feat: Feature 1.2 (NBA stats FastAPI service) + Feature 1.4 (database schema)

Feature 1.2: Python FastAPI microservice wrapping nba_api
- GET /stats/season-avg, /stats/last-n, /stats/splits, /players/search
- Redis caching (24hr/1hr/6hr/7day), 0.6s rate limiting, PRA derived stat
- 27 Python tests passing

Feature 1.4: Complete Supabase database schema
- 6 tables: users, picks, scan_sessions, bets, outcomes, performance
- RLS enabled on all tables with auth.uid() policies
- 3 triggers: auto-create user, updated_at, scan count reset
- 37 schema validation tests passing
- Migration SQL ready, pending manual apply (WSL2 DNS blocker)

Total: 92 tests (65 Node.js + 27 Python), all passing

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Kev
2026-03-21 10:58:58 -04:00
parent 00409fd6cd
commit 3da1b4242c
27 changed files with 2360 additions and 16 deletions
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import os
REDIS_URL = os.getenv("REDIS_URL", "redis://127.0.0.1:6379")
# Cache TTLs in seconds
SEASON_AVG_TTL = 86400 # 24 hours
LAST_N_TTL = 3600 # 1 hour
SPLITS_TTL = 21600 # 6 hours
PLAYER_SEARCH_TTL = 604800 # 7 days
# nba_api rate limiting
NBA_API_DELAY = 0.6 # seconds between calls
NBA_API_RETRY_DELAY = 2.0
NBA_API_TIMEOUT = 30
# Service
PORT = int(os.getenv("NBA_SERVICE_PORT", "8000"))
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from fastapi import FastAPI, HTTPException, Query
from app.services.stats import get_season_avg, get_last_n, get_splits
from app.utils.player_map import search_players
from app.utils.cache import cache_health
app = FastAPI(title="BetonBLK NBA Stats Service", version="1.0.0")
VALID_STAT_TYPES = {
"points", "rebounds", "assists", "threes", "blocks",
"steals", "pra", "turnovers", "minutes", "games_played",
}
VALID_SPLIT_TYPES = {"home_away", "rest_days", "vs_team"}
@app.get("/health")
async def health():
return {"status": "ok", "cache": "connected" if cache_health() else "disconnected"}
@app.get("/players/search")
async def player_search(name: str = Query(..., min_length=2)):
results = search_players(name)
if not results:
raise HTTPException(status_code=404, detail=f"Player not found: {name}")
return {"results": results}
@app.get("/stats/season-avg")
async def season_avg(
player: str = Query(..., min_length=2),
stat_type: str = Query(None),
season: str = Query(None),
):
if stat_type and stat_type not in VALID_STAT_TYPES:
raise HTTPException(status_code=400, detail=f"Invalid stat_type: {stat_type}")
try:
result = get_season_avg(player, stat_type=stat_type, season=season)
except Exception as e:
raise HTTPException(status_code=503, detail="NBA stats service unavailable")
if result is None:
raise HTTPException(status_code=404, detail=f"Player not found: {player}")
return result
@app.get("/stats/last-n")
async def last_n(
player: str = Query(..., min_length=2),
n: int = Query(10, ge=1, le=30),
stat_type: str = Query(None),
):
if stat_type and stat_type not in VALID_STAT_TYPES:
raise HTTPException(status_code=400, detail=f"Invalid stat_type: {stat_type}")
try:
result = get_last_n(player, n=n, stat_type=stat_type)
except Exception as e:
raise HTTPException(status_code=503, detail="NBA stats service unavailable")
if result is None:
raise HTTPException(status_code=404, detail=f"Player not found: {player}")
return result
@app.get("/stats/splits")
async def splits(
player: str = Query(..., min_length=2),
stat_type: str = Query(...),
split_type: str = Query(...),
opponent: str = Query(None),
):
if stat_type not in VALID_STAT_TYPES:
raise HTTPException(status_code=400, detail=f"Invalid stat_type: {stat_type}")
if split_type not in VALID_SPLIT_TYPES:
raise HTTPException(status_code=400, detail=f"Invalid split_type: {split_type}")
if split_type == "vs_team" and not opponent:
raise HTTPException(status_code=400, detail="opponent is required when split_type=vs_team")
try:
result = get_splits(player, stat_type, split_type, opponent=opponent)
except Exception as e:
raise HTTPException(status_code=503, detail="NBA stats service unavailable")
if result is None:
raise HTTPException(status_code=404, detail=f"Player not found: {player}")
return result
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import time
from datetime import datetime, timedelta, timezone
from nba_api.stats.endpoints import playercareerstats, playergamelog
from nba_api.stats.library.parameters import SeasonAll
from app.utils.cache import cache_get, cache_set
from app.utils.player_map import resolve_player
from app.config import (
SEASON_AVG_TTL, LAST_N_TTL, SPLITS_TTL, NBA_API_DELAY,
NBA_API_RETRY_DELAY, NBA_API_TIMEOUT,
)
# Map nba_api columns to our internal stat names
STAT_MAP = {
"PTS": "points",
"REB": "rebounds",
"AST": "assists",
"FG3M": "threes",
"BLK": "blocks",
"STL": "steals",
"TOV": "turnovers",
"MIN": "minutes",
"GP": "games_played",
}
def get_current_season():
"""Return current NBA season string (e.g., '2025-26'). Season starts in October."""
