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and "agribalyse_food_code" in taxonomy[insight.value_tag].additional_data + and "agribalyse_food_code" in taxonomy[insight.value_tag].properties ): # This category is linked to an agribalyse category, add it as a # campaign tag diff --git a/robotoff/prediction/category/neural/keras_category_classifier_3_0/preprocessing.py b/robotoff/prediction/category/neural/keras_category_classifier_3_0/preprocessing.py index 03e1a34968..d7f278d618 100644 --- a/robotoff/prediction/category/neural/keras_category_classifier_3_0/preprocessing.py +++ b/robotoff/prediction/category/neural/keras_category_classifier_3_0/preprocessing.py @@ -8,7 +8,7 @@ import numpy as np from robotoff import settings -from robotoff.taxonomy import Taxonomy, fetch_taxonomy +from robotoff.taxonomy import Taxonomy from robotoff.types import JSONType from robotoff.utils.text import KeywordProcessor @@ -35,11 +35,7 @@ @functools.cache def get_ingredient_taxonomy(): - return fetch_taxonomy( - "", - V3_MODEL_DATA_DIR / "ingredients.full.json.gz", - offline=True, - ) + return Taxonomy.from_path(V3_MODEL_DATA_DIR / "ingredients.full.json.gz") @functools.cache diff --git a/robotoff/taxonomy.py b/robotoff/taxonomy.py index a4cf962de0..9fac4ec4a3 100644 --- a/robotoff/taxonomy.py +++ b/robotoff/taxonomy.py @@ -1,255 +1,18 @@ import collections -import pathlib -from enum import Enum -from typing import Any, Iterable, Optional, Union +from typing import Optional import cachetools -import requests +from openfoodfacts.taxonomy import Taxonomy +from openfoodfacts.taxonomy import get_taxonomy as _get_taxonomy +from openfoodfacts.types import TaxonomyType from robotoff import settings -from robotoff.types import JSONType -from robotoff.utils import get_logger, http_session, load_json +from robotoff.utils import get_logger from robotoff.utils.text import get_tag -try: - import networkx -except ImportError: - networkx = None - logger = get_logger(__name__) -class TaxonomyType(Enum): - category = 1 - ingredient = 2 - label = 3 - brand = 4 - packaging_shape = 5 - packaging_material = 6 - packaging_recycling = 7 - - -class TaxonomyNode: - __slots__ = ("id", "names", "parents", "children", "synonyms", "additional_data") - - def __init__( - self, - identifier: str, - names: dict[str, str], - synonyms: Optional[dict[str, list[str]]], - additional_data: Optional[dict[str, Any]] = None, - ): - self.id: str = identifier - self.names: dict[str, str] = names - self.parents: list["TaxonomyNode"] = [] - self.children: list["TaxonomyNode"] = [] - self.additional_data = additional_data or {} - - if synonyms: - self.synonyms = synonyms - else: - self.synonyms = {} - - def is_child_of(self, item: "TaxonomyNode") -> bool: - """Return True if `item` is a child of `self` in the taxonomy.""" - if not self.parents: - return False - - if item in self.parents: - return True - - for parent in self.parents: - is_parent = parent.is_child_of(item) - - if is_parent: - return True - - return False - - def is_parent_of(self, item: "TaxonomyNode") -> bool: - return item.is_child_of(self) - - def is_parent_of_any(self, candidates: Iterable["TaxonomyNode"]) -> bool: - for candidate in candidates: - if candidate.is_child_of(self): - return True - - return False - - def get_parents_hierarchy(self) -> list["TaxonomyNode"]: - """Return the list of all parent nodes (direct and indirect).""" - all_parents = [] - seen: set[str] = set() - - if not self.parents: - return [] - - for self_parent in self.parents: - if self_parent.id not in seen: - all_parents.append(self_parent) - seen.add(self_parent.id) - - for parent_parent in self_parent.get_parents_hierarchy(): - if parent_parent.id not in seen: - all_parents.append(parent_parent) - seen.add(parent_parent.id) - - return all_parents - - def get_localized_name(self, lang: str) -> str: - if lang in self.names: - return self.names[lang] - - if "xx" in self.names: - # Return international name if it exists - return self.names["xx"] - - return self.id - - def get_synonyms(self, lang: str) -> list[str]: - return self.synonyms.get(lang, []) - - def add_parents(self, parents: Iterable["TaxonomyNode"]): - for