val
return out
def filter_pros(
pro_index: dict[int, dict],
*,
with_team: bool,
active_days: int | None,
limit_pros: int,
player_ids: list[int],
watchlist: list[dict] | None = None,
) -> list[tuple[int, dict]]:
if player_ids:
rows: list[tuple[int, dict]] = []
for aid in player_ids:
rows.append((aid, merge_prof(aid, pro_index.get(aid))))
return rows
if watchlist:
rows = []
for entry in watchlist:
aid = int(entry["account_id"])
rows.append((aid, merge_prof(aid, pro_index.get(aid), entry)))
return rows
cutoff = None
if active_days is not None and active_days > 0:
cutoff = datetime.now(timezone.utc) - timedelta(days=active_days)
candidates: list[tuple[int, dict, float]] = []
for aid, prof in pro_index.items():
if with_team and not prof.get("team_tag") and not prof.get("team_name"):
continue
last = prof.get("last_match_time")
score = 0.0
if isinstance(last, str) and last.strip():
try:
ts = datetime.fromisoformat(last.replace("Z", "+00:00"))
if cutoff and ts < cutoff:
continue
score = ts.timestamp()
except ValueError:
if cutoff:
continue
candidates.append((aid, prof, score))
candidates.sort(key=lambda t: (-t[2], str(t[1].get("name") or ""), t[0]))
picked = candidates[: max(1, limit_pros)]
return [(aid, merge_prof(aid, prof)) for aid, prof, _ in picked]
def player_match_metas(
account_id: int,
limit: int,
*,
lobby_types: tuple[int, ...] = LOBBY_LEAGUE,
) -> list[dict]:
"""Recent match list rows for a pro (deduped, newest first)."""
per_lt = max(limit, limit // max(1, len(lobby_types)) + 2)
by_id: dict[int, dict] = {}
for lt in lobby_types:
url = f"{OPENDOTA}/players/{account_id}/matches?limit={per_lt}&lobby_type={lt}"
try:
raw = http_json(url)
except (
urllib.error.HTTPError,
urllib.error.URLError,
TimeoutError,
json.JSONDecodeError,
OSError,
):
continue
if not isinstance(raw, list):
continue
for row in raw:
if not isinstance(row, dict):
continue
try:
mid = int(row.get("match_id") or 0)
except (TypeError, ValueError):
continue
if mid <= 0:
continue
prev = by_id.get(mid)
if prev is None:
by_id[mid] = row
continue
try:
st_new = int(row.get("start_time") or 0)
st_old = int(prev.get("start_time") or 0)
except (TypeError, ValueError):
st_new = st_old = 0
if st_new >= st_old:
by_id[mid] = row
ranked = sorted(
by_id.values(),
key=lambda r: (-int(r.get("start_time") or 0), -int(r.get("match_id") or 0)),
)
return ranked[:limit]
def fetch_player_matches(
account_id: int,
*,
limit: int,
id_map: dict[int, str],
catalog: dict[int, dict],
id_to_key: dict[int, str],
delay: float,
lobby_types: tuple[int, ...],
) -> list[dict]:
metas = player_match_metas(account_id, limit, lobby_types=lobby_types)
rows: list[dict] = []
for meta in metas:
try:
mid = int(meta.get("match_id") or 0)
hid = int(meta.get("hero_id") or 0)
except (TypeError, ValueError):
continue
if mid <= 0 or hid <= 0:
continue
detail = fetch_match(mid)
if delay > 0:
time.sleep(delay)
if not detail:
continue
slim = extract_player_row(
detail,
hid,
origin="pro",
id_map=id_map,
item_catalog=catalog,
list_meta=meta,
)
if not slim:
continue
row_aid = slim.get("account_id")
try:
row_aid_i = int(row_aid) if row_aid is not None else 0
except (TypeError, ValueError):
row_aid_i = 0
if row_aid_i and row_aid_i != account_id:
continue
slim["hero_id"] = hid
slim["hero_key"] = id_to_key.get(hid)
lt = meta.get("lobby_type")
try:
slim["lobby_type"] = int(lt) if lt is not None else None
except (TypeError, ValueError):
slim["lobby_type"] = None
rows.append(slim)
return rows
def build_indexes(
by_pro: dict[str, dict],
id_to_key: dict[int, str],
) -> dict[str, dict]:
by_hero: dict[str, list[dict]] = {}
for cell in by_pro.values():
for row in cell.get("matches") or []:
if not isinstance(row, dict):
continue
key = row.get("hero_key")
if not key:
hid = row.get("hero_id")
try:
key = id_to_key.get(int(hid)) if hid is not None else None
except (TypeError, ValueError):
key = None
if not key:
continue
by_hero.setdefault(str(key), []).append(row)
out: dict[str, dict] = {}
for key, rows in by_hero.items():
seen: set[int] = set()
deduped: list[dict] = []
for row in sorted(
rows,
key=lambda r: (-int(r.get("start_time") or 0), -int(r.get("match_id") or 0)),
):
try:
mid = int(row.get("match_id") or 0)
except (TypeError, ValueError):
continue
if mid in seen:
continue
seen.add(mid)
deduped.append(row)
out[key] = {"matches": deduped}
return out
def write_out(
path: Path,
*,
by_pro: dict[str, dict],
by_hero: dict[str, dict],
pros_meta: dict[str, dict],
item_catalog: dict[int, dict],
limit: int,
limit_pros: int,
lobby_types: tuple[int, ...],
player_source: str,
) -> None:
used = collect_item_ids(by_hero)
items_out = {
str(iid): {
