fix: use datetime.now(timezone.utc) instead of utcnow()

robotoff/app/api.py

@@ -795,7 +795,7 @@ class ImagePredictionImporterResource:
     @jsonschema.validate(schema.IMAGE_PREDICTION_IMPORTER_SCHEMA)
     def on_post(self, req: falcon.Request, resp: falcon.Response):
         server_type = get_server_type_from_req(req)
-        timestamp = datetime.datetime.utcnow()
+        timestamp = datetime.datetime.now(datetime.timezone.utc)
         inserts = []
         media = req.get_media()
 
@@ -1077,7 +1077,7 @@ def on_put(self, req: falcon.Request, resp: falcon.Response, logo_id: int):
                 annotated_logos = update_logo_annotations(
                     [(type_, value, logo)],
                     username=auth.get_username() or "unknown",
-                    completed_at=datetime.datetime.utcnow(),
+                    completed_at=datetime.datetime.now(datetime.timezone.utc),
                 )
                 server_type = ServerType[logo.image_prediction.image.server_type]
                 generate_insights_from_annotated_logos(
@@ -1151,7 +1151,7 @@ def on_post(self, req: falcon.Request, resp: falcon.Response):
             )
         server_type = get_server_type_from_req(req)
         annotations = media["annotations"]
-        completed_at = datetime.datetime.utcnow()
+        completed_at = datetime.datetime.now(datetime.timezone.utc)
         annotation_logos = []
 
         with db.atomic():
@@ -1209,7 +1209,7 @@ def on_post(self, req: falcon.Request, resp: falcon.Response):
 
         auth = parse_auth(req)
         username = None if auth is None else auth.get_username()
-        completed_at = datetime.datetime.utcnow()
+        completed_at = datetime.datetime.now(datetime.timezone.utc)
 
         target_value_tag = get_tag(target_value)
         source_value_tag = get_tag(source_value)

robotoff/cli/logos.py

@@ -43,7 +43,7 @@ def import_logos(
 
     for batch in chunked(tqdm.tqdm(jsonl_iter(data_path)), batch_size):
         with db.atomic():
-            timestamp = datetime.datetime.utcnow()
+            timestamp = datetime.datetime.now(datetime.timezone.utc)
             for item in batch:
                 barcode = item["barcode"]
                 product_id = ProductIdentifier(barcode, server_type)

robotoff/insights/annotate.py

@@ -165,7 +165,7 @@ def _annotate(
 
         insight.username = username
         insight.annotation = annotation
-        insight.completed_at = datetime.datetime.utcnow()
+        insight.completed_at = datetime.datetime.now(datetime.timezone.utc)
 
         if annotation in (1, 2) and update:
             # Save insight before processing the annotation

robotoff/insights/extraction.py

@@ -84,7 +84,7 @@ def run_object_detection_model(
             return None
         return existing_image_prediction
 
-    timestamp = datetime.datetime.utcnow()
+    timestamp = datetime.datetime.now(datetime.timezone.utc)
     results = ObjectDetectionModelRegistry.get(model_name.value).detect_from_image(
         image, output_image=False, triton_uri=triton_uri, threshold=threshold
     )

robotoff/insights/importer.py

@@ -382,7 +382,7 @@ def generate_insights(
         It calls the `generate_candidates` method, specific to each insight
         type (and implemented in sub-classes).
         """
-        timestamp = datetime.datetime.utcnow()
+        timestamp = datetime.datetime.now(datetime.timezone.utc)
 
         product = product_store[product_id]
         references = get_existing_insight(cls.get_type(), product_id)
@@ -1776,7 +1776,7 @@ def import_product_predictions(
     :return: a (imported, deleted) tuple: the number of predictions imported
         and deleted in DB.
     """
-    timestamp = datetime.datetime.utcnow()
+    timestamp = datetime.datetime.now(datetime.timezone.utc)
 
     deleted = 0
     if delete_previous_versions:

robotoff/logos.py

@@ -200,7 +200,7 @@ def save_nearest_neighbors(
             logo_embedding.logo.nearest_neighbors = {
                 "distances": distances,
                 "logo_ids": logo_ids,
-                "updated_at": datetime.datetime.utcnow().isoformat(),
+                "updated_at": datetime.datetime.now(datetime.timezone.utc).isoformat(),
             }
             updated.append(logo_embedding.logo)
 

robotoff/scheduler/__init__.py

@@ -47,7 +47,8 @@ def process_insights() -> None:
             .where(
                 ProductInsight.annotation.is_null(),
                 ProductInsight.process_after.is_null(False),
-                ProductInsight.process_after <= datetime.datetime.utcnow(),
+                ProductInsight.process_after
+                <= datetime.datetime.now(datetime.timezone.utc),
             )
             .iterator()
         ):
@@ -99,7 +100,7 @@ def refresh_insights(with_deletion: bool = True) -> None:
     # Only OFF is currently supported
     server_type = ServerType.off
 
