vangef/BBGradebookOrganiser
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include file name (without full path) in output csv

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vangef
2023-02-28 23:09:33 +00:00
parent 980281c5fd
commit 599d8eec04
1 changed files with 3 additions and 3 deletions
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6
utils/inspector.py
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@@ -13,7 +13,7 @@ def get_hashes_in_dir(dir_path: str) -> list:
filepath = os.path.join(subdir, file) filepath = os.path.join(subdir, file)
with open(filepath, 'rb') as f: with open(filepath, 'rb') as f:
filehash = hashlib.sha256(f.read()).hexdigest() filehash = hashlib.sha256(f.read()).hexdigest()
hash_list.append({ 'file': filepath, 'sha256 hash': filehash}) hash_list.append({ 'filepath': filepath, 'filename': file, 'sha256 hash': filehash})
return hash_list return hash_list
@@ -24,7 +24,7 @@ def hash_submissions(submissions_dir_path: str):
csv_file_name = f'{submissions_dir_name}_file_hashes_{datetime.now().strftime("%Y%m%d-%H%M%S")}.csv' csv_file_name = f'{submissions_dir_name}_file_hashes_{datetime.now().strftime("%Y%m%d-%H%M%S")}.csv'
csv_file_path = os.path.join(CSV_DIR, csv_file_name) csv_file_path = os.path.join(CSV_DIR, csv_file_name)
with open(csv_file_path, 'w', newline='') as csvfile: # Open the output CSV file for writing with open(csv_file_path, 'w', newline='') as csvfile: # Open the output CSV file for writing
fieldnames = ['Student ID', 'file', 'sha256 hash'] fieldnames = ['Student ID', 'filepath', 'filename', 'sha256 hash']
writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader() writer.writeheader()
@@ -37,7 +37,7 @@ def hash_submissions(submissions_dir_path: str):
return csv_file_path return csv_file_path
def get_suspicious_hashes(df: pd.DataFrame) -> list: def get_suspicious_hashes(df: pd.DataFrame) -> list:
drop_columns = ['file'] drop_columns = ['filepath', 'filename']
df = df.drop(columns=drop_columns).sort_values('sha256 hash') # clear not needed colums & sort by hash df = df.drop(columns=drop_columns).sort_values('sha256 hash') # clear not needed colums & sort by hash
duplicate_hash = df.loc[df.duplicated(subset=['sha256 hash'], keep=False), :] # all files with duplicate hash - incl. files from the same student id duplicate_hash = df.loc[df.duplicated(subset=['sha256 hash'], keep=False), :] # all files with duplicate hash - incl. files from the same student id