now = datetime.now(timezone.utc)
year = now.year if now.month >= 10 else now.year - 1
return f"{year}-{str(year + 1)[-2:]}"
def _call_nba_api(fn, **kwargs):
"""Call nba_api with rate limiting and retry."""
time.sleep(NBA_API_DELAY)
try:
return fn(**kwargs, timeout=NBA_API_TIMEOUT)
except Exception:
time.sleep(NBA_API_RETRY_DELAY)
return fn(**kwargs, timeout=NBA_API_TIMEOUT)
def _map_stats(row):
"""Convert a single nba_api stats row to our internal format."""
stats = {}
for nba_col, our_name in STAT_MAP.items():
val = row.get(nba_col)
if val is not None:
stats[our_name] = round(float(val), 1)
# Compute PRA
pts = stats.get("points", 0)
reb = stats.get("rebounds", 0)
ast = stats.get("assists", 0)
stats["pra"] = round(pts + reb + ast, 1)
return stats
def _extract_team(career_data, season):
"""Extract team abbreviation from career stats for given season."""
rows = career_data.get_data_frames()[0]
season_row = rows[rows["SEASON_ID"] == season]
if not season_row.empty:
return season_row.iloc[0]["TEAM_ABBREVIATION"]
if not rows.empty:
return rows.iloc[-1]["TEAM_ABBREVIATION"]
return "UNK"
def get_season_avg(player_name, stat_type=None, season=None):
"""Get a player's season averages."""
player_id, full_name = resolve_player(player_name)
if player_id is None:
return None
if season is None:
season = get_current_season()
cache_key = f"nba:season:{player_id}:{season}"
cached = cache_get(cache_key)
if cached is not None:
result = cached
result["source"] = "cache"
if stat_type and stat_type in result["stats"]:
result["stats"] = {stat_type: result["stats"][stat_type]}
return result
career = _call_nba_api(playercareerstats.PlayerCareerStats, player_id=player_id)
df = career.get_data_frames()[0]
season_row = df[df["SEASON_ID"] == season]
if season_row.empty:
return {
"player": full_name,
"player_id": player_id,
"team": "UNK",
"season": season,
"source": "live",
"stats": {},
}
row = season_row.iloc[0].to_dict()
team = row.get("TEAM_ABBREVIATION", "UNK")
stats = _map_stats(row)
result = {
"player": full_name,
"player_id": player_id,
"team": team,
"season": season,
"source": "live",
"stats": stats,
}
cache_set(cache_key, result, SEASON_AVG_TTL)
if stat_type and stat_type in result["stats"]:
result_filtered = dict(result)
result_filtered["stats"] = {stat_type: result["stats"][stat_type]}
return result_filtered
return result
def get_last_n(player_name, n=10, stat_type=None):
"""Get a player's averages over their last N games."""
