| Total Complexity | 64 |
| Total Lines | 656 |
| Duplicated Lines | 70.73 % |
| Changes | 0 | ||
Duplicate code is one of the most pungent code smells. A rule that is often used is to re-structure code once it is duplicated in three or more places.
Common duplication problems, and corresponding solutions are:
Complex classes like annif.cli 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 | """Definitions for command-line (Click) commands for invoking Annif |
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| 2 | operations and printing the results to console.""" |
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| 3 | |||
| 4 | |||
| 5 | import collections |
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| 6 | import os.path |
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| 7 | import re |
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| 8 | import sys |
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| 9 | import json |
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| 10 | import click |
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| 11 | import click_log |
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| 12 | from flask import current_app |
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| 13 | from flask.cli import FlaskGroup, ScriptInfo |
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| 14 | import annif |
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| 15 | import annif.corpus |
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| 16 | import annif.parallel |
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| 17 | import annif.project |
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| 18 | import annif.registry |
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| 19 | from annif.project import Access |
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| 20 | from annif.suggestion import SuggestionFilter, ListSuggestionResult |
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| 21 | from annif.exception import ConfigurationException, NotSupportedException |
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| 22 | from annif.exception import NotInitializedException |
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| 23 | from annif.util import metric_code |
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| 24 | |||
| 25 | logger = annif.logger |
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| 26 | click_log.basic_config(logger) |
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| 27 | |||
| 28 | cli = FlaskGroup(create_app=annif.create_app, add_version_option=False) |
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| 29 | cli = click.version_option(message='%(version)s')(cli) |
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| 30 | |||
| 31 | |||
| 32 | def get_project(project_id): |
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| 33 | """ |
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| 34 | Helper function to get a project by ID and bail out if it doesn't exist""" |
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| 35 | try: |
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| 36 | return annif.registry.get_project(project_id, |
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| 37 | min_access=Access.private) |
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| 38 | except ValueError: |
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| 39 | click.echo( |
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| 40 | "No projects found with id \'{0}\'.".format(project_id), |
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| 41 | err=True) |
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| 42 | sys.exit(1) |
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| 43 | |||
| 44 | |||
| 45 | def get_vocab(vocab_id): |
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| 46 | """ |
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| 47 | Helper function to get a vocabulary by ID and bail out if it doesn't |
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| 48 | exist""" |
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| 49 | try: |
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| 50 | return annif.registry.get_vocab(vocab_id, |
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| 51 | min_access=Access.private) |
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| 52 | except ValueError: |
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| 53 | click.echo( |
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| 54 | f"No vocabularies found with the id '{vocab_id}'.", |
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| 55 | err=True) |
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| 56 | sys.exit(1) |
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| 57 | |||
| 58 | |||
| 59 | View Code Duplication | def open_documents(paths, subject_index, vocab_lang, docs_limit): |
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|
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| 60 | """Helper function to open a document corpus from a list of pathnames, |
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| 61 | each of which is either a TSV file or a directory of TXT files. For |
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| 62 | directories with subjects in TSV files, the given vocabulary language |
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| 63 | will be used to convert subject labels into URIs. The corpus will be |
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| 64 | returned as an instance of DocumentCorpus or LimitingDocumentCorpus.""" |
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| 65 | |||
| 66 | def open_doc_path(path, subject_index): |
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| 67 | """open a single path and return it as a DocumentCorpus""" |
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| 68 | if os.path.isdir(path): |
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| 69 | return annif.corpus.DocumentDirectory(path, subject_index, |
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| 70 | vocab_lang, |
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| 71 | require_subjects=True) |
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| 72 | return annif.corpus.DocumentFile(path, subject_index) |
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| 73 | |||
| 74 | if len(paths) == 0: |
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| 75 | logger.warning('Reading empty file') |
