include file name (without full path) in output csv
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@@ -13,7 +13,7 @@ def get_hashes_in_dir(dir_path: str) -> list:
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filepath = os.path.join(subdir, file)
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with open(filepath, 'rb') as f:
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filehash = hashlib.sha256(f.read()).hexdigest()
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hash_list.append({ 'file': filepath, 'sha256 hash': filehash})
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hash_list.append({ 'filepath': filepath, 'filename': file, 'sha256 hash': filehash})
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return hash_list
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@@ -24,7 +24,7 @@ def hash_submissions(submissions_dir_path: str):
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csv_file_name = f'{submissions_dir_name}_file_hashes_{datetime.now().strftime("%Y%m%d-%H%M%S")}.csv'
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csv_file_path = os.path.join(CSV_DIR, csv_file_name)
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with open(csv_file_path, 'w', newline='') as csvfile: # Open the output CSV file for writing
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fieldnames = ['Student ID', 'file', 'sha256 hash']
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fieldnames = ['Student ID', 'filepath', 'filename', 'sha256 hash']
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writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
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writer.writeheader()
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@@ -37,7 +37,7 @@ def hash_submissions(submissions_dir_path: str):
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return csv_file_path
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def get_suspicious_hashes(df: pd.DataFrame) -> list:
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drop_columns = ['file']
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drop_columns = ['filepath', 'filename']
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df = df.drop(columns=drop_columns).sort_values('sha256 hash') # clear not needed colums & sort by hash
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duplicate_hash = df.loc[df.duplicated(subset=['sha256 hash'], keep=False), :] # all files with duplicate hash - incl. files from the same student id
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