Coverage for src/lightmlrestapi/args/encrypt_helper.py: 84%

1""" 

2@file 

3@brief Helper about encryption. 

4""" 

5import os 

6import hashlib 

7from io import StringIO 

8import pandas 

9 

10 

11def encrypt_password(pwd, algo="sha224"): 

12 """ 

13 Encrypts one password. 

14 

15 @param pwd string 

16 @param algo algorithm used to hash passwords 

17 @return encrypted password 

18 """ 

19 if algo == "sha224": 

20 return hashlib.sha224(pwd.encode('ascii')).hexdigest() 

21 else: 

22 raise NotImplementedError( 

23 "Algorithm '{0}' is not implemented.".format(algo)) 

24 

25 

26def encrypt_passwords(users, algo="sha224"): 

27 """ 

28 Encrypts users passwords. 

29 

30 @param users dataframe or... 

31 @param algo algorithm used to hash passwords 

32 @return password are replaced by the hashed passwords 

33 """ 

34 if isinstance(users, list): 

35 res = [] 

36 for login, pwd in users: 

37 pwd = encrypt_password(pwd, algo=algo) 

38 res.append((login, pwd)) 

39 return res 

40 elif hasattr(users, "values"): 

41 df = users.copy() 

42 col = df.columns[1] 

43 df[col] = df[col].apply(lambda pwd: encrypt_password(pwd, algo=algo)) 

44 return df 

45 else: 

46 raise TypeError("Unexpected type '{0}'".format(type(users))) 

47 

48 

49def load_passwords(source): 

50 """ 

51 Loads the encrypted passwords from a filename, a dataframe, 

52 a list of tuple. 

53 

54 @param source filename, dataframe 

55 @return dictionary ``{user: encrypted_pwd}`` 

56 """ 

57 if isinstance(source, str): 

58 if "\n" in source or ',' in source: 

59 st = StringIO(source) 

60 df = pandas.read_csv(st, encoding="utf-8", header=None) 

61 elif os.path.exists(source): 

62 df = pandas.read_csv(source, encoding="utf-8", header=None) 

63 else: 

64 raise ValueError("Unexpected string '{0}'".format(source)) 

65 elif isinstance(source, dict): 

66 return source 

67 elif hasattr(source, "values"): 

68 df = source 

69 elif isinstance(source, list): 

70 res = {} 

71 for a, b in source: 

72 res[a] = b 

73 return res 

74 else: 

75 raise TypeError("Unable to interpret type '{0}'".format(type(source))) 

76 

77 # dataframe 

78 res = {} 

79 for i in range(df.shape[0]): 

80 res[df.iloc[i, 0]] = df.iloc[i, 1] 

81 return res