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| 76 | docs = open_doc_path(os.path.devnull, subject_index) |
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| 77 | elif len(paths) == 1: |
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| 78 | docs = open_doc_path(paths[0], subject_index) |
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| 79 | else: |
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| 80 | corpora = [open_doc_path(path, subject_index) for path in paths] |
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| 81 | docs = annif.corpus.CombinedCorpus(corpora) |
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| 82 | if docs_limit is not None: |
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| 83 | docs = annif.corpus.LimitingDocumentCorpus(docs, docs_limit) |
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| 84 | return docs |
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| 85 | |||
| 86 | |||
| 87 | View Code Duplication | def parse_backend_params(backend_param, project): |
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| 88 | """Parse a list of backend parameters given with the --backend-param |
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| 89 | option into a nested dict structure""" |
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| 90 | backend_params = collections.defaultdict(dict) |
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| 91 | for beparam in backend_param: |
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| 92 | backend, param = beparam.split('.', 1) |
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| 93 | key, val = param.split('=', 1) |
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| 94 | validate_backend_params(backend, beparam, project) |
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| 95 | backend_params[backend][key] = val |
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| 96 | return backend_params |
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| 97 | |||
| 98 | |||
| 99 | def validate_backend_params(backend, beparam, project): |
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| 100 | if backend != project.config['backend']: |
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| 101 | raise ConfigurationException( |
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| 102 | 'The backend {} in CLI option "-b {}" not matching the project' |
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| 103 | ' backend {}.' |
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| 104 | .format(backend, beparam, project.config['backend'])) |
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| 105 | |||
| 106 | |||
| 107 | BATCH_MAX_LIMIT = 15 |
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| 108 | |||
| 109 | |||
| 110 | def generate_filter_batches(subjects): |
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| 111 | import annif.eval |
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| 112 | filter_batches = collections.OrderedDict() |
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| 113 | for limit in range(1, BATCH_MAX_LIMIT + 1): |
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| 114 | for threshold in [i * 0.05 for i in range(20)]: |
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| 115 | hit_filter = SuggestionFilter(subjects, limit, threshold) |
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| 116 | batch = annif.eval.EvaluationBatch(subjects) |
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| 117 | filter_batches[(limit, threshold)] = (hit_filter, batch) |
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| 118 | return filter_batches |
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| 119 | |||
| 120 | |||
| 121 | def set_project_config_file_path(ctx, param, value): |
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| 122 | """Override the default path or the path given in env by CLI option""" |
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| 123 | with ctx.ensure_object(ScriptInfo).load_app().app_context(): |
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| 124 | if value: |
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| 125 | current_app.config['PROJECTS_CONFIG_PATH'] = value |
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| 126 | |||
| 127 | |||
| 128 | def common_options(f): |
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| 129 | """Decorator to add common options for all CLI commands""" |
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| 130 | f = click.option( |
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| 131 | '-p', '--projects', |
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| 132 | help='Set path to project configuration file or directory', |
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| 133 | type=click.Path(dir_okay=True, exists=True), |
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| 134 | callback=set_project_config_file_path, expose_value=False, |
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| 135 | is_eager=True)(f) |
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| 136 | return click_log.simple_verbosity_option(logger)(f) |
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| 137 | |||
| 138 | |||
| 139 | def backend_param_option(f): |
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| 140 | """Decorator to add an option for CLI commands to override BE parameters""" |
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| 141 | return click.option( |
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| 142 | '--backend-param', '-b', multiple=True, |
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| 143 | help='Override backend parameter of the config file. ' + |
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| 144 | 'Syntax: `-b <backend>.<parameter>=<value>`.')(f) |
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| 145 | |||
| 146 | |||
| 147 | View Code Duplication | @cli.command('list-projects') |
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| 148 | @common_options |
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| 149 | @click_log.simple_verbosity_option(logger, default='ERROR') |
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| 150 | def run_list_projects(): |
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| 151 | """ |
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| 152 | List available projects. |
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| 153 | \f |