player_id, full_name = resolve_player(player_name)
if player_id is None:
return None
n = min(max(n, 1), 30)
cache_key = f"nba:last:{player_id}:{n}"
cached = cache_get(cache_key)
if cached is not None:
result = cached
result["source"] = "cache"
if stat_type and stat_type in result["stats"]:
result["stats"] = {stat_type: result["stats"][stat_type]}
return result
season = get_current_season()
gamelog = _call_nba_api(
playergamelog.PlayerGameLog,
player_id=player_id,
season=season,
)
df = gamelog.get_data_frames()[0]
if df.empty:
return {
"player": full_name,
"player_id": player_id,
"team": "UNK",
"last_n": n,
"source": "live",
"stats": {},
}
last_n_df = df.head(n)
team = last_n_df.iloc[0].get("TEAM_ABBREVIATION", "UNK") if not last_n_df.empty else "UNK"
# Compute averages
avg_row = {}
for col in STAT_MAP:
if col in last_n_df.columns:
avg_row[col] = last_n_df[col].mean()
avg_row["GP"] = len(last_n_df)
stats = _map_stats(avg_row)
result = {
"player": full_name,
"player_id": player_id,
"team": team,
"last_n": n,
"source": "live",
"stats": stats,
}
cache_set(cache_key, result, LAST_N_TTL)
if stat_type and stat_type in result["stats"]:
result_filtered = dict(result)
result_filtered["stats"] = {stat_type: result["stats"][stat_type]}
return result_filtered
return result
def get_splits(player_name, stat_type, split_type, opponent=None):
"""Get situational splits for a player."""
player_id, full_name = resolve_player(player_name)
if player_id is None:
return None
cache_key = f"nba:splits:{player_id}:{stat_type}:{split_type}"
if opponent:
cache_key += f":{opponent}"
cached = cache_get(cache_key)
if cached is not None:
cached["source"] = "cache"
return cached
season = get_current_season()
gamelog = _call_nba_api(
playergamelog.PlayerGameLog,
player_id=player_id,
season=season,
)
df = gamelog.get_data_frames()[0]
if df.empty:
return {
"player": full_name,
"player_id": player_id,
"stat_type": stat_type,
"split_type": split_type,
"source": "live",
"splits": {},
}
# Map stat_type to nba_api column
reverse_map = {v: k for k, v in STAT_MAP.items()}
if stat_type == "pra":
nba_cols = ["PTS", "REB", "AST"]
else:
nba_col = reverse_map.get(stat_type)
if nba_col is None or nba_col not in df.columns:
return None
nba_cols = [nba_col]
def avg_stat(subset):
if subset.empty:
return 0
if stat_type == "pra":
return round((subset["PTS"] + subset["REB"] + subset["AST"]).mean(), 1)
return round(subset[nba_cols[0]].mean(), 1)
team = df.iloc[0].get("TEAM_ABBREVIATION", "UNK") if not df.empty else "UNK"
if split_type == "home_away":
# MATCHUP contains "vs." for home games, "@" for away
home = df[df["MATCHUP"].str.contains("vs.", na=False)]
away = df[df["MATCHUP"].str.contains("@", na=False)]
splits = {
"home": {"avg": avg_stat(home), "games": len(home)},
"away": {"avg": avg_stat(away), "games": len(away)},
}
elif split_type == "rest_days":
df = df.copy()
df["GAME_DATE_PARSED"] = df["GAME_DATE"].apply(_parse_game_date)
df = df.sort_values("GAME_DATE_PARSED")
b2b = []
one_day = []
two_plus = []
dates = df["GAME_DATE_PARSED"].tolist()
for i, row_idx in enumerate(df.index):
if i == 0:
two_plus.append(row_idx)
continue
delta = (dates[i] - dates[i - 1]).days
if delta <= 1:
b2b.append(row_idx)
elif delta == 2:
one_day.append(row_idx)
else:
two_plus.append(row_idx)
splits = {
"b2b": {"avg": avg_stat(df.loc[b2b]) if b2b else 0, "games": len(b2b)},
"1_day_rest": {"avg": avg_stat(df.loc[one_day]) if one_day else 0, "games": len(one_day)},
"2_plus_days_rest": {"avg": avg_stat(df.loc[two_plus]) if two_plus else 0, "games": len(two_plus)},
}
elif split_type == "vs_team":
if not opponent:
return None
opponent_upper = opponent.upper()
vs_opp = df[df["MATCHUP"].str.contains(opponent_upper, na=False)]
vs_others = df[~df["MATCHUP"].str.contains(opponent_upper, na=False)]
splits = {
"vs_opponent": {"avg": avg_stat(vs_opp), "games": len(vs_opp)},
"vs_all_others": {"avg": avg_stat(vs_others), "games": len(vs_others)},
}
else:
return None
result = {
"player": full_name,
"player_id": player_id,
"team": team,
"stat_type": stat_type,
"split_type": split_type,
"source": "live",
"splits": splits,
}
if opponent:
result["opponent"] = opponent
cache_set(cache_key, result, SPLITS_TTL)
return result
def _parse_game_date(date_str):
"""Parse game date from nba_api format. Handles 'MAR 21, 2026' and similar."""
