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Move and re-arrange more tests
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@pipliggins
pipliggins committed Jan 31, 2025
1 parent 5e7afea commit 853f3a4
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340 changes: 297 additions & 43 deletions tests/test_adtl/test_get_value.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,41 +3,262 @@

import adtl.get_value as parser

RULE_SINGLE_FIELD = {"field": "diabetes_mhyn"}
RULE_SINGLE_FIELD_WITH_MAPPING = {
"field": "diabetes_mhyn",
"values": {"1": True, "2": False, "3": None},
}

ROW_CONCISE = {"mildliv": 0, "modliv": 2}
RULE_EXCLUDE = {
"combinedType": "list",
"fields": [{"field": "mildliv"}, {"field": "modliv"}],
}

LIVER_DISEASE = [
{
"field": "modliv",
"values": {"1": True, "0": False, "2": None},
"description": "Moderate liver disease",
},
{
"field": "mildliver",
"values": {"1": True, "0": False, "2": None},
"description": "Mild liver disease",
},
]

def test_exception_get_value_unhashed():
with pytest.raises(ValueError, match="Could not convert"):
parser.get_value_unhashed(
{"age_unit": "years", "age": "a"},
{"source_unit": {"field": "age_unit"}, "field": "age", "unit": "months"},
)
RULE_NON_SENSITIVE = {"field": "id"}
RULE_SENSITIVE = {"field": "id", "sensitive": True}

RULE_IGNOREMISSINGKEY = {
"field": "diabetes_mhyn",
"values": {"type 1": "E10", "type 2": "E11"}, # ICD-10 codes
"ignoreMissingKey": True,
}

def test_invalid_rule():
with pytest.raises(ValueError, match="Could not return value for"):
parser.get_value_unhashed({"age_unit": "years", "age": "a"}, {})
RULE_CASEINSENSITIVE = {
"field": "diabetes_mhyn",
"values": {"Type 1": "E10", "TYPE 2": "E11"}, # ICD-10 codes
"caseInsensitive": True,
}

ROW_CONDITIONAL = {"outcome_date": "2022-01-01", "outcome_type": 4}
RULE_CONDITIONAL_OK = {"field": "outcome_date", "if": {"outcome_type": 4}}
RULE_CONDITIONAL_FAIL = {"field": "outcome_date", "if": {"outcome_type": {"<": 4}}}

def test_missing_apply_function():
with pytest.raises(AttributeError, match="Error using a data transformation"):
parser.get_value_unhashed(
{"brthdtc": "2020-02-04", "dsstdat": "2023-04-06"},
{
"field": "brthdtc",
"apply": {"function": "undefinedFunction", "params": ["$dsstdat"]},
},
)
ROW_UNIT_MONTH = {"age": 18, "age_unit": "1"}
ROW_UNIT_YEAR = {"age": 18, "age_unit": "2"}
RULE_UNIT = {
"field": "age",
"unit": "years",
"source_unit": {"field": "age_unit", "values": {"1": "months", "2": "years"}},
}

with pytest.raises(AttributeError, match="Error using a data transformation"):
parser.get_value_unhashed(
{"brthdtc": "2020-02-04", "dsstdat": "2023-04-06"},
{"field": "brthdtc", "apply": {"function": "undefinedFunction"}},
)
ROW_DATE_BOTH_PRESENT = {"admission_date": "2020-05-05", "enrolment_date": "2020-05-19"}
ROW_DATE_ONLY_ONE = {"admission_date": "2020-05-05", "enrolment_date": ""}

RULE_DATE_MDY = {"field": "outcome_date", "source_date": "%d/%m/%Y", "date": "%m/%d/%Y"}
RULE_DATE_ISO = {"field": "outcome_date", "source_date": "%d/%m/%Y"}

RULE_FIELD_OPTION_SKIP = {
"field": "aidshiv_mhyn",
"values": {"1": True, "0": False},
"can_skip": True,
}