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| 154 | Show a list of currently defined projects. Projects are defined in a |
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| 155 | configuration file, normally called ``projects.cfg``. See `Project |
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| 156 | configuration |
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| 157 | <https://github.com/NatLibFi/Annif/wiki/Project-configuration>`_ |
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| 158 | for details. |
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| 159 | """ |
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| 160 | |||
| 161 | template = "{0: <25}{1: <45}{2: <10}{3: <7}" |
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| 162 | header = template.format( |
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| 163 | "Project ID", "Project Name", "Language", "Trained") |
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| 164 | click.echo(header) |
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| 165 | click.echo("-" * len(header)) |
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| 166 | for proj in annif.registry.get_projects( |
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| 167 | min_access=Access.private).values(): |
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| 168 | click.echo(template.format( |
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| 169 | proj.project_id, proj.name, proj.language, str(proj.is_trained))) |
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| 170 | |||
| 171 | |||
| 172 | View Code Duplication | @cli.command('show-project') |
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| 173 | @click.argument('project_id') |
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| 174 | @common_options |
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| 175 | def run_show_project(project_id): |
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| 176 | """ |
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| 177 | Show information about a project. |
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| 178 | """ |
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| 179 | |||
| 180 | proj = get_project(project_id) |
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| 181 | click.echo(f'Project ID: {proj.project_id}') |
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| 182 | click.echo(f'Project Name: {proj.name}') |
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| 183 | click.echo(f'Language: {proj.language}') |
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| 184 | click.echo(f'Vocabulary: {proj.vocab.vocab_id}') |
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| 185 | click.echo(f'Vocab language: {proj.vocab_lang}') |
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| 186 | click.echo(f'Access: {proj.access.name}') |
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| 187 | click.echo(f'Trained: {proj.is_trained}') |
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| 188 | click.echo(f'Modification time: {proj.modification_time}') |
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| 189 | |||
| 190 | |||
| 191 | @cli.command('clear') |
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| 192 | @click.argument('project_id') |
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| 193 | @common_options |
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| 194 | def run_clear_project(project_id): |
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| 195 | """ |
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| 196 | Initialize the project to its original, untrained state. |
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| 197 | """ |
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| 198 | proj = get_project(project_id) |
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| 199 | proj.remove_model_data() |
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| 200 | |||
| 201 | |||
| 202 | View Code Duplication | @cli.command('list-vocabs') |
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| 203 | @common_options |
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| 204 | @click_log.simple_verbosity_option(logger, default='ERROR') |
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| 205 | def run_list_vocabs(): |
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| 206 | """ |
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| 207 | List available vocabularies. |
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| 208 | """ |
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| 209 | |||
| 210 | template = "{0: <20}{1: <20}{2: >10} {3: <6}" |
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| 211 | header = template.format( |
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| 212 | "Vocabulary ID", "Languages", "Size", "Loaded") |
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| 213 | click.echo(header) |
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| 214 | click.echo("-" * len(header)) |
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| 215 | for vocab in annif.registry.get_vocabs( |
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| 216 | min_access=Access.private).values(): |
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| 217 | try: |
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| 218 | languages = ','.join(sorted(vocab.languages)) |
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| 219 | size = len(vocab) |
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| 220 | loaded = True |
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| 221 | except NotInitializedException: |
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| 222 | languages = '-' |
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| 223 | size = '-' |
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| 224 | loaded = False |
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| 225 | click.echo(template.format( |
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| 226 | vocab.vocab_id, languages, size, str(loaded))) |
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| 227 | |||
| 228 | |||
| 229 | View Code Duplication | @cli.command('loadvoc', deprecated=True) |
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| 230 | @click.argument('project_id') |
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| 231 | @click.argument('subjectfile', type=click.Path(exists=True, dir_okay=False)) |
