Coverage for rendercv/data/generator.py: 100%

1""" 

2The `rendercv.data.generator` module contains all the functions for generating the JSON 

3Schema of the input data format and a sample YAML input file. 

4""" 

5 

6import io (empty)

7import json (empty)

8import pathlib (empty)

9from typing import Optional (empty)

10 

11import pydantic (empty)

12import ruamel.yaml (empty)

13 

14from . import models, reader (empty)

15 

16 

17def dictionary_to_yaml(dictionary: dict) -> str: (empty)

18 """Converts a dictionary to a YAML string. 

19 

20 Args: 

21 dictionary: The dictionary to be converted to YAML. 

22 

23 Returns: 

24 The YAML string. 

25 """ 

26 yaml_object = ruamel.yaml.YAML() (empty)

27 yaml_object.encoding = "utf-8" (empty)

28 yaml_object.width = 60 (empty)

29 yaml_object.indent(mapping=2, sequence=4, offset=2) (empty)

30 with io.StringIO() as string_stream: (empty)

31 yaml_object.dump(dictionary, string_stream) (empty)

32 return string_stream.getvalue() (empty)

33 

34 

35def create_a_sample_data_model( (empty)

36 name: str = "John Doe", theme: str = "classic" 

37) -> models.RenderCVDataModel: 

38 """Return a sample data model for new users to start with. 

39 

40 Args: 

41 name: The name of the person. Defaults to "John Doe". 

42 

43 Returns: 

44 A sample data model. 

45 """ 

46 # Check if the theme is valid: 

47 if theme not in models.available_theme_options: (empty)

48 available_themes_string = ", ".join(models.available_theme_options.keys()) (empty)

49 message = ( (empty)

50 f"The theme should be one of the following: {available_themes_string}!" 

51 f' The provided theme is "{theme}".' 

52 ) 

53 raise ValueError(message) (empty)

54 

55 # read the sample_content.yaml file 

56 sample_content = pathlib.Path(__file__).parent / "sample_content.yaml" (empty)

57 sample_content_dictionary = reader.read_a_yaml_file(sample_content) (empty)

58 cv = models.CurriculumVitae(**sample_content_dictionary) (empty)

59 

60 # Update the name: 

61 name = name.encode().decode("unicode-escape") (empty)

62 cv.name = name (empty)

63 

64 design = models.available_theme_options[theme](theme=theme) (empty)

65 

66 return models.RenderCVDataModel(cv=cv, design=design) (empty)

67 

68 

69def create_a_sample_yaml_input_file( (empty)

70 input_file_path: Optional[pathlib.Path] = None, 

71 name: str = "John Doe", 

72 theme: str = "classic", 

73) -> str: 

74 """Create a sample YAML input file and return it as a string. If the input file path 

75 is provided, then also save the contents to the file. 

76 

77 Args: 

78 input_file_path: The path to save the input file. Defaults to None. 

79 name: The name of the person. Defaults to "John Doe". 

80 theme: The theme of the CV. Defaults to "classic". 

81 

82 Returns: 

83 The sample YAML input file as a string. 

84 """ 

85 data_model = create_a_sample_data_model(name=name, theme=theme) (empty)

86 

87 # Instead of getting the dictionary with data_model.model_dump() directly, we 

88 # convert it to JSON and then to a dictionary. Because the YAML library we are 

89 # using sometimes has problems with the dictionary returned by model_dump(). 

90 

91 # We exclude "cv.sections" because the data model automatically generates them. 

92 # The user's "cv.sections" input is actually "cv.sections_input" in the data 

93 # model. It is shown as "cv.sections" in the YAML file because an alias is being 

94 # used. If"cv.sections" were not excluded, the automatically generated 

95 # "cv.sections" would overwrite the "cv.sections_input". "cv.sections" are 

96 # automatically generated from "cv.sections_input" to make the templating 

97 # process easier. "cv.sections_input" exists for the convenience of the user. 