for fmt in ("%b %d, %Y", "%Y-%m-%d", "%m/%d/%Y"):
try:
return datetime.strptime(date_str, fmt)
except (ValueError, TypeError):
continue
return datetime.now(timezone.utc)
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import json
import redis as redis_lib
from app.config import REDIS_URL
_client = None
def get_redis():
global _client
if _client is None:
_client = redis_lib.from_url(REDIS_URL, decode_responses=True)
return _client
def cache_get(key):
r = get_redis()
data = r.get(key)
if data is not None:
return json.loads(data)
return None
def cache_set(key, value, ttl):
r = get_redis()
r.set(key, json.dumps(value), ex=ttl)
def cache_health():
try:
r = get_redis()
r.ping()
return True
except Exception:
return False
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from nba_api.stats.static import players
from app.utils.cache import cache_get, cache_set
from app.config import PLAYER_SEARCH_TTL
def normalize_name(name):
return name.strip().lower()
def search_players(name):
cache_key = f"nba:player:{normalize_name(name)}"
cached = cache_get(cache_key)
if cached is not None:
return cached
all_players = players.get_players()
search_lower = normalize_name(name)
matches = []
for p in all_players:
full_name = p["full_name"].lower()
if search_lower in full_name:
matches.append({
"player_id": p["id"],
"full_name": p["full_name"],
"is_active": p["is_active"],
})
cache_set(cache_key, matches, PLAYER_SEARCH_TTL)
return matches
def resolve_player(name):
"""Resolve a player name to a single active player. Returns (player_id, full_name) or raises."""
matches = search_players(name)
active = [m for m in matches if m["is_active"]]
if not active:
if matches:
# Return first inactive match as fallback
return matches[0]["player_id"], matches[0]["full_name"]
return None, None
# Prefer exact match
search_lower = normalize_name(name)
for m in active:
if m["full_name"].lower() == search_lower:
return m["player_id"], m["full_name"]
return active[0]["player_id"], active[0]["full_name"]
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fastapi==0.115.12
uvicorn==0.34.2
nba_api==1.11.4
redis==5.3.0
httpx==0.28.1
pytest==8.3.5
pytest-asyncio==0.25.3
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import pytest
from unittest.mock import patch, MagicMock
import pandas as pd
MOCK_PLAYERS = [{"id": 203999, "full_name": "Nikola Jokic", "is_active": True}]
MOCK_CAREER_DF = pd.DataFrame([{
"SEASON_ID": "2025-26",
"TEAM_ABBREVIATION": "DEN",
"PTS": 26.3, "REB": 12.4, "AST": 9.1, "FG3M": 1.1,
"BLK": 0.7, "STL": 1.4, "TOV": 3.2, "MIN": 34.2, "GP": 65,
}])
MOCK_GAMELOG_DF = pd.DataFrame([
{
"GAME_DATE": "MAR 21, 2026", "MATCHUP": "DEN vs. LAL",
"TEAM_ABBREVIATION": "DEN",
"PTS": 30, "REB": 15, "AST": 10, "FG3M": 2, "BLK": 1, "STL": 2, "TOV": 3, "MIN": 36,
},
{
"GAME_DATE": "MAR 20, 2026", "MATCHUP": "DEN @ PHX",
"TEAM_ABBREVIATION": "DEN",
"PTS": 22, "REB": 10, "AST": 8, "FG3M": 0, "BLK": 0, "STL": 1, "TOV": 4, "MIN": 32,
},
{
"GAME_DATE": "MAR 18, 2026", "MATCHUP": "DEN vs. LAL",
"TEAM_ABBREVIATION": "DEN",
"PTS": 28, "REB": 12, "AST": 9, "FG3M": 1, "BLK": 1, "STL": 1, "TOV": 2, "MIN": 35,
},
{
"GAME_DATE": "MAR 16, 2026", "MATCHUP": "DEN @ GSW",
"TEAM_ABBREVIATION": "DEN",
"PTS": 24, "REB": 11, "AST": 7, "FG3M": 1, "BLK": 0, "STL": 2, "TOV": 3, "MIN": 33,
},
{
"GAME_DATE": "MAR 14, 2026", "MATCHUP": "DEN vs. MIA",
"TEAM_ABBREVIATION": "DEN",
"PTS": 26, "REB": 13, "AST": 11, "FG3M": 2, "BLK": 1, "STL": 1, "TOV": 2, "MIN": 37,
},
])
def _mock_career(*args, **kwargs):
m = MagicMock()