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| 232 | @click.option('--force', '-f', default=False, is_flag=True, |
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| 233 | help='Replace existing vocabulary completely ' + |
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| 234 | 'instead of updating it') |
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| 235 | @common_options |
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| 236 | def run_loadvoc(project_id, force, subjectfile): |
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| 237 | """ |
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| 238 | Load a vocabulary for a project. |
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| 239 | \f |
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| 240 | This will load the vocabulary to be used in subject indexing. Note that |
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| 241 | although ``PROJECT_ID`` is a parameter of the command, the vocabulary is |
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| 242 | shared by all the projects with the same vocab identifier in the project |
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| 243 | configuration, and the vocabulary only needs to be loaded for one of those |
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| 244 | projects. |
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| 245 | |||
| 246 | If a vocabulary has already been loaded, reinvoking loadvoc with a new |
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| 247 | subject file will update the Annif’s internal vocabulary: label names are |
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| 248 | updated and any subject not appearing in the new subject file is removed. |
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| 249 | Note that new subjects will not be suggested before the project is |
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| 250 | retrained with the updated vocabulary. The update behavior can be |
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| 251 | overridden with the ``--force`` option. |
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| 252 | """ |
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| 253 | proj = get_project(project_id) |
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| 254 | if annif.corpus.SubjectFileSKOS.is_rdf_file(subjectfile): |
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| 255 | # SKOS/RDF file supported by rdflib |
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| 256 | subjects = annif.corpus.SubjectFileSKOS(subjectfile) |
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| 257 | elif annif.corpus.SubjectFileCSV.is_csv_file(subjectfile): |
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| 258 | # CSV file |
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| 259 | subjects = annif.corpus.SubjectFileCSV(subjectfile) |
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| 260 | else: |
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| 261 | # probably a TSV file |
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| 262 | subjects = annif.corpus.SubjectFileTSV(subjectfile, proj.vocab_lang) |
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| 263 | proj.vocab.load_vocabulary(subjects, force=force) |
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| 264 | |||
| 265 | |||
| 266 | View Code Duplication | @cli.command('load-vocab') |
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| 267 | @click.argument('vocab_id') |
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| 268 | @click.argument('subjectfile', type=click.Path(exists=True, dir_okay=False)) |
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| 269 | @click.option('--language', '-L', help='Language of subject file') |
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| 270 | @click.option('--force', '-f', default=False, is_flag=True, |
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| 271 | help='Replace existing vocabulary completely ' + |
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| 272 | 'instead of updating it') |
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| 273 | @common_options |
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| 274 | def run_load_vocab(vocab_id, language, force, subjectfile): |
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| 275 | """ |
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| 276 | Load a vocabulary from a subject file. |
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| 277 | """ |
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| 278 | vocab = get_vocab(vocab_id) |
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| 279 | if annif.corpus.SubjectFileSKOS.is_rdf_file(subjectfile): |
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| 280 | # SKOS/RDF file supported by rdflib |
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| 281 | subjects = annif.corpus.SubjectFileSKOS(subjectfile) |
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| 282 | elif annif.corpus.SubjectFileCSV.is_csv_file(subjectfile): |
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| 283 | # CSV file |
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| 284 | subjects = annif.corpus.SubjectFileCSV(subjectfile) |
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| 285 | else: |
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| 286 | # probably a TSV file - we need to know its language |
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| 287 | if not language: |
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| 288 | click.echo("Please use --language option to set the language of " + |
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| 289 | "a TSV vocabulary.", err=True) |
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| 290 | sys.exit(1) |
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| 291 | subjects = annif.corpus.SubjectFileTSV(subjectfile, language) |
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| 292 | vocab.load_vocabulary(subjects, force=force) |
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| 293 | |||
| 294 | |||
| 295 | View Code Duplication | @cli.command('train') |
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| 296 | @click.argument('project_id') |
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| 297 | @click.argument('paths', type=click.Path(exists=True), nargs=-1) |
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| 298 | @click.option('--cached/--no-cached', '-c/-C', default=False, |
