Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.11/site-packages/sqlalchemy_utils/types/ts_vector.py: 53%

1import sqlalchemy as sa 

2from sqlalchemy.dialects.postgresql import TSVECTOR 

3 

4 

5class TSVectorType(sa.types.TypeDecorator): 

6 """ 

7 .. note:: 

8 

9 This type is PostgreSQL specific and is not supported by other 

10 dialects. 

11 

12 Provides additional functionality for SQLAlchemy PostgreSQL dialect's 

13 TSVECTOR_ type. This additional functionality includes: 

14 

15 * Vector concatenation 

16 * regconfig constructor parameter which is applied to match function if no 

17 postgresql_regconfig parameter is given 

18 * Provides extensible base for extensions such as SQLAlchemy-Searchable_ 

19 

20 .. _TSVECTOR: 

21 https://docs.sqlalchemy.org/en/latest/dialects/postgresql.html#full-text-search 

22 

23 .. _SQLAlchemy-Searchable: 

24 https://www.github.com/kvesteri/sqlalchemy-searchable 

25 

26 :: 

27 

28 from sqlalchemy_utils import TSVectorType 

29 

30 

31 class Article(Base): 

32 __tablename__ = 'user' 

33 id = sa.Column(sa.Integer, primary_key=True) 

34 name = sa.Column(sa.String(100)) 

35 search_vector = sa.Column(TSVectorType) 

36 

37 

38 # Find all articles whose name matches 'finland' 

39 session.query(Article).filter(Article.search_vector.match('finland')) 

40 

41 

42 TSVectorType also supports vector concatenation. 

43 

44 :: 

45 

46 

47 class Article(Base): 

48 __tablename__ = 'user' 

49 id = sa.Column(sa.Integer, primary_key=True) 

50 name = sa.Column(sa.String(100)) 

51 name_vector = sa.Column(TSVectorType) 

52 content = sa.Column(sa.String) 

53 content_vector = sa.Column(TSVectorType) 

54 

55 # Find all articles whose name or content matches 'finland' 

56 session.query(Article).filter( 

57 (Article.name_vector | Article.content_vector).match('finland') 

58 ) 

59 

60 You can configure TSVectorType to use a specific regconfig. 

61 :: 

62 

63 class Article(Base): 

64 __tablename__ = 'user' 

65 id = sa.Column(sa.Integer, primary_key=True) 

66 name = sa.Column(sa.String(100)) 

67 search_vector = sa.Column( 

68 TSVectorType(regconfig='pg_catalog.simple') 

69 ) 

70 

71 

72 Now expression such as:: 

73 

74 

75 Article.search_vector.match('finland') 

76 

77 

78 Would be equivalent to SQL:: 

79 

80 

81 search_vector @@ to_tsquery('pg_catalog.simple', 'finland') 

82 

83 """ 

84 

85 impl = TSVECTOR 

86 cache_ok = True 

87 

88 class comparator_factory(TSVECTOR.Comparator): 

89 def match(self, other, **kwargs): 

90 if 'postgresql_regconfig' not in kwargs: 

91 if 'regconfig' in self.type.options: 

92 kwargs['postgresql_regconfig'] = self.type.options['regconfig'] 

93 return TSVECTOR.Comparator.match(self, other, **kwargs) 

94 

95 def __or__(self, other): 

96 return self.op('||')(other) 

97 

98 def __init__(self, *args, **kwargs): 

99 """ 

100 Initializes new TSVectorType 

101 

102 :param *args: list of column names 

103 :param **kwargs: various other options for this TSVectorType 

104 """ 

105 self.columns = args 

106 self.options = kwargs 

107 super().__init__()