Working stat estimates
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1
.gitignore
vendored
1
.gitignore
vendored
@@ -1 +1,2 @@
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*.venv
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temp.md
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214
main.py
214
main.py
@@ -12,6 +12,7 @@ TORN_API_KEY = "9VLK0Wte1BwXOheB"
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ENEMY_FACTION_ID = 52935
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YOUR_FACTION_ID = 654321
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ALLOWED_CHANNEL_ID = 1442876328536707316
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FFSCOUTER_KEY = "XYmWPO9ZYkLqnv3v"
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POLL_INTERVAL = 30
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HIT_CHECK_INTERVAL = 60
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@@ -47,71 +48,96 @@ class HitDispatchBot(commands.Bot):
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# Create bot now (ONE bot only)
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bot = HitDispatchBot(command_prefix="!", intents=intents)
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# ------------------------------------------------------------------
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# Helper – get a single member's crimes & networth
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# ------------------------------------------------------------------
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async def _get_user_stats(session: aiohttp.ClientSession, user_id: int):
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url = f"https://api.torn.com/v2/user/{user_id}/personalstats?stat=criminaloffenses,networth&key={TORN_API_KEY}"
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async def fetch_ffscouter_stats(session: aiohttp.ClientSession, torn_id: int):
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"""
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Calls FFScouter and returns predicted battle stats.
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Uses an existing aiohttp session (caller must provide).
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"""
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url = f"https://ffscouter.com/api/v1/get-stats?key={FFSCOUTER_KEY}&targets={torn_id}"
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#print(url)
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async with session.get(url) as resp:
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if resp.status != 200:
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print(f"FFScouter Error for {torn_id}:", resp.status)
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return None
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data = await resp.json()
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# FFScouter v1 returns: {"code":200,"message":"OK","data": {"<id>": {...}}}
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if "data" not in data:
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return None
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inner = data["data"]
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return inner.get(str(torn_id))
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crimes = 0
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networth_raw = 0
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for stat in data.get("personalstats", []):
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if stat.get("name") == "criminaloffenses":
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crimes = int(stat.get("value", 0))
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elif stat.get("name") == "networth":
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networth_raw = float(stat.get("value", 0))
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networth_mill = networth_raw / 1_000_000
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return crimes, networth_mill
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# ------------------------------------------------------------------
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# Updated fetch_enemy_faction – now pulls crimes & networth
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# ------------------------------------------------------------------
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async def fetch_enemy_faction():
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"""
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Pulls all active members from the target faction and enriches each
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member with level, crimes and networth (in millions).
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Pulls faction members from Torn (selections=members),
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then fetches FFScouter stats in a single batch request.
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Returns a list of enemies with name, id, level, and estimated BS.
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"""
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url = (
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f"https://api.torn.com/v2/faction/{ENEMY_FACTION_ID}"
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"?selections=members"
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f"&key={TORN_API_KEY}"
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f"?selections=members&key={TORN_API_KEY}"
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)
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enemies = []
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async with aiohttp.ClientSession() as session:
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# --- Fetch faction members ---
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async with session.get(url) as resp:
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if resp.status != 200:
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print("Torn faction fetch error:", resp.status)
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return enemies
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data = await resp.json()
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# The response is a dict → {"members": [ {...}, ... ]}
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members_list = data.get("members", [])
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if not members_list:
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return enemies
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enemies: list[dict] = []
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# --- Build comma-separated list of IDs ---
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member_ids = [
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str(info.get("player_id", info.get("id", 0)))
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for info in members_list
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if info.get("status", {}).get("state", "Unknown") in ("Okay", "Idle")
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]
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if not member_ids:
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return enemies
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ids_str = ",".join(member_ids)
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# --- Single FFScouter batch request ---
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ff_url = f"https://ffscouter.com/api/v1/get-stats?key={FFSCOUTER_KEY}&targets={ids_str}"
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async with session.get(ff_url) as resp:
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if resp.status != 200:
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print("FFScouter batch error:", resp.status)
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ff_data_list = []
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else:
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ff_data_list = await resp.json()
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# --- Map FFScouter data by player_id for quick lookup ---
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ff_map = {str(d["player_id"]): d for d in ff_data_list}
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# --- Build final enemies list ---
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for info in members_list:
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status_state = info["status"]["state"]
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if status_state not in ["Okay", "Idle"]:
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pid = str(info.get("player_id", info.get("id", 0)))
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state = info.get("status", {}).get("state", "Unknown")
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if state not in ("Okay", "Idle"):
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continue
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name = info.get("name", "Unknown")
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level = int(info.get("level", 0))
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# ------------------------------------------------------------------
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# Pull the per‑user stats (crimes & networth)
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# ------------------------------------------------------------------
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crimes, networth_mill = await _get_user_stats(session, info["id"])
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est = ff_map.get(pid, {}).get("bs_estimate_human", "?")
