Preparing Game Data Starcraft 2 - [repack]

import pandas as pd actions = [] for event in replay.events: if hasattr(event, 'second'): actions.append( 'time_sec': event.second, 'event_type': event.name, 'player': getattr(event, 'player', None), 'unit_type': getattr(event, 'unit_type_name', None), 'position': getattr(event, 'location', None) ) df = pd.DataFrame(actions) Create a time-aligned representation: every 5 seconds, record game state (supply, workers, army, buildings, resources).

for event in replay.events: if event.name == 'UnitBornEvent': print(f"Unit event.unit_type_name born at event.second") if event.name == 'PlayerStatsEvent': print(f"Minerals: event.minerals, Vespene: event.vespene") Store actions as a table: preparing game data starcraft 2

Here’s a comprehensive, step-by-step guide to for machine learning, replay analysis, or build order mining. 1. Understanding SC2 Data Sources You have three primary sources of game data: import pandas as pd actions = [] for event in replay

build_order_vector = [] for second in [60, 120, 180, 240, 300]: units_at_time = [e for e in replay.events if e.second <= second and e.name == 'UnitBornEvent'] build_order_vector.append(len([u for u in units_at_time if 'Zergling' in u.unit_type_name])) Goal: Predict race & opening from first 3 minutes. Extraction Code import sc2reader import pandas as pd replay = sc2reader.load_file("replay.SC2Replay") Understanding SC2 Data Sources You have three primary

df.to_parquet('sc2_actions.parquet', compression='snappy') If you control the game (bot development):