Ruff afternoon!

2 files changed, 18 insertions, 139 deletions

diff --git a/tests/models/precision/__init__.py b/tests/models/precision/__init__.py
index 8006fa3..e69de29 100644
--- a/tests/models/precision/__init__.py
+++ b/tests/models/precision/__init__.py
@@ -1,115 +0,0 @@
-survey_json = {
-    "cpi": "1.44",
-    "country_isos": "ca",
-    "language_isos": "eng",
-    "country_iso": "ca",
-    "language_iso": "eng",
-    "buyer_id": "7047",
-    "bid_loi": 1200,
-    "bid_ir": 0.45,
-    "source": "e",
-    "used_question_ids": ["age", "country_iso", "gender", "gender_1"],
-    "survey_id": "0000",
-    "group_id": "633473",
-    "status": "open",
-    "name": "beauty survey",
-    "survey_guid": "c7f375c5077d4c6c8209ff0b539d7183",
-    "category_id": "-1",
-    "global_conversion": None,
-    "desired_count": 96,
-    "achieved_count": 0,
-    "allowed_devices": "1,2,3",
-    "entry_link": "https://www.opinionetwork.com/survey/entry.aspx?mid=[%MID%]&project=633473&key=%%key%%",
-    "excluded_surveys": "470358,633286",
-    "quotas": [
-        {
-            "name": "25-34,Male,Quebec",
-            "id": "2324110",
-            "guid": "23b5760d24994bc08de451b3e62e77c7",
-            "status": "open",
-            "desired_count": 48,
-            "achieved_count": 0,
-            "termination_count": 0,
-            "overquota_count": 0,
-            "condition_hashes": ["b41e1a3", "bc89ee8", "4124366", "9f32c61"],
-        },
-        {
-            "name": "25-34,Female,Quebec",
-            "id": "2324111",
-            "guid": "0706f1a88d7e4f11ad847c03012e68d2",
-            "status": "open",
-            "desired_count": 48,
-            "achieved_count": 0,
-            "termination_count": 4,
-            "overquota_count": 0,
-            "condition_hashes": ["b41e1a3", "0cdc304", "500af2c", "9f32c61"],
-        },
-    ],
-    "conditions": {
-        "b41e1a3": {
-            "logical_operator": "OR",
-            "value_type": 1,
-            "negate": False,
-            "question_id": "country_iso",
-            "values": ["ca"],
-            "criterion_hash": "b41e1a3",
-            "value_len": 1,
-            "sizeof": 2,
-        },
-        "bc89ee8": {
-            "logical_operator": "OR",
-            "value_type": 1,
-            "negate": False,
-            "question_id": "gender",
-            "values": ["male"],
-            "criterion_hash": "bc89ee8",
-            "value_len": 1,
-            "sizeof": 4,
-        },
-        "4124366": {
-            "logical_operator": "OR",
-            "value_type": 1,
-            "negate": False,
-            "question_id": "gender_1",
-            "values": ["male"],
-            "criterion_hash": "4124366",
-            "value_len": 1,
-            "sizeof": 4,
-        },
-        "9f32c61": {
-            "logical_operator": "OR",
-            "value_type": 1,
-            "negate": False,
-            "question_id": "age",
-            "values": ["25", "26", "27", "28", "29", "30", "31", "32", "33", "34"],
-            "criterion_hash": "9f32c61",
-            "value_len": 10,
-            "sizeof": 20,
-        },
-        "0cdc304": {
-            "logical_operator": "OR",
-            "value_type": 1,
-            "negate": False,
-            "question_id": "gender",
-            "values": ["female"],
-            "criterion_hash": "0cdc304",
-            "value_len": 1,
-            "sizeof": 6,
-        },
-        "500af2c": {
-            "logical_operator": "OR",
-            "value_type": 1,
-            "negate": False,
-            "question_id": "gender_1",
-            "values": ["female"],
-            "criterion_hash": "500af2c",
-            "value_len": 1,
-            "sizeof": 6,
-        },
-    },
-    "expected_end_date": "2024-06-28T10:40:33.000000Z",
-    "created": None,
-    "updated": None,
-    "is_live": True,
-    "all_hashes": ["0cdc304", "b41e1a3", "9f32c61", "bc89ee8", "4124366", "500af2c"],
-}
diff --git a/tests/models/precision/test_survey.py b/tests/models/precision/test_survey.py
index ff2d6d1..4d671f2 100644
--- a/tests/models/precision/test_survey.py
+++ b/tests/models/precision/test_survey.py
@@ -1,10 +1,15 @@
-class TestPrecisionQuota:
+from __future__ import annotations
+
+from typing import Any
+
+from generalresearch.models.precision import PrecisionStatus
+from generalresearch.models.precision.survey import PrecisionSurvey
 