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enemies.append({
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"id": int(info["id"]),
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"name": info["name"],
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"status": status_state,
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"level": level,
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"crimes": crimes,
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"networth": networth_mill, # millions
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"id": int(pid),
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"name": name,
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"level": level,
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"estimate": est
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})
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return enemies
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return enemies
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async def update_enemy_queue_loop():
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global enemy_queue
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@@ -124,86 +150,6 @@ async def update_enemy_queue_loop():
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print(f"Enemy queue updated: {len(enemy_queue)} valid targets.")
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await asyncio.sleep(POLL_INTERVAL)
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# ==============================
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# STAT SYSTEM
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# ==============================
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def estimate_battlestats(level: int, crimes: int, networth: float) -> str:
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"""
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Returns the score‑range string that matches the chart.
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"""
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# ------------------------------------------------------------------
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# Bucket definitions (same as in the original code)
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# ------------------------------------------------------------------
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level_buckets = [
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(6, "2k‑25k"),
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(11, "20k‑25k"),
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(26, "200k‑250k"),
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(31, "2m‑2.5m"),
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(50, "20m‑35m"),
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(float('inf'), "200m‑250m")
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]
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crimes_buckets = [
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(5000, "2k‑25k"),
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(10000, "20k‑25k"),
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(20000, "200k‑250k"),
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(30000, "2m‑2.5m"),
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(50000, "20m‑35m"),
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(float('inf'), "200m‑250m")
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]
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networth_buckets = [
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(50, "2k‑25k"), # < 50 m
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(500, "20k‑25k"), # < 500 m
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(5_000, "200k‑250k"), # < 5 b
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(50_000, "2m‑2.5m"), # < 50 b
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(200_000, "20m‑35m"), # < 200 b
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(float('inf'), "200m‑250m")
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]
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def find_bucket(value: float, buckets):
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for limit, label in buckets:
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if value < limit:
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return label
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return "Unknown"
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lvl_label = find_bucket(level, level_buckets)
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crime_label = find_bucket(crimes, crimes_buckets)
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net_label = find_bucket(networth, networth_buckets)
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# ------------------------------------------------------------------
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# Convert a label like '200k‑250k' into its lower bound in points.
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# We only need the *first* number – everything after the dash is
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# ignored. The unit (k/m/b) tells us how to scale it.
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# ------------------------------------------------------------------
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def score_value(label: str) -> float:
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"""
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Convert a label such as '200k‑250k' or '20m‑35' into the numeric
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lower bound in points.
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"""
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m = re.match(r"(\d+(?:\.\d*)?)([kmb]?)", label, flags=re.IGNORECASE)
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if not m:
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return float('inf') # shouldn't happen
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number_str, unit = m.groups()
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try:
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num = float(number_str)
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except ValueError:
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return float('inf')
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unit = unit.lower()
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if unit == 'm':
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return num * 1_000_000
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if unit == 'k':
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return num * 1_000
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# No unit → plain points
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return num
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chosen_label = min([lvl_label, crime_label, net_label], key=score_value)
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return chosen_label
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# ==============================
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# ASSIGNMENT SYSTEM
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@@ -224,6 +170,7 @@ async def assign_next_target():
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if not enemy_queue:
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return None, None
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# Pop the weakest enemy (already sorted by score_value)
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enemy = enemy_queue.pop(0)
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attacker = get_next_attacker()
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@@ -238,7 +185,6 @@ async def assign_next_target():
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return enemy, attacker
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async def monitor_assignments_loop():
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await bot.wait_until_ready()
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@@ -346,18 +292,22 @@ async def stats(ctx):
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await ctx.send("No active members found.")
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return
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for e in enemies:
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score_range = estimate_battlestats(e["level"], e["crimes"], e["networth"])
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# await ctx.send(
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# f'{e["name"]} (ID:{e["id"]}) | '
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# f'Lv {e["level"]}, Crimes {e["crimes"]}, NetWorth ${e["networth"]:,.1f}m → '
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# f'Score: {score_range}'
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# )
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print(
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f'{e["name"]} (ID:{e["id"]}) | '
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f'Lv {e["level"]}, Crimes {e["crimes"]}, NetWorth ${e["networth"]:,.1f}m → '
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f'Score: {score_range}'
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)
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lines = [
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f"**{e['name']}** (ID:{e['id']}) | Lv {e['level']} | Estimated BS: {e['estimate']}"
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for e in enemies
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]
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# Discord chunking
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chunk = ""
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for line in lines:
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if len(chunk) + len(line) > 1900:
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await ctx.send(chunk)
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chunk = ""
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chunk += line + "\n"
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if chunk:
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await ctx.send(chunk)
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# ==============================
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# BOT READY
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# ==============================
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Block a user