@pytest.mark.parametrize(
"row_rule,expected",
[
(({"diabetes_mhyn": "1"}, RULE_SINGLE_FIELD_WITH_MAPPING), True),
(({"diabetes_mhyn": "1"}, RULE_SINGLE_FIELD), 1),
(({}, "CONST"), "CONST"),
(({"id": "1"}, RULE_NON_SENSITIVE), 1),
(
({"id": "1"}, RULE_SENSITIVE),
"6b86b273ff34fce19d6b804eff5a3f5747ada4eaa22f1d49c01e52ddb7875b4b",
),
(
({"id": 1}, RULE_SENSITIVE),
"6b86b273ff34fce19d6b804eff5a3f5747ada4eaa22f1d49c01e52ddb7875b4b",
),
(({"diabetes_mhyn": "type 1"}, RULE_IGNOREMISSINGKEY), "E10"),
(({"diabetes_mhyn": "gestational"}, RULE_IGNOREMISSINGKEY), "gestational"),
(({"diabetes_mhyn": "type 2"}, RULE_CASEINSENSITIVE), "E11"),
(({"diabetes_mhyn": "TYPE 1"}, RULE_CASEINSENSITIVE), "E10"),
((ROW_CONDITIONAL, RULE_CONDITIONAL_OK), "2022-01-01"),
((ROW_CONDITIONAL, RULE_CONDITIONAL_FAIL), None),
((ROW_UNIT_MONTH, RULE_UNIT), 1.5),
((ROW_UNIT_YEAR, RULE_UNIT), 18),
(({"outcome_date": "02/05/2022"}, RULE_DATE_MDY), "05/02/2022"),
(({"outcome_date": "02/05/2022"}, RULE_DATE_ISO), "2022-05-02"),
(({"outcome_date": "2022-05-02"}, RULE_DATE_ISO), None),
(({"aidshiv": "1"}, RULE_FIELD_OPTION_SKIP), None),
(({"aidshiv_mhyn": "1"}, RULE_FIELD_OPTION_SKIP), True),
(({"aidshiv_mhyn": "2"}, RULE_FIELD_OPTION_SKIP), None),
],
)
def test_get_value_single_field(row_rule, expected):
row, rule = row_rule
assert parser.get_value(row, rule) == expected


RULE_COMBINED_TYPE_MIN = { # earliest date
"combinedType": "min",
"fields": [{"field": "admission_date"}, {"field": "enrolment_date"}],
}
RULE_COMBINED_TYPE_MAX = { # latest date
"combinedType": "max",
"fields": [{"field": "admission_date"}, {"field": "enrolment_date"}],
}

RULE_COMBINED_TYPE_ANY = {"combinedType": "any", "fields": LIVER_DISEASE}
RULE_COMBINED_TYPE_ALL = {"combinedType": "all", "fields": LIVER_DISEASE}
RULE_COMBINED_FIRST_NON_NULL = {
"combinedType": "firstNonNull",
"fields": [{"field": "first"}, {"field": "second"}],
}
RULE_COMBINED_TYPE_LIST = {"combinedType": "list", "fields": LIVER_DISEASE}
RULE_COMBINED_TYPE_LIST_PATTERN = {
"combinedType": "list",
"fields": [
{"fieldPattern": ".*liv.*", "values": {"1": True, "0": False, "2": None}}
],
}
RULE_COMBINED_TYPE_MIN = { # earliest date
"combinedType": "min",
"fields": [{"field": "admission_date"}, {"field": "enrolment_date"}],
}
RULE_COMBINED_TYPE_MAX = { # latest date
"combinedType": "max",
"fields": [{"field": "admission_date"}, {"field": "enrolment_date"}],
}
ANTIVIRAL_TYPE = [
{"field": "antiviral_cmtrt___1", "values": {"1": "Ribavirin"}},
{"field": "antiviral_cmtrt___2", "values": {"1": "Lopinavir/Ritonvir"}},
{"field": "antiviral_cmtrt___3", "values": {"1": "Interferon alpha"}},
{"field": "daily_antiviral_cmtrt___1", "values": {"1": "Ribavirin"}},
{"field": "daily_antiviral_cmtrt___2", "values": {"1": "Lopinavir/Ritonvir"}},
{"field": "daily_antiviral_cmtrt___3", "values": {"1": "Interferon alpha"}},
{"field": "overall_antiviral_cmtrt___1", "values": {"1": "Ribavirin"}},
{"field": "overall_antiviral_cmtrt___2", "values": {"1": "Lopinavir/Ritonvir"}},
{"field": "overall_antiviral_cmtrt___3", "values": {"1": "Interferon alpha"}},
]

