24 lines
1.2 KiB
Python
24 lines
1.2 KiB
Python
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import os, sys
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import pandas as pd
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from datetime import datetime
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from utils.inspector import hash_submissions, suspicious_by_hash
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def main():
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submissions_dir_name = ' '.join(sys.argv[1:]) if len(sys.argv) > 1 else exit(f'\nNo submissions dir name given. Provide the name as an argument.\n\nUsage: python {sys.argv[0]} [submissions dir name]\nExample: python {sys.argv[0]} AssignmentX\n')
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submissions_dir_path = os.path.join('BB_submissions', submissions_dir_name)
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if not os.path.isdir(submissions_dir_path):
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exit(f'Directory {submissions_dir_path} does not exist.\nMake sure "{submissions_dir_name}" exists in "BB_submissions".')
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else:
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hashes_csv_file_path = hash_submissions(submissions_dir_path)
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csv = pd.read_csv(hashes_csv_file_path)
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df = pd.DataFrame(csv) # df with all files and their hashes
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df_suspicious = suspicious_by_hash(df) # df with all files with duplicate hash, excludes files from the same student id
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csv_name = f'{submissions_dir_name}_suspicious_{datetime.now().strftime("%Y%m%d-%H%M%S")}.csv'
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csv_out = os.path.join('csv', csv_name)
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df_suspicious.to_csv(csv_out, index=False)
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if __name__ == '__main__':
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main()
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