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| 299 | help='Reuse preprocessed training data from previous run') |
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| 300 | @click.option('--docs-limit', '-d', default=None, |
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| 301 | type=click.IntRange(0, None), |
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| 302 | help='Maximum number of documents to use') |
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| 303 | @click.option('--jobs', |
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| 304 | '-j', |
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| 305 | default=0, |
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| 306 | help='Number of parallel jobs (0 means choose automatically)') |
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| 307 | @backend_param_option |
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| 308 | @common_options |
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| 309 | def run_train(project_id, paths, cached, docs_limit, jobs, backend_param): |
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| 310 | """ |
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| 311 | Train a project on a collection of documents. |
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| 312 | \f |
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| 313 | This will train the project using the documents from ``PATHS`` (directories |
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| 314 | or possibly gzipped TSV files) in a single batch operation. If ``--cached`` |
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| 315 | is set, preprocessed training data from the previous run is reused instead |
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| 316 | of documents input; see `Reusing preprocessed training data |
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| 317 | <https://github.com/NatLibFi/Annif/wiki/ |
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| 318 | Reusing-preprocessed-training-data>`_. |
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| 319 | """ |
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| 320 | proj = get_project(project_id) |
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| 321 | backend_params = parse_backend_params(backend_param, proj) |
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| 322 | if cached: |
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| 323 | if len(paths) > 0: |
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| 324 | raise click.UsageError( |
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| 325 | "Corpus paths cannot be given when using --cached option.") |
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| 326 | documents = 'cached' |
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| 327 | else: |
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| 328 | documents = open_documents(paths, proj.subjects, |
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| 329 | proj.vocab_lang, docs_limit) |
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| 330 | proj.train(documents, backend_params, jobs) |
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| 331 | |||
| 332 | |||
| 333 | View Code Duplication | @cli.command('learn') |
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| 334 | @click.argument('project_id') |
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| 335 | @click.argument('paths', type=click.Path(exists=True), nargs=-1) |
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| 336 | @click.option('--docs-limit', '-d', default=None, |
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| 337 | type=click.IntRange(0, None), |
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| 338 | help='Maximum number of documents to use') |
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| 339 | @backend_param_option |
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| 340 | @common_options |
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| 341 | def run_learn(project_id, paths, docs_limit, backend_param): |
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| 342 | """ |
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| 343 | Further train an existing project on a collection of documents. |
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| 344 | \f |
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| 345 | Similar to the ``train`` command. This will continue training an already |
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| 346 | trained project using the documents given by ``PATHS`` in a single batch |
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| 347 | operation. Not supported by all backends. |
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| 348 | """ |
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| 349 | proj = get_project(project_id) |
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| 350 | backend_params = parse_backend_params(backend_param, proj) |
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| 351 | documents = open_documents(paths, proj.subjects, |
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| 352 | proj.vocab_lang, docs_limit) |
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| 353 | proj.learn(documents, backend_params) |
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| 354 | |||
| 355 | |||
| 356 | View Code Duplication | @cli.command('suggest') |
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| 357 | @click.argument('project_id') |
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| 358 | @click.option('--limit', '-l', default=10, help='Maximum number of subjects') |
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| 359 | @click.option('--threshold', '-t', default=0.0, help='Minimum score threshold') |
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| 360 | @backend_param_option |
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| 361 | @common_options |
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| 362 | def run_suggest(project_id, limit, threshold, backend_param): |
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| 363 | """ |
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| 364 | Suggest subjects for a single document from standard input. |
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| 365 | \f |
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| 366 | This will read a text document from standard input and suggest subjects for |
