| Total Complexity | 42 | 
| Total Lines | 258 | 
| Duplicated Lines | 0 % | 
| Changes | 0 | ||
Complex classes like annif.project often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
| 1 | """Project management functionality for Annif"""  | 
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| 2 | |||
| 3 | import collections  | 
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| 4 | import configparser  | 
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| 5 | import enum  | 
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| 6 | import os.path  | 
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| 7 | from sklearn.externals import joblib  | 
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| 8 | from sklearn.feature_extraction.text import TfidfVectorizer  | 
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| 9 | from flask import current_app  | 
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| 10 | import annif  | 
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| 11 | import annif.analyzer  | 
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| 12 | import annif.corpus  | 
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| 13 | import annif.hit  | 
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| 14 | import annif.backend  | 
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| 15 | import annif.util  | 
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| 16 | import annif.vocab  | 
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| 17 | from annif.datadir import DatadirMixin  | 
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| 18 | from annif.exception import AnnifException, ConfigurationException, \  | 
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| 19 | NotInitializedException  | 
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| 20 | |||
| 21 | logger = annif.logger  | 
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| 22 | |||
| 23 | |||
| 24 | class Access(enum.IntEnum):  | 
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| 25 | """Enumeration of access levels for projects"""  | 
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| 26 | private = 1  | 
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| 27 | hidden = 2  | 
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| 28 | public = 3  | 
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| 29 | |||
| 30 | |||
| 31 | class AnnifProject(DatadirMixin):  | 
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| 32 | """Class representing the configuration of a single Annif project."""  | 
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| 33 | |||
| 34 | # defaults for uninitialized instances  | 
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| 35 | _analyzer = None  | 
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| 36 | _backend = None  | 
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| 37 | _vocab = None  | 
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| 38 | _vectorizer = None  | 
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| 39 | initialized = False  | 
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| 40 | |||
| 41 | # default values for configuration settings  | 
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| 42 | DEFAULT_ACCESS = 'public'  | 
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| 43 | |||
| 44 | def __init__(self, project_id, config, datadir):  | 
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| 45 | DatadirMixin.__init__(self, datadir, 'projects', project_id)  | 
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| 46 | self.project_id = project_id  | 
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| 47 | self.name = config['name']  | 
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| 48 | self.language = config['language']  | 
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| 49 |         self.analyzer_spec = config.get('analyzer', None) | 
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| 50 |         self.vocab_id = config.get('vocab', None) | 
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| 51 | self.config = config  | 
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| 52 | self._base_datadir = datadir  | 
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| 53 | self._init_access()  | 
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| 54 | |||
| 55 | def _init_access(self):  | 
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| 56 |         access = self.config.get('access', self.DEFAULT_ACCESS) | 
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| 57 | try:  | 
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| 58 | self.access = getattr(Access, access)  | 
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| 59 | except AttributeError:  | 
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| 60 | raise ConfigurationException(  | 
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| 61 |                 "'{}' is not a valid access setting".format(access), | 
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| 62 | project_id=self.project_id)  | 
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| 63 | |||
| 64 | def _initialize_analyzer(self):  | 
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| 65 | analyzer = self.analyzer  | 
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| 66 |         logger.debug("Project '%s': initialized analyzer: %s", | 
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| 67 | self.project_id,  | 
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| 68 | str(analyzer))  | 
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| 69 | |||
| 70 | def _initialize_subjects(self):  | 
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| 71 | try:  | 
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| 72 | subjects = self.subjects  | 
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| 73 |             logger.debug("Project '%s': initialized subjects: %s", | 
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| 74 | self.project_id,  | 
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| 75 | str(subjects))  | 
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| 76 | except AnnifException as err:  | 
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| 77 | logger.warning(err.format_message())  | 
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| 78 | |||
| 79 | def _initialize_vectorizer(self):  | 
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| 80 | try:  | 
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| 81 | vectorizer = self.vectorizer  | 
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| 82 |             logger.debug("Project '%s': initialized vectorizer: %s", | 
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| 83 | self.project_id,  | 
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| 84 | str(vectorizer))  | 
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| 85 | except AnnifException as err:  | 
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| 86 | logger.warning(err.format_message())  | 
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| 87 | |||
| 88 | def _initialize_backend(self):  | 
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| 89 |         logger.debug("Project '%s': initializing backend", self.project_id) | 