RULE_COMBINED_TYPE_SET = {
"combinedType": "set",
"excludeWhen": "none",
"fields": ANTIVIRAL_TYPE,
}


@pytest.mark.parametrize(
"row_rule,expected",
[
(({"modliv": "1", "mildliver": "0"}, RULE_COMBINED_TYPE_ANY), True),
(({"modliv": "", "mildliver": ""}, RULE_COMBINED_TYPE_ANY), None),
(({"modliv": "1", "mildliver": "0"}, RULE_COMBINED_TYPE_ALL), False),
(({"modliv": "1", "mildliver": "0"}, RULE_COMBINED_TYPE_LIST), [True, False]),
(
({"modliv": "1", "mildliver": "0"}, RULE_COMBINED_TYPE_LIST_PATTERN),
[True, False],
),
(
(
{"modliv": "1", "mildliver": "3"},
{**RULE_COMBINED_TYPE_LIST_PATTERN, "excludeWhen": "none"},
),
[True],
),
(
({"modliv": "1", "mildliver": "3"}, RULE_COMBINED_TYPE_LIST_PATTERN),
[True, None],
),
(({"first": "1", "second": ""}, RULE_COMBINED_FIRST_NON_NULL), 1),
(({"first": "1", "second": "2"}, RULE_COMBINED_FIRST_NON_NULL), 1),
(({"first": "2", "second": "1"}, RULE_COMBINED_FIRST_NON_NULL), 2),
(({"first": "", "second": "3"}, RULE_COMBINED_FIRST_NON_NULL), 3),
(({"first": False, "second": True}, RULE_COMBINED_FIRST_NON_NULL), False),
(({"first": "", "second": False}, RULE_COMBINED_FIRST_NON_NULL), False),
((ROW_DATE_BOTH_PRESENT, RULE_COMBINED_TYPE_MIN), "2020-05-05"),
((ROW_DATE_BOTH_PRESENT, RULE_COMBINED_TYPE_MAX), "2020-05-19"),
((ROW_DATE_ONLY_ONE, RULE_COMBINED_TYPE_MIN), "2020-05-05"),
((ROW_DATE_ONLY_ONE, RULE_COMBINED_TYPE_MAX), "2020-05-05"),
(({"admission_date": "", "enrolment_date": ""}, RULE_COMBINED_TYPE_MIN), None),
(({"admission_date": "", "enrolment_date": ""}, RULE_COMBINED_TYPE_MAX), None),
(
(
{
"antiviral_cmtrt___1": "0",
"antiviral_cmtrt___2": "1",
"antiviral_cmtrt___3": "0",
"daily_antiviral_cmtrt___1": "0",
"daily_antiviral_cmtrt___2": "1",
"daily_antiviral_cmtrt___3": "1",
"overall_antiviral_cmtrt___1": "0",
"overall_antiviral_cmtrt___2": "0",
"overall_antiviral_cmtrt___3": "1",
},
RULE_COMBINED_TYPE_SET,
),
unordered(["Lopinavir/Ritonvir", "Interferon alpha"]),
),
(({"first": "", "second": ""}, RULE_COMBINED_FIRST_NON_NULL), None),
],
)
def test_get_value_combined_type(row_rule, expected):
row, rule = row_rule
assert parser.get_value(row, rule) == expected