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| 367 | it. |
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| 368 | """ |
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| 369 | project = get_project(project_id) |
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| 370 | text = sys.stdin.read() |
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| 371 | backend_params = parse_backend_params(backend_param, project) |
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| 372 | hit_filter = SuggestionFilter(project.subjects, limit, threshold) |
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| 373 | hits = hit_filter(project.suggest(text, backend_params)) |
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| 374 | for hit in hits.as_list(): |
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| 375 | subj = project.subjects[hit.subject_id] |
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| 376 | click.echo( |
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| 377 | "<{}>\t{}\t{}".format( |
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| 378 | subj.uri, |
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| 379 | '\t'.join(filter(None, |
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| 380 | (subj.labels[project.vocab_lang], |
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| 381 | subj.notation))), |
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| 382 | hit.score)) |
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| 383 | |||
| 384 | |||
| 385 | View Code Duplication | @cli.command('index') |
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| 386 | @click.argument('project_id') |
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| 387 | @click.argument('directory', type=click.Path(exists=True, file_okay=False)) |
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| 388 | @click.option( |
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| 389 | '--suffix', |
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| 390 | '-s', |
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| 391 | default='.annif', |
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| 392 | help='File name suffix for result files') |
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| 393 | @click.option('--force/--no-force', '-f/-F', default=False, |
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| 394 | help='Force overwriting of existing result files') |
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| 395 | @click.option('--limit', '-l', default=10, help='Maximum number of subjects') |
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| 396 | @click.option('--threshold', '-t', default=0.0, help='Minimum score threshold') |
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| 397 | @backend_param_option |
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| 398 | @common_options |
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| 399 | def run_index(project_id, directory, suffix, force, |
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| 400 | limit, threshold, backend_param): |
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| 401 | """ |
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| 402 | Index a directory with documents, suggesting subjects for each document. |
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| 403 | Write the results in TSV files with the given suffix (``.annif`` by |
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| 404 | default). |
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| 405 | """ |
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| 406 | project = get_project(project_id) |
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| 407 | backend_params = parse_backend_params(backend_param, project) |
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| 408 | hit_filter = SuggestionFilter(project.subjects, limit, threshold) |
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| 409 | |||
| 410 | for docfilename, dummy_subjectfn in annif.corpus.DocumentDirectory( |
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| 411 | directory, project.subjects, project.vocab_lang, |
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| 412 | require_subjects=False): |
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| 413 | with open(docfilename, encoding='utf-8-sig') as docfile: |
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| 414 | text = docfile.read() |
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| 415 | subjectfilename = re.sub(r'\.txt$', suffix, docfilename) |
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| 416 | if os.path.exists(subjectfilename) and not force: |
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| 417 | click.echo( |
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| 418 | "Not overwriting {} (use --force to override)".format( |
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| 419 | subjectfilename)) |
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| 420 | continue |
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| 421 | with open(subjectfilename, 'w', encoding='utf-8') as subjfile: |
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| 422 | results = project.suggest(text, backend_params) |
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| 423 | for hit in hit_filter(results).as_list(): |
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| 424 | subj = project.subjects[hit.subject_id] |
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| 425 | line = "<{}>\t{}\t{}".format( |
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| 426 | subj.uri, |
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| 427 | '\t'.join(filter(None, (subj.labels[project.vocab_lang], |
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| 428 | subj.notation))), |
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| 429 | hit.score) |
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| 430 | click.echo(line, file=subjfile) |
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| 431 | |||
| 432 | |||
| 433 | View Code Duplication | @cli.command('eval') |
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| 434 | @click.argument('project_id') |
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| 435 | @click.argument('paths', type=click.Path(exists=True), nargs=-1) |
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| 436 | @click.option('--limit', '-l', default=10, help='Maximum number of subjects') |
