wehub-resource-sync
57 lines
1.9 KiB
Python
57 lines
1.9 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# This software may be used and distributed according to the terms of the Llama 3 Community License Agreement.
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import csv
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# Define the input and output file names
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input_file = 'nba.txt'
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output_file = 'nba_roster.csv'
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# Initialize lists to store data
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roster_data = []
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current_team = None
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# Open the input file
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with open(input_file, 'r') as file:
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for line in file:
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# Remove leading and trailing whitespaces from the line
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line = line.strip()
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# Check if the line starts with 'https', skip it
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if line.startswith('https'):
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continue
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# Check if the line contains the team name
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if 'Roster' in line:
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current_team = line.split(' Roster ')[0]
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elif line and "NAME" not in line: # Skip empty lines and header lines
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# Split the line using tabs as the delimiter
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player_info = line.split('\t')
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# Remove any numbers from the player's name and set Jersey accordingly
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name = ''.join([c for c in player_info[0] if not c.isdigit()])
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jersey = ''.join([c for c in player_info[0] if c.isdigit()])
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# If no number found, set Jersey to "NA"
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if not jersey:
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jersey = "NA"
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# Append the team name, name, and jersey to the player's data
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player_info = [current_team, name, jersey] + player_info[1:]
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# Append the player's data to the roster_data list
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roster_data.append(player_info)
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# Write the data to a CSV file
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with open(output_file, 'w', newline='') as csvfile:
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writer = csv.writer(csvfile)
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# Write the header row
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writer.writerow(['Team', 'NAME', 'Jersey', 'POS', 'AGE', 'HT', 'WT', 'COLLEGE', 'SALARY'])
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# Write the player data
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writer.writerows(roster_data)
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print(f'Conversion completed. Data saved to {output_file}')
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