m.get_data_frames.return_value = [MOCK_CAREER_DF]
return m
def _mock_gamelog(*args, **kwargs):
m = MagicMock()
m.get_data_frames.return_value = [MOCK_GAMELOG_DF]
return m
@pytest.fixture
def mock_nba_api():
"""Mocks all external dependencies: nba_api, Redis cache, rate limiter."""
with patch("app.services.stats.playercareerstats.PlayerCareerStats", side_effect=_mock_career), \
patch("app.services.stats.playergamelog.PlayerGameLog", side_effect=_mock_gamelog), \
patch("app.utils.player_map.players.get_players", return_value=MOCK_PLAYERS), \
patch("app.services.stats.cache_get", return_value=None), \
patch("app.services.stats.cache_set"), \
patch("app.utils.player_map.cache_get", return_value=None), \
patch("app.utils.player_map.cache_set"), \
patch("app.services.stats.time.sleep"):
yield
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import sys
import os
import pytest
from unittest.mock import patch, MagicMock
from httpx import AsyncClient, ASGITransport
import pandas as pd
sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
from app.main import app
MOCK_CAREER_DF = pd.DataFrame([{
"SEASON_ID": "2025-26",
"TEAM_ABBREVIATION": "DEN",
"PTS": 26.3, "REB": 12.4, "AST": 9.1, "FG3M": 1.1,
"BLK": 0.7, "STL": 1.4, "TOV": 3.2, "MIN": 34.2, "GP": 65,
}])
MOCK_GAMELOG_DF = pd.DataFrame([
{
"GAME_DATE": "MAR 21, 2026", "MATCHUP": "DEN vs. LAL",
"TEAM_ABBREVIATION": "DEN",
"PTS": 30, "REB": 15, "AST": 10, "FG3M": 2, "BLK": 1, "STL": 2, "TOV": 3, "MIN": 36,
},
{
"GAME_DATE": "MAR 20, 2026", "MATCHUP": "DEN @ PHX",
"TEAM_ABBREVIATION": "DEN",
"PTS": 22, "REB": 10, "AST": 8, "FG3M": 0, "BLK": 0, "STL": 1, "TOV": 4, "MIN": 32,
},
])
MOCK_PLAYERS = [{"id": 203999, "full_name": "Nikola Jokic", "is_active": True}]
def mock_career(*args, **kwargs):
m = MagicMock()
m.get_data_frames.return_value = [MOCK_CAREER_DF]
return m
def mock_gamelog(*args, **kwargs):
m = MagicMock()
m.get_data_frames.return_value = [MOCK_GAMELOG_DF]
return m
@pytest.fixture
def mock_nba_api():
with patch("app.services.stats.playercareerstats.PlayerCareerStats", side_effect=mock_career), \
patch("app.services.stats.playergamelog.PlayerGameLog", side_effect=mock_gamelog), \
patch("app.utils.player_map.players.get_players", return_value=MOCK_PLAYERS), \
patch("app.services.stats.cache_get", return_value=None), \
patch("app.services.stats.cache_set"), \
patch("app.utils.player_map.cache_get", return_value=None), \
patch("app.utils.player_map.cache_set"), \
patch("app.services.stats.time.sleep"):
yield
@pytest.mark.asyncio
async def test_health():
with patch("app.main.cache_health", return_value=True):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
resp = await client.get("/health")
assert resp.status_code == 200
assert resp.json()["status"] == "ok"
@pytest.mark.asyncio
async def test_player_search(mock_nba_api):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
resp = await client.get("/players/search?name=Jokic")
assert resp.status_code == 200
assert len(resp.json()["results"]) > 0
assert resp.json()["results"][0]["full_name"] == "Nikola Jokic"
@pytest.mark.asyncio
async def test_player_search_not_found():
with patch("app.utils.player_map.players.get_players", return_value=[]), \
patch("app.utils.player_map.cache_get", return_value=None), \
patch("app.utils.player_map.cache_set"):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
resp = await client.get("/players/search?name=Zzzzzzz")
assert resp.status_code == 404
@pytest.mark.asyncio
async def test_season_avg(mock_nba_api):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
