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test_api_rules.py
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test_api_rules.py
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import pytest
from rubrix.server.commons.errors import EntityAlreadyExistsError
from rubrix.server.tasks.text_classification import (
CreateLabelingRule,
DatasetLabelingRulesMetricsSummary,
LabelingRule,
LabelingRuleMetricsSummary,
TextClassificationBulkData,
TextClassificationRecord,
)
from tests.server.test_helpers import client
def log_some_records(
dataset: str, annotation: str = None, multi_label: bool = False, delete: bool = True
):
if delete:
assert client.delete(f"/api/datasets/{dataset}").status_code == 200
record = {
"id": 0,
"inputs": {"text": "Esto es un ejemplo de texto"},
"metadata": {"field.one": 1, "field.two": 2},
"multi_label": multi_label,
}
if annotation:
record["annotation"] = {"agent": "test", "labels": [{"class": annotation}]}
response = client.post(
f"/api/datasets/{dataset}/TextClassification:bulk",
data=TextClassificationBulkData(
records=[
TextClassificationRecord(**record),
],
).json(by_alias=True),
)
assert response.status_code == 200
def test_dataset_without_rules():
dataset = "test_dataset_without_rules"
log_some_records(dataset)
response = client.get(f"/api/datasets/TextClassification/{dataset}/labeling/rules")
assert response.status_code == 200
assert len(response.json()) == 0
def test_dataset_update_rule():
dataset = "test_dataset_with_rules"
query = "a query"
log_some_records(dataset)
response = client.post(
f"/api/datasets/TextClassification/{dataset}/labeling/rules",
json=CreateLabelingRule(query=query, label="LALA").dict(),
)
assert response.status_code == 200
client.patch(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/{query}",
json={"label": "NEW Label"},
)
response = client.get(f"/api/datasets/TextClassification/{dataset}/labeling/rules")
rules = list(map(LabelingRule.parse_obj, response.json()))
assert len(rules) == 1
assert rules[0].label == "NEW Label"
assert rules[0].description is None
client.patch(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/{query}",
json={"label": "NEW Label", "description": "New description"},
)
response = client.get(f"/api/datasets/TextClassification/{dataset}/labeling/rules")
rules = list(map(LabelingRule.parse_obj, response.json()))
assert len(rules) == 1
assert rules[0].description == "New description"
def test_dataset_with_rules():
dataset = "test_dataset_with_rules"
log_some_records(dataset)
response = client.post(
f"/api/datasets/TextClassification/{dataset}/labeling/rules",
json=CreateLabelingRule(
query="a query", description="Description", label="LALA"
).dict(),
)
assert response.status_code == 200
created_rule = LabelingRule.parse_obj(response.json())
assert created_rule.query == "a query"
assert created_rule.label == "LALA"
assert created_rule.description == "Description"
assert created_rule.author == "rubrix"
response = client.get(f"/api/datasets/TextClassification/{dataset}/labeling/rules")
assert response.status_code == 200
rules = list(map(LabelingRule.parse_obj, response.json()))
assert len(rules) == 1
assert rules[0] == created_rule
def test_get_dataset_rule():
dataset = "test_get_dataset_rule"
log_some_records(dataset)
rule_query = "a query"
rule_label = "TEST"
rule_description = "Description"
response = client.post(
f"/api/datasets/TextClassification/{dataset}/labeling/rules",
json=CreateLabelingRule(
query=rule_query, label=rule_label, description=rule_description
).dict(),
)
assert response.status_code == 200
response = client.get(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/{rule_query}"
)
assert response.status_code == 200
rule = LabelingRule.parse_obj(response.json())
assert rule.query == rule_query
assert rule.label == rule_label
assert rule.description == rule_description
def test_delete_dataset_rules():
dataset = "test_delete_dataset_rules"
log_some_records(dataset)
response = client.post(
f"/api/datasets/TextClassification/{dataset}/labeling/rules",
json=CreateLabelingRule(
query="a query", label="TEST", description="Description"
).dict(),
)
assert response.status_code == 200
response = client.delete(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/{'a query'}"
)
assert response.status_code == 200
response = client.get(f"/api/datasets/TextClassification/{dataset}/labeling/rules")
assert response.status_code == 200
assert len(response.json()) == 0
def test_duplicated_dataset_rules():
dataset = "test_duplicated_dataset_rules"
log_some_records(dataset)
rule = CreateLabelingRule(query="a query", label="TEST")
response = client.post(
f"/api/datasets/TextClassification/{dataset}/labeling/rules",
json=rule.dict(),
)
assert response.status_code == 200
response = client.post(
f"/api/datasets/TextClassification/{dataset}/labeling/rules",
json=rule.dict(),
)
assert response.status_code == 409
assert response.json() == {
"detail": {
"code": "rubrix.api.errors::EntityAlreadyExistsError",
"params": {"name": "a query", "type": "LabelingRule"},
}
}
def test_rules_with_multi_label_dataset():
dataset = "test_rules_with_multi_label_dataset"
log_some_records(dataset, multi_label=True)
response = client.post(
f"/api/datasets/TextClassification/{dataset}/labeling/rules",
