austindavis
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Upload prepare.py
Browse files- prepare.py +145 -0
prepare.py
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import os
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import re
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import io
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import requests
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from zipfile import ZipFile
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from tqdm import tqdm
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import chess.pgn as pgn
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import pandas as pd
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from datasets import Dataset, DatasetInfo
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tqdm.pandas()
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ZIP_URLS = [
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"https://database.nikonoel.fr/lichess_elite_2023-01.zip",
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"https://database.nikonoel.fr/lichess_elite_2023-02.zip",
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"https://database.nikonoel.fr/lichess_elite_2023-03.zip",
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"https://database.nikonoel.fr/lichess_elite_2023-04.zip",
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"https://database.nikonoel.fr/lichess_elite_2023-05.zip",
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"https://database.nikonoel.fr/lichess_elite_2023-06.zip",
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"https://database.nikonoel.fr/lichess_elite_2023-07.zip",
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"https://database.nikonoel.fr/lichess_elite_2023-08.zip",
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"https://database.nikonoel.fr/lichess_elite_2023-09.zip",
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"https://database.nikonoel.fr/lichess_elite_2023-10.zip",
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"https://database.nikonoel.fr/lichess_elite_2023-11.zip",
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"https://database.nikonoel.fr/lichess_elite_2023-12.zip",
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]
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def download_and_unzip(url, save_directory, force_download=False):
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# Extract the filename from the URL
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filename = url.split("/")[-1]
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file_path = os.path.join(save_directory, filename)
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# Check if the file already exists
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if force_download or not os.path.exists(file_path):
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# Download the file if it does not exist
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print(f"Downloading {filename}...")
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response = requests.get(url)
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with open(file_path, "wb") as file:
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file.write(response.content)
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print(f"Downloaded {filename}.")
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else:
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print(f"{filename} already exists. Skipping download.")
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# Unzip the file
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with ZipFile(file_path, "r") as zip_ref:
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print(f"Unzipping {filename}...")
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zip_ref.extractall(save_directory)
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print(f"Unzipped {filename}.")
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def parse_pgn_dataset_to_dataframe(pgn_file_path):
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# Regular expressions for matching headers and moves
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header_pattern = re.compile(r"\[([A-Za-z0-9]+) \"(.+?)\"\]")
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games_list = []
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current_game = {}
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transcript = []
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with open(pgn_file_path, "r") as file:
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for line in file:
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line = line.encode("utf-8").decode("ascii", "ignore")
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header_match = header_pattern.match(line)
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if header_match:
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# If a new game starts and current_game is not empty, save the current game
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if header_match.group(1) == "Event" and current_game:
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current_game["transcript"] = " ".join(transcript).strip()
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games_list.append(current_game)
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current_game = {}
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transcript = []
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current_game[header_match.group(1)] = header_match.group(2)
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else:
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# Add moves to transcript, ignoring empty lines and game results
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clean_line = line.strip()
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if (
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clean_line
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and not clean_line.startswith("1-0")
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and not clean_line.startswith("1/2-1/2")
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and not clean_line.startswith("0-1")
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):
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transcript.append(clean_line)
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# Add the last game if it exists
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if current_game:
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current_game["transcript"] = " ".join(transcript).strip()
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games_list.append(current_game)
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# Create a DataFrame
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df = pd.DataFrame(games_list)
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return df
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def pgn_to_uci_transcript(pgn_transcript):
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game = pgn.read_game(io.StringIO(pgn_transcript))
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if game is None:
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return
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board = game.board()
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move_list = []
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for move in game.mainline_moves():
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move_list.append(board.uci(move))
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board.push(move)
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return " ".join(move_list)
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if __name__ == "__main__":
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save_directory = "."
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if not os.path.exists(save_directory):
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os.makedirs(save_directory)
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for url in ZIP_URLS:
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download_and_unzip(url, save_directory)
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pgn_files = [file for file in os.listdir(
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save_directory) if file.endswith(".pgn")]
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file_dfs = []
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for pgn_file in pgn_files:
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print(f"Parsing PGN from: {pgn_file}")
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df = parse_pgn_dataset_to_dataframe(pgn_file)
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df = df[df["EventType"] == "rapid"]
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file_dfs.append(df)
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df = pd.concat(file_dfs)
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# cast numeric columns
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for column in df.columns:
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if df[column].str.isnumeric().all():
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df[column] = df[column].astype(int)
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df["transcript"] = df["transcript"].progress_apply(pgn_to_uci_transcript)
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# filter unresolved games
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df = df[df["Result"] != "*"]
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df.to_feather("elite_dataset.feather")
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ds_info = DatasetInfo(
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description="The Lichess Elite Dataset includes all (rapid) games from Lichess by players rated 2500+ against players rated 2300+ played during the year 2023. Only games with an outcome of 1/2-1/2, 1-0, or 0-1 are included."
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)
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ds = Dataset.from_pandas(df, info=ds_info)
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ds.push_to_hub("austindavis/chess_world_lichess_elite")
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