-    def test_quota_passes(self):
-        from generalresearch.models.precision.survey import PrecisionSurvey
-        from tests.models.precision import survey_json
 
-        s = PrecisionSurvey.model_validate(survey_json)
+class TestPrecisionQuota:
+
+    def test_quota_passes(self, precision_survey_json: dict[str, Any]):
+        s = PrecisionSurvey.model_validate(precision_survey_json)
         q = s.quotas[0]
         ce = {k: True for k in ["b41e1a3", "bc89ee8", "4124366", "9f32c61"]}
         assert q.matches(ce)
@@ -16,12 +21,9 @@ class TestPrecisionQuota:
         assert not q.matches(ce)
         assert not q.matches({})
 
-    def test_quota_passes_closed(self):
-        from generalresearch.models.precision import PrecisionStatus
-        from generalresearch.models.precision.survey import PrecisionSurvey
-        from tests.models.precision import survey_json
+    def test_quota_passes_closed(self, precision_survey_json: dict[str, Any]):
 
-        s = PrecisionSurvey.model_validate(survey_json)
+        s = PrecisionSurvey.model_validate(precision_survey_json)
         q = s.quotas[0]
         q.status = PrecisionStatus.CLOSED
         ce = {k: True for k in ["b41e1a3", "bc89ee8", "4124366", "9f32c61"]}
@@ -32,20 +34,15 @@ class TestPrecisionQuota:
 
 class TestPrecisionSurvey:
 
-    def test_passes(self):
-        from generalresearch.models.precision.survey import PrecisionSurvey
-        from tests.models.precision import survey_json
+    def test_passes(self, precision_survey_json: dict[str, Any]):
 
-        s = PrecisionSurvey.model_validate(survey_json)
+        s = PrecisionSurvey.model_validate(precision_survey_json)
         ce = {k: True for k in ["b41e1a3", "bc89ee8", "4124366", "9f32c61"]}
         assert s.determine_eligibility(ce)
 
-    def test_elig_closed_quota(self):
-        from generalresearch.models.precision import PrecisionStatus
-        from generalresearch.models.precision.survey import PrecisionSurvey
-        from tests.models.precision import survey_json
+    def test_elig_closed_quota(self, precision_survey_json: dict[str, Any]):
 
-        s = PrecisionSurvey.model_validate(survey_json)
+        s = PrecisionSurvey.model_validate(precision_survey_json)
         ce = {k: True for k in ["b41e1a3", "bc89ee8", "4124366", "9f32c61"]}
         q = s.quotas[0]
         q.status = PrecisionStatus.CLOSED
@@ -57,12 +54,9 @@ class TestPrecisionSurvey:
         # Now me match an open quota and dont match the closed quota, so we should be eligible
         assert s.determine_eligibility(ce)
 
-    def test_passes_sp(self):
-        from generalresearch.models.precision import PrecisionStatus
-        from generalresearch.models.precision.survey import PrecisionSurvey
-        from tests.models.precision import survey_json
+    def test_passes_sp(self, precision_survey_json: dict[str, Any]):
 
-        s = PrecisionSurvey.model_validate(survey_json)
+        s = PrecisionSurvey.model_validate(precision_survey_json)
         ce = {k: True for k in ["b41e1a3", "bc89ee8", "4124366", "9f32c61"]}
         passes, hashes = s.determine_eligibility_soft(ce)