json=CreateLabelingRule(
query="a query", description="Description", label="LALA"
).dict(),
)
assert response.status_code == 400
assert response.json() == {
"detail": {
"code": "rubrix.api.errors::BadRequestError",
"params": {
"message": "Labeling rules are not supported for multi-label datasets"
},
}
}
def test_rule_metrics_with_missing_label():
dataset = "test_rule_metrics_with_missing_label"
log_some_records(dataset, annotation="OK")
response = client.get(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/a query/metrics"
)
assert response.status_code == 200, response.json()
assert response.json() == {
"coverage": 0.0,
"coverage_annotated": 0.0,
"correct": 0.0,
"incorrect": 0.0,
"total_records": 1,
"annotated_records": 1,
}
def test_rule_metrics_with_missing_label_for_stored_rule():
dataset = "test_rule_metrics_with_missing_label_for_stored_rule"
log_some_records(dataset, annotation="OK")
for query in ["ejemplo", "bad query"]:
client.post(
f"/api/datasets/TextClassification/{dataset}/labeling/rules",
json=CreateLabelingRule(
query=query, label="TEST", description="Description"
).dict(),
)
response = client.get(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/bad query/metrics"
)
assert response.status_code == 200
def test_create_rules_and_then_log():
dataset = "test_create_rules_and_then_log"
log_some_records(dataset, annotation="OK")
for query in ["ejemplo", "bad query"]:
client.post(
f"/api/datasets/TextClassification/{dataset}/labeling/rules",
json=CreateLabelingRule(
query=query, label="TEST", description="Description"
).dict(),
)
response = client.get(f"/api/datasets/TextClassification/{dataset}/labeling/rules")
rules = list(map(LabelingRule.parse_obj, response.json()))
assert len(rules) == 2
log_some_records(dataset, annotation="OK", delete=False)
response = client.get(f"/api/datasets/TextClassification/{dataset}/labeling/rules")
rules = list(map(LabelingRule.parse_obj, response.json()))
assert len(rules) == 2
def test_dataset_rules_metrics():
dataset = "test_dataset_rules_metrics"
log_some_records(dataset, annotation="OK")
for query in ["ejemplo", "bad query"]:
client.post(
f"/api/datasets/TextClassification/{dataset}/labeling/rules",
json=CreateLabelingRule(
query=query, label="TEST", description="Description"
).dict(),
)
response = client.get(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/metrics"
)
assert response.status_code == 200, response.json()
metrics = DatasetLabelingRulesMetricsSummary.parse_obj(response.json())
assert metrics.coverage == 1
assert metrics.coverage_annotated == 1
assert metrics.total_records == 1
assert metrics.annotated_records == 1
def test_dataset_rules_metrics_without_annotation():
dataset = "test_dataset_rules_metrics_without_annotation"
log_some_records(dataset)
for query in ["ejemplo", "bad query"]:
client.post(
f"/api/datasets/TextClassification/{dataset}/labeling/rules",
json=CreateLabelingRule(
query=query, label="TEST", description="Description"
).dict(),
)
response = client.get(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/metrics"
)
assert response.status_code == 200, response.json()
metrics = DatasetLabelingRulesMetricsSummary.parse_obj(response.json())
assert metrics.coverage == 1
assert metrics.total_records == 1
assert metrics.annotated_records == 0
assert metrics.coverage_annotated is None
def test_rule_metric():
dataset = "test_rule_metric"
log_some_records(dataset, annotation="OK")
response = client.get(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/ejemplo/metrics?label=TEST"
)
assert response.status_code == 200
metrics = LabelingRuleMetricsSummary.parse_obj(response.json())
assert metrics.total_records == 1
assert metrics.coverage == 1
assert metrics.coverage_annotated == 1
assert metrics.correct == 0
assert metrics.incorrect == 1
assert metrics.precision == 0
response = client.get(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/ejemplo/metrics?label=OK"
)
assert response.status_code == 200
metrics = LabelingRuleMetricsSummary.parse_obj(response.json())
assert metrics.correct == 1
assert metrics.incorrect == 0
assert metrics.precision == 1
response = client.get(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/ejemplo/metrics"
)
assert response.status_code == 200
metrics = LabelingRuleMetricsSummary.parse_obj(response.json())
assert metrics.correct == 0
assert metrics.incorrect == 0
assert metrics.precision is None
assert metrics.coverage_annotated == 1
response = client.get(
f"/api/datasets/TextClassification/{dataset}/labeling/rules/badd/metrics?label=OK"
)
assert response.status_code == 200
metrics = LabelingRuleMetricsSummary.parse_obj(response.json())
assert metrics.total_records == 1
assert metrics.coverage == 0
assert metrics.coverage_annotated == 0
assert metrics.correct == 0
assert metrics.incorrect == 0
assert metrics.precision is None
def test_search_records_with_uncovered_rules():
dataset = "test_search_records_with_uncovered_rules"
log_some_records(dataset, annotation="OK")
response = client.post(
f"/api/datasets/{dataset}/TextClassification:search",
)
assert len(response.json()["records"]) == 1
response = client.post(
f"/api/datasets/{dataset}/TextClassification:search",
json={"query": {"uncovered_by_rules": ["texto"]}},
)
assert len(response.json()["records"]) == 0