"key": item_catalog[iid]["key"],
"dname": item_catalog[iid]["dname"],
"name_loc": item_catalog[iid].get("name_loc") or item_catalog[iid]["dname"],
}
for iid in sorted(used)
if iid in item_catalog
}
match_count = sum(
len(cell.get("matches") or [])
for cell in by_pro.values()
if isinstance(cell, dict)
)
payload = {
"meta": {
"source": "opendota",
"attribution": "https://www.opendota.com",
"fetched_at": datetime.now(timezone.utc).isoformat(),
"player_source": player_source,
"limit_per_pro": limit,
"limit_pros": limit_pros,
"lobby_types": list(lobby_types),
"pro_count": len(by_pro),
"match_count": match_count,
"hero_count": len(by_hero),
"note_zh": (
"OpenDota 明星/职业选手近期联赛/锦标赛对局;"
"默认名单见 web/data/pro_player_watchlist.json"
"lobby_type 1=训练/practice、2=tournament"
"含终局出装、加点与联赛名(若有)。"
),
},
"items": items_out,
"pros": pros_meta,
"by_pro": by_pro,
"by_hero": by_hero,
}
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(
json.dumps(payload, ensure_ascii=False, indent=2) + "\n", encoding="utf-8"
)
def main() -> None:
ap = argparse.ArgumentParser(description=__doc__)
ap.add_argument("--out", type=Path, default=OUT)
ap.add_argument(
"--watchlist",
type=Path,
default=WATCHLIST,
help=f"Star player list JSON (default: {WATCHLIST})",
)
ap.add_argument(
"--limit",
type=int,
default=DEFAULT_LIMIT,
help=f"Matches per pro (default: {DEFAULT_LIMIT})",
)
ap.add_argument(
"--limit-pros",
type=int,
default=DEFAULT_LIMIT_PROS,
help=f"Max pros when --all-pros (default: {DEFAULT_LIMIT_PROS})",
)
ap.add_argument(
"--players",
default="",
help="Comma-separated account_id or registered pro name (overrides watchlist)",
)
ap.add_argument(
"--all-pros",
action="store_true",
help="Ignore watchlist; auto-pick from /proPlayers (see --limit-pros/--with-team)",
)
ap.add_argument(
"--with-team",
action="store_true",
help="With --all-pros: only pros with a team_tag/team_name",
)
ap.add_argument(
"--active-days",
type=int,
default=60,
help="With --all-pros: skip pros idle > N days (0=disable; default: 60)",
)
ap.add_argument("--delay", type=float, default=0.35)
ap.add_argument(
"--include-pubs",
action="store_true",
help="Also include ranked pub lobby_type=7 (high-MMR scrims)",
)
args = ap.parse_args()
limit = max(1, int(args.limit))
limit_pros = max(1, int(args.limit_pros))
active_days = int(args.active_days) if args.active_days > 0 else None
lobby_types: tuple[int, ...] = LOBBY_LEAGUE
if args.include_pubs:
lobby_types = LOBBY_LEAGUE + (7,)
_log("loading pro players ...")
pro_index = fetch_pro_index()
_log(f" {len(pro_index)} registered pros")
player_ids = parse_pro_filter(args.players, pro_index)
watchlist: list[dict] | None = None
player_source = "cli"
if player_ids:
player_source = "cli"
elif not args.all_pros:
watchlist = load_watchlist(args.watchlist)
if not watchlist:
raise SystemExit(
f"Empty/missing watchlist {args.watchlist}. "
"Add players or pass --players / --all-pros."
)
player_source = f"watchlist:{args.watchlist.name}"
_log(f" watchlist {len(watchlist)} players ← {args.watchlist}")
else:
player_source = "proPlayers"
picked = filter_pros(
pro_index,
with_team=args.with_team,
active_days=active_days,
limit_pros=limit_pros,
player_ids=player_ids,
watchlist=watchlist,
)
if not picked:
raise SystemExit("No pros matched filters")
heroes = hero_table()
id_to_key = {int(h["id"]): h["key"] for h in heroes}
catalog, _ = load_item_catalog()
id_map = load_ability_id_map()
by_pro: dict[str, dict] = {}
pros_meta: dict[str, dict] = {}
total_matches = 0
for i, (aid, prof) in enumerate(picked, 1):
label = prof.get("name") or prof.get("team_tag") or str(aid)
_log(f"[{i}/{len(picked)}] {label} ({aid}) ...")
matches = fetch_player_matches(
aid,
limit=limit,
id_map=id_map,
catalog=catalog,
id_to_key=id_to_key,
delay=args.delay,
lobby_types=lobby_types,
)
sid = str(aid)
by_pro[sid] = {
"account_id": aid,
"name": prof.get("name"),
"team_tag": prof.get("team_tag"),
"team_name": prof.get("team_name"),
"country_code": prof.get("country_code"),
"match_count": len(matches),
"matches": matches,
}
pros_meta[sid] = {
"account_id": aid,
"name": prof.get("name"),
"team_tag": prof.get("team_tag"),
"team_name": prof.get("team_name"),
"country_code": prof.get("country_code"),
}
total_matches += len(matches)
_log(f" {len(matches)} matches")
by_hero = build_indexes(by_pro, id_to_key)
write_out(
args.out,
by_pro=by_pro,
by_hero=by_hero,
pros_meta=pros_meta,
item_catalog=catalog,
limit=limit,
limit_pros=len(picked),
lobby_types=lobby_types,
player_source=player_source,
)
_log(
f"done pros={len(by_pro)} matches={total_matches} heroes={len(by_hero)}{args.out}"
)
if __name__ == "__main__":
main()