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| 437 | @click.option('--threshold', '-t', default=0.0, help='Minimum score threshold') |
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| 438 | @click.option('--docs-limit', '-d', default=None, |
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| 439 | type=click.IntRange(0, None), |
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| 440 | help='Maximum number of documents to use') |
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| 441 | @click.option('--metric', '-m', default=[], multiple=True, |
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| 442 | help='Metric to calculate (default: all)') |
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| 443 | @click.option( |
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| 444 | '--metrics-file', |
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| 445 | '-M', |
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| 446 | type=click.File( |
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| 447 | 'w', |
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| 448 | encoding='utf-8', |
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| 449 | errors='ignore', |
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| 450 | lazy=True), |
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| 451 | help="""Specify file in order to write evaluation metrics in JSON format. |
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| 452 | File directory must exist, existing file will be overwritten.""") |
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| 453 | @click.option( |
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| 454 | '--results-file', |
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| 455 | '-r', |
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| 456 | type=click.File( |
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| 457 | 'w', |
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| 458 | encoding='utf-8', |
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| 459 | errors='ignore', |
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| 460 | lazy=True), |
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| 461 | help="""Specify file in order to write non-aggregated results per subject. |
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| 462 | File directory must exist, existing file will be overwritten.""") |
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| 463 | @click.option('--jobs', |
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| 464 | '-j', |
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| 465 | default=1, |
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| 466 | help='Number of parallel jobs (0 means all CPUs)') |
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| 467 | @backend_param_option |
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| 468 | @common_options |
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| 469 | def run_eval( |
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| 470 | project_id, |
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| 471 | paths, |
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| 472 | limit, |
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| 473 | threshold, |
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| 474 | docs_limit, |
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| 475 | metric, |
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| 476 | metrics_file, |
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| 477 | results_file, |
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| 478 | jobs, |
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| 479 | backend_param): |
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| 480 | """ |
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| 481 | Suggest subjects for documents and evaluate the results by comparing |
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| 482 | against a gold standard. |
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| 483 | \f |
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| 484 | With this command the documents from ``PATHS`` (directories or possibly |
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| 485 | gzipped TSV files) will be assigned subject suggestions and then |
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| 486 | statistical measures are calculated that quantify how well the suggested |
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| 487 | subjects match the gold-standard subjects in the documents. |
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| 488 | |||
| 489 | Normally the output is the list of the metrics calculated across documents. |
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| 490 | If ``--results-file <FILENAME>`` option is given, the metrics are |
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| 491 | calculated separately for each subject, and written to the given file. |
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| 492 | """ |
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| 493 | |||
| 494 | project = get_project(project_id) |
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| 495 | backend_params = parse_backend_params(backend_param, project) |
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| 496 | |||
| 497 | import annif.eval |
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| 498 | eval_batch = annif.eval.EvaluationBatch(project.subjects) |
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| 499 | |||
| 500 | if results_file: |
||
| 501 | try: |
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| 502 | print('', end='', file=results_file) |
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| 503 | click.echo('Writing per subject evaluation results to {!s}'.format( |
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| 504 | results_file.name)) |
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| 505 | except Exception as e: |
||
| 506 | raise NotSupportedException( |
||
| 507 | "cannot open results-file for writing: " + str(e)) |
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| 508 | docs = open_documents(paths, project.subjects, |
||
| 509 | project.vocab_lang, docs_limit) |
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| 510 | |||
| 511 | jobs, pool_class = annif.parallel.get_pool(jobs) |
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| 512 | |||
| 513 | project.initialize(parallel=True) |
||
| 514 | psmap = annif.parallel.ProjectSuggestMap( |
||