resp = await client.get("/stats/season-avg?player=Nikola Jokic&season=2025-26")
assert resp.status_code == 200
data = resp.json()
assert data["player"] == "Nikola Jokic"
assert data["team"] == "DEN"
assert "points" in data["stats"]
assert "pra" in data["stats"]
@pytest.mark.asyncio
async def test_season_avg_invalid_stat_type(mock_nba_api):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
resp = await client.get("/stats/season-avg?player=Jokic&stat_type=invalid")
assert resp.status_code == 400
@pytest.mark.asyncio
async def test_last_n(mock_nba_api):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
resp = await client.get("/stats/last-n?player=Nikola Jokic&n=2")
assert resp.status_code == 200
data = resp.json()
assert data["last_n"] == 2
assert "points" in data["stats"]
@pytest.mark.asyncio
async def test_last_n_clamps_max(mock_nba_api):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
resp = await client.get("/stats/last-n?player=Nikola Jokic&n=50")
# FastAPI validates n <= 30, returns 422
assert resp.status_code == 422
@pytest.mark.asyncio
async def test_splits_home_away(mock_nba_api):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
resp = await client.get("/stats/splits?player=Nikola Jokic&stat_type=points&split_type=home_away")
assert resp.status_code == 200
data = resp.json()
assert "home" in data["splits"]
assert "away" in data["splits"]
@pytest.mark.asyncio
async def test_splits_vs_team_requires_opponent(mock_nba_api):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
resp = await client.get("/stats/splits?player=Jokic&stat_type=points&split_type=vs_team")
assert resp.status_code == 400
assert "opponent" in resp.json()["detail"]
@pytest.mark.asyncio
async def test_splits_invalid_split_type(mock_nba_api):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
resp = await client.get("/stats/splits?player=Jokic&stat_type=points&split_type=invalid")
assert resp.status_code == 400
@pytest.mark.asyncio
async def test_season_avg_player_not_found():
with patch("app.utils.player_map.players.get_players", return_value=[]), \
patch("app.utils.player_map.cache_get", return_value=None), \
patch("app.utils.player_map.cache_set"), \
patch("app.services.stats.cache_get", return_value=None), \
patch("app.services.stats.time.sleep"):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
resp = await client.get("/stats/season-avg?player=Nobody")
assert resp.status_code == 404
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import sys
import os
import pytest
from unittest.mock import patch
sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
from app.services.stats import (
_map_stats,
get_current_season,
get_season_avg,
get_last_n,
get_splits,
)
class TestMapStats:
def test_maps_all_nba_api_columns(self):
row = {
"PTS": 26.3, "REB": 12.4, "AST": 9.1, "FG3M": 1.1,
"BLK": 0.7, "STL": 1.4, "TOV": 3.2, "MIN": 34.2, "GP": 65,
}
result = _map_stats(row)
assert result["points"] == 26.3
assert result["rebounds"] == 12.4
assert result["assists"] == 9.1
assert result["threes"] == 1.1
assert result["blocks"] == 0.7
assert result["steals"] == 1.4
assert result["turnovers"] == 3.2
assert result["minutes"] == 34.2
assert result["games_played"] == 65.0
def test_computes_pra(self):
row = {"PTS": 25.0, "REB": 10.0, "AST": 8.0}
result = _map_stats(row)
assert result["pra"] == 43.0
def test_handles_missing_stats(self):
row = {}
result = _map_stats(row)
assert result["pra"] == 0
assert "points" not in result