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| 90 | if not self.backend:  | 
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| 91 |             logger.debug("Cannot initialize backend: does not exist") | 
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| 92 | return  | 
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| 93 | try:  | 
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| 94 | self.backend.initialize()  | 
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| 95 | except AnnifException as err:  | 
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| 96 | logger.warning(err.format_message())  | 
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| 97 | |||
| 98 | def initialize(self):  | 
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| 99 | """initialize this project and its backend so that they are ready to  | 
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| 100 | analyze"""  | 
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| 101 |         logger.debug("Initializing project '%s'", self.project_id) | 
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| 102 | |||
| 103 | self._initialize_analyzer()  | 
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| 104 | self._initialize_subjects()  | 
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| 105 | self._initialize_vectorizer()  | 
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| 106 | self._initialize_backend()  | 
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| 107 | |||
| 108 | self.initialized = True  | 
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| 109 | |||
| 110 | def _analyze_with_backend(self, text, backend_params):  | 
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| 111 | if backend_params is None:  | 
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| 112 |             backend_params = {} | 
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| 113 |         beparams = backend_params.get(self.backend.backend_id, {}) | 
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| 114 | hits = self.backend.analyze(text, project=self, params=beparams)  | 
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| 115 | logger.debug(  | 
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| 116 | 'Got %d hits from backend %s',  | 
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| 117 | len(hits), self.backend.backend_id)  | 
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| 118 | return hits  | 
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| 119 | |||
| 120 | @property  | 
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| 121 | def analyzer(self):  | 
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| 122 | if self._analyzer is None and self.analyzer_spec:  | 
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| 123 | self._analyzer = annif.analyzer.get_analyzer(self.analyzer_spec)  | 
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| 124 | return self._analyzer  | 
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| 125 | |||
| 126 | @property  | 
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| 127 | def backend(self):  | 
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| 128 | if self._backend is None:  | 
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| 129 | backend_id = self.config['backend']  | 
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| 130 | try:  | 
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| 131 | backend_class = annif.backend.get_backend(backend_id)  | 
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| 132 | self._backend = backend_class(  | 
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| 133 | backend_id, params=self.config, datadir=self.datadir)  | 
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| 134 | except ValueError:  | 
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| 135 | logger.warning(  | 
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| 136 | "Could not create backend %s, "  | 
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| 137 | "make sure you've installed optional dependencies",  | 
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| 138 | backend_id)  | 
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| 139 | return self._backend  | 
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| 140 | |||
| 141 | @property  | 
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| 142 | def vocab(self):  | 
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| 143 | if self._vocab is None:  | 
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| 144 | if self.vocab_id is None:  | 
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| 145 |                 raise ConfigurationException("vocab setting is missing", | 
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| 146 | project_id=self.project_id)  | 
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| 147 | self._vocab = annif.vocab.AnnifVocabulary(self.vocab_id,  | 
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| 148 | self._base_datadir)  | 
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| 149 | return self._vocab  | 
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| 150 | |||
| 151 | @property  | 
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| 152 | def subjects(self):  | 
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| 153 | return self.vocab.subjects  | 
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| 154 | |||
| 155 | @property  | 
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| 156 | def vectorizer(self):  | 
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| 157 | if self._vectorizer is None:  | 
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| 158 | path = os.path.join(self.datadir, 'vectorizer')  | 
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| 159 | if os.path.exists(path):  | 
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| 160 |                 logger.debug('loading vectorizer from %s', path) | 
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| 161 | self._vectorizer = joblib.load(path)  | 
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| 162 | else:  | 
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| 163 | raise NotInitializedException(  | 
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| 164 |                     "vectorizer file '{}' not found".format(path), | 
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| 165 | project_id=self.project_id)  | 
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| 166 | return self._vectorizer  | 
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| 167 | |||
| 168 | def analyze(self, text, backend_params=None):  | 
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| 169 | """Analyze the given text by passing it to the backend. Returns a  | 
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| 170 | list of AnalysisHit objects ordered by decreasing score."""  | 
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| 171 | |||
| 172 |         logger.debug('Analyzing text "%s..." (len=%d)', | 
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| 173 | text[:20], len(text))  | 
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| 174 | hits = self._analyze_with_backend(text, backend_params)  | 