@pytest.mark.parametrize(
"row_rule,expected",
[
(({"pathogen": "covid 19"}, {"pathogen": {"=~": ".*covid.*"}}), True),
(({"pathogen": "covid 19"}, {"pathogen": {"=~": ".*SARS-?CoV-?2.*"}}), False),
(
({"pathogen": "sars cov 2"}, {"pathogen": {"=~": ".*SARS[- ]CoV[- ]2.*"}}),
True,
),
(
({"pathogen": "sars-cov 2"}, {"pathogen": {"=~": ".*SARS[- ]CoV[- ]2.*"}}),
True,
),
(
({"pathogen": "coronavírus"}, {"pathogen": {"=~": ".*coronav[ií]rus.*"}}),
True,
),
((ROW_CONDITIONAL, {"outcome_type": 4}), True),
((ROW_CONDITIONAL, {"not": {"outcome_type": 4}}), False),
((ROW_CONDITIONAL, {"outcome_type": {"==": 4}}), True),
((ROW_CONDITIONAL, {"outcome_type": 3}), False),
((ROW_CONDITIONAL, {"outcome_type": {">": 2}}), True),
((ROW_CONDITIONAL, {"outcome_type": {"<": 10}}), True),
((ROW_CONDITIONAL, {"outcome_type": {"<=": 4}}), True),
((ROW_CONDITIONAL, {"outcome_type": {">=": 4}}), True),
((ROW_CONDITIONAL, {"outcome_type": {"<": 10}}), True),
((ROW_CONDITIONAL, {"outcome_type": {"!=": 4}}), False),
((ROW_CONDITIONAL, {"outcome_date": {"==": 2022}}), False),
((ROW_CONDITIONAL, {"outcome_date": 2022}), False),
(
(
ROW_CONDITIONAL,
{"any": [{"outcome_type": {">": 2}}, {"outcome_date": {"<": "2022"}}]},
),
True,
),
(
(
ROW_CONDITIONAL,
{"all": [{"outcome_type": {">": 2}}, {"outcome_date": {"<": "2022"}}]},
),
False,
),
],
)
def test_parse_if(row_rule, expected):
assert parser.parse_if(*row_rule) == expected


@pytest.mark.parametrize(
Expand All @@ -53,26 +274,6 @@ def test_list_exclude(rowrule, expected):
assert parser.get_combined_type(*rowrule) == expected


def test_invalid_list_exclude():
with pytest.raises(
ValueError,
match="excludeWhen rule should be 'none', 'false-like', or a list of values",
):
parser.get_combined_type(
{"modliv": 1, "mildliv": 2},
{
"combinedType": "list",
"fields": [{"field": "modliv"}, {"field": "mildliv"}],
"excludeWhen": 5,
},
)


def test_invalid_combined_type():
with pytest.raises(ValueError, match="Unknown"):
parser.get_combined_type(ROW_CONCISE, {"combinedType": "collage", "fields": []})


@pytest.mark.parametrize(
"test_input,expected",
[
Expand Down Expand Up @@ -128,3 +329,56 @@ def test_combinedtype_wordsubstituteset(test_row, test_combination, expected):
}

assert parser.get_combined_type(test_row, test_rule) == unordered(expected)


# test exceptions


def test_exception_get_value_unhashed():
with pytest.raises(ValueError, match="Could not convert"):
parser.get_value_unhashed(
{"age_unit": "years", "age": "a"},
{"source_unit": {"field": "age_unit"}, "field": "age", "unit": "months"},
)


def test_invalid_rule():
with pytest.raises(ValueError, match="Could not return value for"):
parser.get_value_unhashed({"age_unit": "years", "age": "a"}, {})


def test_missing_apply_function():
with pytest.raises(AttributeError, match="Error using a data transformation"):
parser.get_value_unhashed(
{"brthdtc": "2020-02-04", "dsstdat": "2023-04-06"},
{
"field": "brthdtc",
"apply": {"function": "undefinedFunction", "params": ["$dsstdat"]},
},
)

with pytest.raises(AttributeError, match="Error using a data transformation"):
parser.get_value_unhashed(
{"brthdtc": "2020-02-04", "dsstdat": "2023-04-06"},
{"field": "brthdtc", "apply": {"function": "undefinedFunction"}},
)


def test_invalid_list_exclude():
with pytest.raises(
ValueError,
match="excludeWhen rule should be 'none', 'false-like', or a list of values",
):
parser.get_combined_type(
{"modliv": 1, "mildliv": 2},
{
"combinedType": "list",
"fields": [{"field": "modliv"}, {"field": "mildliv"}],
"excludeWhen": 5,
},
)


def test_invalid_combined_type():
with pytest.raises(ValueError, match="Unknown"):
parser.get_combined_type(ROW_CONCISE, {"combinedType": "collage", "fields": []})
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