def test_rounds_to_one_decimal(self):
row = {"PTS": 26.333333}
result = _map_stats(row)
assert result["points"] == 26.3
class TestGetCurrentSeason:
def test_current_season_format(self):
season = get_current_season()
assert len(season) == 7
assert "-" in season
year = int(season[:4])
suffix = int(season[5:])
assert suffix == (year + 1) % 100
class TestGetSeasonAvg:
def test_returns_season_averages(self, mock_nba_api):
result = get_season_avg("Nikola Jokic", season="2025-26")
assert result is not None
assert result["player"] == "Nikola Jokic"
assert result["team"] == "DEN"
assert result["stats"]["points"] == 26.3
assert result["stats"]["pra"] == 47.8
assert result["source"] == "live"
def test_filters_by_stat_type(self, mock_nba_api):
result = get_season_avg("Nikola Jokic", stat_type="points", season="2025-26")
assert list(result["stats"].keys()) == ["points"]
def test_returns_cache_when_available(self):
cached = {
"player": "Nikola Jokic", "player_id": 203999, "team": "DEN",
"season": "2025-26", "source": "live", "stats": {"points": 26.3},
}
with patch("app.services.stats.cache_get", return_value=cached), \
patch("app.utils.player_map.cache_get", return_value=None), \
patch("app.utils.player_map.cache_set"), \
patch("app.utils.player_map.players.get_players", return_value=[
{"id": 203999, "full_name": "Nikola Jokic", "is_active": True}
]), \
patch("app.services.stats.time.sleep"):
result = get_season_avg("Nikola Jokic", season="2025-26")
assert result["source"] == "cache"
class TestGetLastN:
def test_returns_last_n_averages(self, mock_nba_api):
result = get_last_n("Nikola Jokic", n=5)
assert result is not None
assert result["last_n"] == 5
assert result["stats"]["games_played"] == 5.0
assert result["source"] == "live"
assert result["stats"]["points"] == 26.0
def test_clamps_n_to_max_30(self, mock_nba_api):
result = get_last_n("Nikola Jokic", n=50)
assert result["last_n"] == 30
class TestGetSplits:
def test_home_away_split(self, mock_nba_api):
result = get_splits("Nikola Jokic", "points", "home_away")
assert result is not None
assert "home" in result["splits"]
assert "away" in result["splits"]
assert result["splits"]["home"]["games"] == 3
assert result["splits"]["away"]["games"] == 2
def test_rest_days_split(self, mock_nba_api):
result = get_splits("Nikola Jokic", "points", "rest_days")
assert result is not None
assert "b2b" in result["splits"]
assert "1_day_rest" in result["splits"]
assert "2_plus_days_rest" in result["splits"]
def test_vs_team_split(self, mock_nba_api):
result = get_splits("Nikola Jokic", "points", "vs_team", opponent="LAL")
assert result is not None
assert "vs_opponent" in result["splits"]
assert "vs_all_others" in result["splits"]
assert result["splits"]["vs_opponent"]["games"] == 2
def test_vs_team_requires_opponent(self, mock_nba_api):
result = get_splits("Nikola Jokic", "points", "vs_team", opponent=None)
assert result is None
class TestPlayerNotFound:
@patch("app.utils.player_map.players.get_players", return_value=[])
@patch("app.utils.player_map.cache_get", return_value=None)
@patch("app.utils.player_map.cache_set")
def test_season_avg_returns_none(self, mock_set, mock_get, mock_players):
result = get_season_avg("Nonexistent Player")
assert result is None
@patch("app.utils.player_map.players.get_players", return_value=[])
@patch("app.utils.player_map.cache_get", return_value=None)
@patch("app.utils.player_map.cache_set")
def test_last_n_returns_none(self, mock_set, mock_get, mock_players):
result = get_last_n("Nonexistent Player")
assert result is None