-    datetime_threshold = datetime.datetime.utcnow().replace(
+    datetime_threshold = datetime.datetime.now(datetime.timezone.utc).replace(
         hour=0, minute=0, second=0, microsecond=0
     )
     dataset_datetime = datetime.datetime.fromtimestamp(

robotoff/workers/tasks/import_image.py

@@ -340,7 +340,7 @@ def run_upc_detection(product_id: ProductIdentifier, image_url: str) -> None:
                     "class": prediction_class.value,
                 },
                 max_confidence=None,
-                timestamp=datetime.datetime.utcnow(),
+                timestamp=datetime.datetime.now(datetime.timezone.utc),
             )
 
         # no prediction neccessary if the image is not a UPC Image
@@ -684,7 +684,7 @@ def extract_ingredients_job(
             model_name=ingredient_list.MODEL_NAME,
             model_version=ingredient_list.MODEL_VERSION,
             data=ingredient_prediction_data,
-            timestamp=datetime.datetime.utcnow(),
+            timestamp=datetime.datetime.now(datetime.timezone.utc),
             max_confidence=(
                 max(entity.score for entity in entities) if entities else None
             ),

scripts/insert_image_predictions.py

@@ -38,7 +38,7 @@ def insert_batch(
     model_version: str,
     server_type: ServerType,
 ) -> int:
-    timestamp = datetime.datetime.utcnow()
+    timestamp = datetime.datetime.now(datetime.timezone.utc)
     logger.info("Loading seen set...")
     seen_set = get_seen_set(server_type)
     logger.info("Seen set loaded")

tests/integration/insights/test_process_insights.py

@@ -1,4 +1,4 @@
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 
 import pytest
 
@@ -34,7 +34,7 @@ def _create_insight(**kwargs):
             "type": "category",
             "value_tag": "en:Salmons",
             "automatic_processing": True,
-            "process_after": datetime.utcnow() - timedelta(minutes=12),
+            "process_after": datetime.now(timezone.utc) - timedelta(minutes=12),
             "n_votes": 3,
             "server_type": DEFAULT_SERVER_TYPE.name,
         },
@@ -50,7 +50,7 @@ def test_process_insight_category(mocker, peewee_db):
     )
     mock = mocker.patch("robotoff.off.update_product")
     # a processed insight exists
-    date0 = datetime.utcnow() - timedelta(minutes=10)
+    date0 = datetime.now(timezone.utc) - timedelta(minutes=10)
     with peewee_db:
         id0, code0 = _create_insight(type="category", completed_at=date0, annotation=1)
         # an insight to be processed
@@ -63,7 +63,7 @@ def test_process_insight_category(mocker, peewee_db):
         # insight 1 processed
         insight = ProductInsight.get(id=id1)
     assert insight.completed_at is not None
-    assert insight.completed_at <= datetime.utcnow()
+    assert insight.completed_at <= datetime.now(timezone.utc)
     assert insight.annotation == 1
     # update_product calledfor item 1
     mock.assert_called_once_with(
@@ -93,7 +93,7 @@ def test_process_insight_category_existing(mocker, peewee_db):
     with peewee_db:
         insight = ProductInsight.get(id=id1)
     assert insight.completed_at is not None
-    assert insight.completed_at <= datetime.utcnow()
+    assert insight.completed_at <= datetime.now(timezone.utc)
     assert insight.annotation == 1
     # but update_product wasn't called
     mock.assert_not_called()
@@ -112,7 +112,7 @@ def test_process_insight_non_existing_product(mocker, peewee_db):
     with peewee_db:
         insight = ProductInsight.get(id=id1)
     assert insight.completed_at is not None
-    assert insight.completed_at <= datetime.utcnow()
+    assert insight.completed_at <= datetime.now(timezone.utc)
     assert insight.annotation == 1
     # but update_product wasn't called
     mock.assert_not_called()
@@ -136,9 +136,9 @@ def raise_for_salmons(params, *args, **kwargs):
         # add another insight that should pass
         id2, code2 = _create_insight(type="category", value_tag="en:Tuna")
     # run process
-    start = datetime.utcnow()
+    start = datetime.now(timezone.utc)
     process_insights()
-    end = datetime.utcnow()
+    end = datetime.now(timezone.utc)
 
     with peewee_db:
         # insight1 not marked processed
@@ -198,7 +198,7 @@ def test_process_insight_same_product(mocker, peewee_db):
         for id_ in [id1, id2, id3]:
             insight = ProductInsight.get(id=id_)
             assert insight.completed_at is not None
-            assert insight.completed_at <= datetime.utcnow()
+            assert insight.completed_at <= datetime.now(timezone.utc)
             assert insight.annotation == 1
     # update_product was called twice
     assert mock.call_count == 2