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| 175 |         logger.debug('%d hits from backend', len(hits)) | 
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| 176 | return hits  | 
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| 177 | |||
| 178 | def _create_vectorizer(self, subjectcorpus):  | 
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| 179 | if not self.backend.needs_subject_vectorizer:  | 
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| 180 |             logger.debug('not creating vectorizer: not needed by backend') | 
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| 181 | return  | 
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| 182 |         logger.info('creating vectorizer') | 
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| 183 | self._vectorizer = TfidfVectorizer(  | 
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| 184 | tokenizer=self.analyzer.tokenize_words)  | 
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| 185 | self._vectorizer.fit((subj.text for subj in subjectcorpus.subjects))  | 
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| 
                                                                                                    
                         1 ignored issue 
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| 186 | annif.util.atomic_save(  | 
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| 187 | self._vectorizer,  | 
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| 188 | self.datadir,  | 
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| 189 | 'vectorizer',  | 
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| 190 | method=joblib.dump)  | 
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| 191 | |||
| 192 | def train(self, corpus):  | 
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| 193 | """train the project using documents from a metadata source"""  | 
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| 194 | |||
| 195 | corpus.set_subject_index(self.subjects)  | 
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| 196 | self._create_vectorizer(corpus)  | 
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| 197 | self.backend.train(corpus, project=self)  | 
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| 198 | |||
| 199 | def dump(self):  | 
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| 200 | """return this project as a dict"""  | 
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| 201 |         return {'project_id': self.project_id, | 
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| 202 | 'name': self.name,  | 
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| 203 | 'language': self.language,  | 
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| 204 |                 'backend': {'backend_id': self.config['backend']} | 
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| 205 | }  | 
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| 206 | |||
| 207 | |||
| 208 | def _create_projects(projects_file, datadir, init_projects):  | 
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| 209 | if not os.path.exists(projects_file):  | 
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| 210 |         logger.warning("Project configuration file '%s' is missing. " + | 
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| 211 | 'Please provide one.', projects_file)  | 
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| 212 |         logger.warning('You can set the path to the project configuration ' + | 
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| 213 | 'file using the ANNIF_PROJECTS environment variable.')  | 
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| 214 |         return {} | 
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| 215 | |||
| 216 | config = configparser.ConfigParser()  | 
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| 217 | config.optionxform = lambda option: option  | 
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| 218 | with open(projects_file) as projf:  | 
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| 219 | config.read_file(projf)  | 
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| 220 | |||
| 221 | # create AnnifProject objects from the configuration file  | 
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| 222 | projects = collections.OrderedDict()  | 
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| 223 | for project_id in config.sections():  | 
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| 224 | projects[project_id] = AnnifProject(project_id,  | 
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| 225 | config[project_id],  | 
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| 226 | datadir)  | 
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| 227 | if init_projects:  | 
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| 228 | projects[project_id].initialize()  | 
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| 229 | return projects  | 
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| 230 | |||
| 231 | |||
| 232 | def initialize_projects(app):  | 
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| 233 | projects_file = app.config['PROJECTS_FILE']  | 
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| 234 | datadir = app.config['DATADIR']  | 
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| 235 | init_projects = app.config['INITIALIZE_PROJECTS']  | 
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| 236 | app.annif_projects = _create_projects(  | 
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| 237 | projects_file, datadir, init_projects)  | 
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| 238 | |||
| 239 | |||
| 240 | def get_projects(min_access=Access.private):  | 
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| 241 | """Return the available projects as a dict of project_id ->  | 
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| 242 | AnnifProject. The min_access parameter may be used to set the minimum  | 
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| 243 | access level required for the returned projects."""  | 
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| 244 | |||
| 245 | projects = [(project_id, project)  | 
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| 246 | for project_id, project in current_app.annif_projects.items()  | 
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| 247 | if project.access >= min_access]  | 
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| 248 | return collections.OrderedDict(projects)  | 
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| 249 | |||
| 250 | |||
| 251 | def get_project(project_id, min_access=Access.private):  | 
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| 252 | """return the definition of a single Project by project_id"""  | 
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| 253 | projects = get_projects(min_access)  | 
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| 254 | try:  | 
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| 255 | return projects[project_id]  | 
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| 256 | except KeyError:  | 
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| 257 |         raise ValueError("No such project {}".format(project_id)) | 
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| 258 |