eeaf900e5a
Replace monolithic scraping scripts with sportstime_parser package: - Multi-source scrapers with automatic fallback for 7 sports - Canonical ID generation for games, teams, and stadiums - Fuzzy matching with configurable thresholds for name resolution - CloudKit Web Services uploader with JWT auth, diff-based updates - Resumable uploads with checkpoint state persistence - Validation reports with manual review items and suggested matches - Comprehensive test suite (249 tests) CLI: sportstime-parser scrape|validate|upload|status|retry|clear Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
109 lines
3.5 KiB
Python
109 lines
3.5 KiB
Python
"""Stadium data model for sportstime-parser."""
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from dataclasses import dataclass
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from typing import Optional
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import json
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@dataclass
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class Stadium:
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"""Represents a stadium with all CloudKit fields.
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Attributes:
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id: Canonical stadium ID (e.g., 'stadium_nba_paycom_center')
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sport: Primary sport code (e.g., 'nba', 'mlb')
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name: Current stadium name (e.g., 'Paycom Center')
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city: City name (e.g., 'Oklahoma City')
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state: State/province code (e.g., 'OK', 'ON')
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country: Country code (e.g., 'USA', 'Canada')
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latitude: Latitude coordinate
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longitude: Longitude coordinate
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capacity: Seating capacity
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surface: Playing surface (e.g., 'grass', 'turf', 'hardwood')
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roof_type: Roof type (e.g., 'dome', 'retractable', 'open')
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opened_year: Year stadium opened
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image_url: URL to stadium image
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timezone: IANA timezone (e.g., 'America/Chicago')
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"""
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id: str
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sport: str
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name: str
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city: str
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state: str
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country: str
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latitude: float
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longitude: float
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capacity: Optional[int] = None
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surface: Optional[str] = None
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roof_type: Optional[str] = None
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opened_year: Optional[int] = None
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image_url: Optional[str] = None
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timezone: Optional[str] = None
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def to_dict(self) -> dict:
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"""Convert to dictionary for JSON serialization."""
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return {
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"id": self.id,
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"sport": self.sport,
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"name": self.name,
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"city": self.city,
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"state": self.state,
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"country": self.country,
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"latitude": self.latitude,
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"longitude": self.longitude,
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"capacity": self.capacity,
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"surface": self.surface,
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"roof_type": self.roof_type,
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"opened_year": self.opened_year,
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"image_url": self.image_url,
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"timezone": self.timezone,
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}
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@classmethod
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def from_dict(cls, data: dict) -> "Stadium":
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"""Create a Stadium from a dictionary."""
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return cls(
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id=data["id"],
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sport=data["sport"],
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name=data["name"],
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city=data["city"],
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state=data["state"],
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country=data["country"],
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latitude=data["latitude"],
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longitude=data["longitude"],
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capacity=data.get("capacity"),
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surface=data.get("surface"),
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roof_type=data.get("roof_type"),
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opened_year=data.get("opened_year"),
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image_url=data.get("image_url"),
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timezone=data.get("timezone"),
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)
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def to_json(self) -> str:
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"""Serialize to JSON string."""
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return json.dumps(self.to_dict(), indent=2)
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@classmethod
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def from_json(cls, json_str: str) -> "Stadium":
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"""Deserialize from JSON string."""
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return cls.from_dict(json.loads(json_str))
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def is_in_allowed_region(self) -> bool:
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"""Check if stadium is in USA, Canada, or Mexico."""
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allowed = {"USA", "US", "United States", "Canada", "CA", "Mexico", "MX"}
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return self.country in allowed
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def save_stadiums(stadiums: list[Stadium], filepath: str) -> None:
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"""Save a list of stadiums to a JSON file."""
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with open(filepath, "w", encoding="utf-8") as f:
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json.dump([s.to_dict() for s in stadiums], f, indent=2)
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def load_stadiums(filepath: str) -> list[Stadium]:
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"""Load a list of stadiums from a JSON file."""
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with open(filepath, "r", encoding="utf-8") as f:
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data = json.load(f)
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return [Stadium.from_dict(d) for d in data]
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