| 515 | project.registry, [project_id], backend_params, limit, threshold) |
||
| 516 | |||
| 517 | with pool_class(jobs) as pool: |
||
| 518 | for hits, subject_set in pool.imap_unordered( |
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| 519 | psmap.suggest, docs.documents): |
||
| 520 | eval_batch.evaluate(hits[project_id], |
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| 521 | subject_set) |
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| 522 | |||
| 523 | template = "{0:<30}\t{1}" |
||
| 524 | metrics = eval_batch.results(metrics=metric, |
||
| 525 | results_file=results_file, |
||
| 526 | language=project.vocab_lang) |
||
| 527 | for metric, score in metrics.items(): |
||
| 528 | click.echo(template.format(metric + ":", score)) |
||
| 529 | if metrics_file: |
||
| 530 | json.dump( |
||
| 531 | {metric_code(mname): val for mname, val in metrics.items()}, |
||
| 532 | metrics_file, indent=2) |
||
| 533 | |||
| 534 | |||
| 535 | View Code Duplication | @cli.command('optimize') |
|
| 536 | @click.argument('project_id') |
||
| 537 | @click.argument('paths', type=click.Path(exists=True), nargs=-1) |
||
| 538 | @click.option('--docs-limit', '-d', default=None, |
||
| 539 | type=click.IntRange(0, None), |
||
| 540 | help='Maximum number of documents to use') |
||
| 541 | @backend_param_option |
||
| 542 | @common_options |
||
| 543 | def run_optimize(project_id, paths, docs_limit, backend_param): |
||
| 544 | """ |
||
| 545 | Suggest subjects for documents, testing multiple limits and thresholds. |
||
| 546 | \f |
||
| 547 | This command will use different limit (maximum number of subjects) and |
||
| 548 | score threshold values when assigning subjects to each document given by |
||
| 549 | ``PATHS`` and compare the results against the gold standard subjects in the |
||
| 550 | documents. The output is a list of parameter combinations and their scores. |
||
| 551 | From the output, you can determine the optimum limit and threshold |
||
| 552 | parameters depending on which measure you want to target. |
||
| 553 | """ |
||
| 554 | project = get_project(project_id) |
||
| 555 | backend_params = parse_backend_params(backend_param, project) |
||
| 556 | |||
| 557 | filter_batches = generate_filter_batches(project.subjects) |
||
| 558 | |||
| 559 | ndocs = 0 |
||
| 560 | docs = open_documents(paths, project.subjects, |
||
| 561 | project.vocab_lang, docs_limit) |
||
| 562 | for doc in docs.documents: |
||
| 563 | raw_hits = project.suggest(doc.text, backend_params) |
||
| 564 | hits = raw_hits.filter(project.subjects, limit=BATCH_MAX_LIMIT) |
||
| 565 | assert isinstance(hits, ListSuggestionResult), \ |
||
| 566 | "Optimize should only be done with ListSuggestionResult " + \ |
||
| 567 | "as it would be very slow with VectorSuggestionResult." |
||
| 568 | for hit_filter, batch in filter_batches.values(): |
||
| 569 | batch.evaluate(hit_filter(hits), doc.subject_set) |
||
| 570 | ndocs += 1 |
||
| 571 | |||
| 572 | click.echo("\t".join(('Limit', 'Thresh.', 'Prec.', 'Rec.', 'F1'))) |
||
| 573 | |||
| 574 | best_scores = collections.defaultdict(float) |
||
| 575 | best_params = {} |
||
| 576 | |||
| 577 | template = "{:d}\t{:.02f}\t{:.04f}\t{:.04f}\t{:.04f}" |
||
| 578 | # Store the batches in a list that gets consumed along the way |
||
| 579 | # This way GC will have a chance to reclaim the memory |
||
| 580 | filter_batches = list(filter_batches.items()) |
||
| 581 | while filter_batches: |
||
| 582 | params, filter_batch = filter_batches.pop(0) |
||
| 583 | metrics = ['Precision (doc avg)', |
||
| 584 | 'Recall (doc avg)', |
||
| 585 | 'F1 score (doc avg)'] |
||
| 586 | results = filter_batch[1].results(metrics=metrics) |
||
| 587 | for metric, score in results.items(): |
||
| 588 | if score >= best_scores[metric]: |
||
| 589 | best_scores[metric] = score |
||
| 590 | best_params[metric] = params |
||
| 591 | click.echo( |
||
| 592 | template.format( |
||
| 593 | params[0], |
||
| 594 | params[1], |
||
| 595 | results['Precision (doc avg)'], |
||
| 596 | results['Recall (doc avg)'], |
||
| 597 | results['F1 score (doc avg)'])) |
||
| 598 | |||
| 599 | click.echo() |
||
| 600 | template2 = "Best {:>19}: {:.04f}\tLimit: {:d}\tThreshold: {:.02f}" |
||
| 601 | for metric in metrics: |
||
| 602 | click.echo( |
||
| 603 | template2.format( |
||
| 604 | metric, |
||
| 605 | best_scores[metric], |
||
| 606 | best_params[metric][0], |
||
| 607 | best_params[metric][1])) |
||
| 608 | click.echo("Documents evaluated:\t{}".format(ndocs)) |
||
| 609 | |||
| 610 | |||
| 611 | View Code Duplication | @cli.command('hyperopt') |
|
| 612 | @click.argument('project_id') |
||
| 613 | @click.argument('paths', type=click.Path(exists=True), nargs=-1) |
||
| 614 | @click.option('--docs-limit', '-d', default=None, |
||
| 615 | type=click.IntRange(0, None), |
||
| 616 | help='Maximum number of documents to use') |
||
| 617 | @click.option('--trials', '-T', default=10, help='Number of trials') |
||
| 618 | @click.option('--jobs', |
||
| 619 | '-j', |
||
| 620 | default=1, |
||
| 621 | help='Number of parallel runs (0 means all CPUs)') |
||
| 622 | @click.option('--metric', '-m', default='NDCG', |
||
| 623 | help='Metric to optimize (default: NDCG)') |
||
| 624 | @click.option( |
||
| 625 | '--results-file', |
||
| 626 | '-r', |
||
| 627 | type=click.File( |
||
| 628 | 'w', |
||
| 629 | encoding='utf-8', |
||
| 630 | errors='ignore', |
||
| 631 | lazy=True), |
||
| 632 | help="""Specify file path to write trial results as CSV. |
||
| 633 | File directory must exist, existing file will be overwritten.""") |
||
| 634 | @common_options |
||
| 635 | def run_hyperopt(project_id, paths, docs_limit, trials, jobs, metric, |
||
| 636 | results_file): |
||
| 637 | """ |
||
| 638 | Optimize the hyperparameters of a project using validation documents from |
||
| 639 | ``PATHS``. Not supported by all backends. Output is a list of trial results |
||
| 640 | and a report of the best performing parameters. |
||
| 641 | """ |
||
| 642 | proj = get_project(project_id) |
||
| 643 | documents = open_documents(paths, proj.subjects, |
||
| 644 | proj.vocab_lang, docs_limit) |
||
| 645 | click.echo(f"Looking for optimal hyperparameters using {trials} trials") |
||
| 646 | rec = proj.hyperopt(documents, trials, jobs, metric, results_file) |
||
| 647 | click.echo(f"Got best {metric} score {rec.score:.4f} with:") |
||
| 648 | click.echo("---") |
||
| 649 | for line in rec.lines: |
||
| 650 | click.echo(line) |
||
| 651 | click.echo("---") |
||
| 652 | |||
| 653 | |||
| 654 | if __name__ == '__main__': |
||
| 655 | cli() |
||
| 656 |