tests/integration/test_annotate_image.py

@@ -1,5 +1,5 @@
 import base64
-from datetime import datetime
+import datetime
 from typing import Any
 
 import falcon.testing
@@ -145,7 +145,7 @@ def test_logo_annotation_brand(client, peewee_db, monkeypatch, mocker, fake_taxo
             annotation_type=None,
         )
     mocker.patch("robotoff.app.api.enqueue_job", return_value=None)
-    start = datetime.utcnow()
+    start = datetime.datetime.now(datetime.timezone.utc)
     result = client.simulate_post(
         "/api/v1/images/logos/annotate",
         json={
@@ -154,7 +154,7 @@ def test_logo_annotation_brand(client, peewee_db, monkeypatch, mocker, fake_taxo
         },
         headers=_AUTH_HEADER,
     )
-    end = datetime.utcnow()
+    end = datetime.datetime.now(datetime.timezone.utc)
     assert result.status_code == 200
     assert result.json == {"annotated": 1}
 
@@ -180,7 +180,7 @@ def test_logo_annotation_label(client, peewee_db, monkeypatch, fake_taxonomy, mo
             barcode=barcode, source_image=source_image, annotation_type=None
         )
     mocker.patch("robotoff.app.api.enqueue_job", return_value=None)
-    start = datetime.utcnow()
+    start = datetime.datetime.now(datetime.timezone.utc)
     result = client.simulate_post(
         "/api/v1/images/logos/annotate",
         json={
@@ -191,7 +191,7 @@ def test_logo_annotation_label(client, peewee_db, monkeypatch, fake_taxonomy, mo
         },
         headers=_AUTH_HEADER,
     )
-    end = datetime.utcnow()
+    end = datetime.datetime.now(datetime.timezone.utc)
     assert result.status_code == 200
     assert result.json == {"annotated": 1}
     with peewee_db:

tests/integration/test_api.py

@@ -1,6 +1,6 @@
 import base64
+import datetime
 import uuid
-from datetime import datetime
 
 import pytest
 import requests
@@ -568,7 +568,7 @@ def test_annotate_insight_anonymous_then_authenticated(client, mocker, peewee_db
     # we still have the vote, but we also have an authenticated validation
     assert insight.items() > {"username": "a", "n_votes": 1, "annotation": 1}.items()
     assert insight.get("completed_at") is not None
-    assert insight.get("completed_at") <= datetime.utcnow()
+    assert insight.get("completed_at") <= datetime.datetime.now(datetime.timezone.utc)
     # update was done
     add_category.assert_called_once_with(
         DEFAULT_PRODUCT_ID,

tests/integration/test_logos.py

@@ -1,4 +1,4 @@
-from datetime import datetime
+import datetime
 
 import robotoff.insights.importer
 import robotoff.taxonomy
@@ -23,7 +23,12 @@ def _fake_store(monkeypatch, product_id: ProductIdentifier):
                     "code": product_id.barcode,  # needed to validate brand/label
                     # needed to validate image
                     "images": {
-                        "2": {"rev": 1, "uploaded_t": datetime.utcnow().timestamp()}
+                        "2": {
+                            "rev": 1,
+                            "uploaded_t": datetime.datetime.now(
+                                datetime.timezone.utc
+                            ).timestamp(),
+                        }
                     },
                 }
             )
@@ -55,13 +60,13 @@ def test_generate_insights_from_annotated_logos_job(peewee_db, monkeypatch, mock
             username=username,
         )
 
-    start = datetime.utcnow()
+    start = datetime.datetime.now(datetime.timezone.utc)
     generate_insights_from_annotated_logos_job(
         [ann.id],
         OFFAuthentication(username=username, password=username),
         server_type=DEFAULT_SERVER_TYPE,
     )
-    end = datetime.utcnow()
+    end = datetime.datetime.now(datetime.timezone.utc)
     # we generate a prediction
 
     with peewee_db:
@@ -115,4 +120,4 @@ def test_generate_insights_from_annotated_logos_job(peewee_db, monkeypatch, mock
     assert insight.annotation == 1
     assert insight.annotated_result == 2
     assert insight.server_type == DEFAULT_SERVER_TYPE.name
-    assert isinstance(insight.completed_at, datetime)
+    assert isinstance(insight.completed_at, datetime.datetime)

tests/unit/insights/test_importer.py

@@ -564,7 +564,7 @@ def get_insight_update(cls, candidates, references):
                             "images": {
                                 "8": {
                                     "uploaded_t": (
-                                        datetime.datetime.utcnow()
+                                        datetime.datetime.now(datetime.timezone.utc)
                                         - datetime.timedelta(days=600)
                                     ).timestamp()
                                 }