98 data_model_as_json = data_model.model_dump_json( (empty)

99 exclude_none=True, by_alias=True, exclude={"cv": {"sections"}} 

100 ) 

101 data_model_as_dictionary = json.loads(data_model_as_json) (empty)

102 

103 yaml_string = dictionary_to_yaml(data_model_as_dictionary) (empty)

104 

105 if input_file_path is not None: (empty)

106 input_file_path.write_text(yaml_string, encoding="utf-8") (empty)

107 

108 return yaml_string (empty)

109 

110 

111def generate_json_schema() -> dict: (empty)

112 """Generate the JSON schema of RenderCV. 

113 

114 JSON schema is generated for the users to make it easier for them to write the input 

115 file. The JSON Schema of RenderCV is saved in the root directory of the repository 

116 and distributed to the users with the 

117 [JSON Schema Store](https://www.schemastore.org/). 

118 

119 Returns: 

120 The JSON schema of RenderCV. 

121 """ 

122 

123 class RenderCVSchemaGenerator(pydantic.json_schema.GenerateJsonSchema): (empty)

124 def generate(self, schema, mode="validation"): # type: ignore (empty)

125 json_schema = super().generate(schema, mode=mode) (empty)

126 

127 # Basic information about the schema: 

128 json_schema["title"] = "RenderCV" (empty)

129 json_schema["description"] = "RenderCV data model." (empty)

130 json_schema["$id"] = ( (empty)

131 "https://raw.githubusercontent.com/rendercv/rendercv/main/schema.json" 

132 ) 

133 json_schema["$schema"] = "http://json-schema.org/draft-07/schema#" (empty)

134 

135 # Loop through $defs and remove docstring descriptions and fix optional 

136 # fields 

137 for _, value in json_schema["$defs"].items(): (empty)

138 # If a type is optional, then Pydantic sets the type to a list of two 

139 # types, one of which is null. The null type can be removed since we 

140 # already have the required field. Moreover, we would like to warn 

141 # users if they provide null values. They can remove the fields if they 

142 # don't want to provide them. 

143 null_type_dict = { (empty)

144 "type": "null", 

145 } 

146 for _, field in value["properties"].items(): (empty)

147 if "anyOf" in field: (empty)

148 if null_type_dict in field["anyOf"]: (empty)

149 field["anyOf"].remove(null_type_dict) (empty)

150 

151 field["oneOf"] = field["anyOf"] (empty)

152 del field["anyOf"] (empty)

153 

154 # # Currently, YAML extension in VS Code doesn't work properly with the 

155 # # `ListOfEntries` objects. For the best user experience, we will update 

156 # # the JSON Schema. If YAML extension in VS Code starts to work properly, 

157 # # then we should remove the following code for the correct JSON Schema. 

158 # ListOfEntriesForJsonSchema = list[models.Entry] 

159 # list_of_entries_json_schema = pydantic.TypeAdapter( 

160 # ListOfEntriesForJsonSchema 

161 # ).json_schema() 

162 # del list_of_entries_json_schema["$defs"] 

163 

164 # json_schema["$defs"]["CurriculumVitae"]["properties"]["sections"]["oneOf"][ 

165 # 0 

166 # ]["additionalProperties"] = list_of_entries_json_schema 

167 

168 # # Loop through json_schema["$defs"] and update keys: 

169 # # Make all ANYTHING__KEY to KEY 

170 # for key in list(json_schema["$defs"]): 

171 # new_key = key.split("__")[-1] 

172 # json_schema["$defs"][new_key] = json_schema["$defs"][key] 

173 

174 return json_schema (empty)

175 

176 return models.RenderCVDataModel.model_json_schema( (empty)

177 schema_generator=RenderCVSchemaGenerator 

178 ) 

179 

180 

181def generate_json_schema_file(json_schema_path: pathlib.Path): (empty)

182 """Generate the JSON schema of RenderCV and save it to a file. 

183 

184 Args: 

185 json_schema_path: The path to save the JSON schema. 

186 """ 

187 schema = generate_json_schema() (empty)

188 schema_json = json.dumps(schema, indent=2, ensure_ascii=False) (empty)

189 json_schema_path.write_text(schema_json, encoding="utf-8") (empty)