parent in parents: - if parent not in self.parents: - self.parents.append(parent) - parent.children.append(self) - - def to_dict(self) -> JSONType: - return {"name": self.names, "parents": [p.id for p in self.parents]} - - def __repr__(self): - return "" % self.id - - -class Taxonomy: - def __init__(self) -> None: - self.nodes: dict[str, TaxonomyNode] = {} - - def add(self, key: str, node: TaxonomyNode) -> None: - self.nodes[key] = node - - def __contains__(self, item: str): - return item in self.nodes - - def __getitem__(self, item: str): - return self.nodes.get(item) - - def __len__(self): - return len(self.nodes) - - def iter_nodes(self) -> Iterable[TaxonomyNode]: - """Iterate over the nodes of the taxonomy.""" - return iter(self.nodes.values()) - - def keys(self): - return self.nodes.keys() - - def find_deepest_nodes(self, nodes: list[TaxonomyNode]) -> list[TaxonomyNode]: - """Given a list of nodes, returns the list of nodes where all the - parents within the list have been removed. - - For example, for a taxonomy, 'fish' -> 'salmon' -> 'smoked-salmon': - - ['fish', 'salmon'] -> ['salmon'] ['fish', 'smoked-salmon'] -> - [smoked-salmon'] - """ - excluded: set[str] = set() - - for node in nodes: - for second_node in ( - n for n in nodes if n.id not in excluded and n.id != node.id - ): - if node.is_child_of(second_node): - excluded.add(second_node.id) - - return [node for node in nodes if node.id not in excluded] - - def is_parent_of_any( - self, item: str, candidates: Iterable[str], raises: bool = True - ) -> bool: - """Return True if `item` is parent of any candidate, False otherwise. - - If the item is not in the taxonomy and raises is False, return False. - - :param item: The item to compare - :param candidates: A list of candidates - :param raises: if True, raises a ValueError if item is not in the - taxonomy, defaults to True. - """ - node: TaxonomyNode = self[item] - - if node is None: - if raises: - raise ValueError(f"unknown id in taxonomy: {node}") - else: - return False - - to_check_nodes: set[TaxonomyNode] = set() - - for candidate in candidates: - candidate_node = self[candidate] - - if candidate_node is not None: - to_check_nodes.add(candidate_node) - - return node.is_parent_of_any(to_check_nodes) - - def get_localized_name(self, key: str, lang: str) -> str: - if key not in self.nodes: - return key - - return self.nodes[key].get_localized_name(lang) - - def to_dict(self) -> JSONType: - export = {} - - for key, node in self.nodes.items(): - export[key] = node.to_dict() - - return export - - @classmethod - def from_dict(cls, data: JSONType) -> "Taxonomy": - taxonomy = Taxonomy() - - for key, key_data in data.items(): - if key not in taxonomy: - node = TaxonomyNode( - identifier=key, - names=key_data.get("name", {}), - synonyms=key_data.get("synonyms", None), - additional_data={ - k: v - for k, v in key_data.items() - if k not in {"parents", "name", "synonyms", "children"} - }, - ) - taxonomy.add(key, node) - - for key, key_data in data.items(): - node = taxonomy[key] - parents = [taxonomy[ref] for ref in key_data.get("parents", [])] - node.add_parents(parents) - - return taxonomy - - @classmethod - def from_json(cls, file_path: Union[str, pathlib.Path]): - return cls.from_dict(load_json(file_path, compressed=True)) # type: ignore - - def to_graph(self): - """Generate a networkx.DiGraph from the taxonomy.""" - graph = networkx.DiGraph() - graph.add_nodes_from((x.id for x in self.iter_nodes())) - - for node in self.iter_nodes(): - for child in node.children: - graph.add_edge(node.id, child.id) - - return graph - - def generate_category_hierarchy( taxonomy: Taxonomy, category_to_index: dict[str, int], root: int ): @@ -280,42 +43,28 @@ def generate_category_hierarchy( return categories_hierarchy_list -def fetch_taxonomy( - url: str, fallback_path: Optional[str] = None, offline: bool = False -) -> Taxonomy: - if offline and fallback_path: - return Taxonomy.from_json(fallback_path) - - try: - r = http_session.get(url, timeout=120) # might take some time - if r.status_code >= 300: - raise requests.HTTPError( - "Taxonomy download at %s returned status code %s", url, r.status_code - ) - data = r.json() - except Exception as e: - logger.exception(f"{type(e)} exception while fetching taxonomy at %s", url) - if fallback_path: - return Taxonomy.from_json(fallback_path) - else: - raise e - - return Taxonomy.from_dict(data) - - @cachetools.cached(cache=cachetools.TTLCache(maxsize=100, ttl=12 * 60 * 60)) # 12h def get_taxonomy(taxonomy_type: str, offline: bool = False) -> Taxonomy: - """Returned the requested Taxonomy.""" - logger.info("Loading taxonomy %s...", taxonomy_type) + """Return the taxonomy of type `taxonomy_type`. + + The taxonomy is cached in memory and locally on disk. Every 12h, we check + if a new version is available and download if True. - if taxonomy_type not in settings.TAXONOMY_URLS: - raise ValueError(f"unknown taxonomy type: {taxonomy_type}") + A local static version can also be fetched (for unit tests for example) + with `offline=True`. + + :param taxonomy_type: the taxonomy type + :param offline: if True, return a local static version of the taxonomy, + defaults to False. It's not available for all taxonomy types. + :return: the Taxonomy + """ + if offline: + return Taxonomy.from_path(str(settings.TAXONOMY_PATHS[taxonomy_type])) - url = settings.TAXONOMY_URLS[taxonomy_type] - return fetch_taxonomy( - url, - fallback_path=str(settings.TAXONOMY_PATHS.get(taxonomy_type, "")) or None, - offline=offline, + return _get_taxonomy( + TaxonomyType[taxonomy_type], + force_download=False, + cache_dir=settings.DATA_DIR / "taxonomies", ) diff --git a/scripts/category_dataset.py b/scripts/category_dataset.py index 9ca29d99c3..fe2013a6f8 100644 --- a/scripts/category_dataset.py +++ b/scripts/category_dataset.py @@ -17,11 +17,12 @@ import os from typing import Iterator, Optional +from openfoodfacts.taxonomy import Taxonomy, TaxonomyNode from sklearn.model_selection import train_test_split from robotoff import settings from robotoff.products import ProductDataset, ProductStream -from robotoff.taxonomy import Taxonomy, TaxonomyNode, get_taxonomy +from robotoff.taxonomy import get_taxonomy from robotoff.types import JSONType from robotoff.utils import dump_jsonl, get_logger diff --git a/tests/conftest.py b/tests/conftest.py index 4269f80289..5428f872c8 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -46,4 +46,4 @@ def peewee_db(peewee_db_create): @pytest.fixture(scope="session") def category_taxonomy(): - return Taxonomy.from_json(settings.TAXONOMY_PATHS["category"]) + return Taxonomy.from_path(settings.TAXONOMY_PATHS["category"]) diff --git a/tests/integration/test_annotate_image.py b/tests/integration/test_annotate_image.py index 5be3ccb448..1967e51636 100644 --- a/tests/integration/test_annotate_image.py +++ b/tests/integration/test_annotate_image.py @@ -4,6 +4,7 @@ import falcon.testing import pytest +from openfoodfacts.types import TaxonomyType import robotoff.insights.importer import robotoff.taxonomy @@ -31,11 +32,11 @@ def _set_up_and_tear_down(peewee_db): @pytest.fixture def fake_taxonomy(monkeypatch): - def fetch_taxonomy_mock(url: str, *args, **kwargs): + def _get_taxonomy_mock(taxonomy_type: TaxonomyType, *args, **kwargs): data: Any = None - if "/brands." in url: + if taxonomy_type is TaxonomyType.brand: data = {"en:etorki": {"name": {"en": "Etorki"}}} - elif "/labels." in url: + elif taxonomy_type is TaxonomyType.label: data = { "en:organic": { "synonyms": {"fr": ["Bio"]}, @@ -50,8 +51,8 @@ def fetch_taxonomy_mock(url: str, *args, **kwargs): monkeypatch.setattr( robotoff.taxonomy, - "fetch_taxonomy", - fetch_taxonomy_mock, + "_get_taxonomy", + _get_taxonomy_mock, ) diff --git a/tests/unit/test_taxonomy.py b/tests/unit/test_taxonomy.py index aa73785d90..59039c6acd 100644 --- a/tests/unit/test_taxonomy.py +++ b/tests/unit/test_taxonomy.py @@ -3,8 +3,8 @@ from robotoff import settings from robotoff.taxonomy import Taxonomy, TaxonomyType, match_taxonomized_value -label_taxonomy = Taxonomy.from_json(settings.TAXONOMY_PATHS["label"]) -category_taxonomy = Taxonomy.from_json(settings.TAXONOMY_PATHS["category"]) +label_taxonomy = Taxonomy.from_path(settings.TAXONOMY_PATHS["label"]) +category_taxonomy = Taxonomy.from_path(settings.TAXONOMY_PATHS["category"]) class TestTaxonomy: