Added and updated tests

tests/conftest.py

@@ -1,4 +1,6 @@
 import pytest
+import json
+import yaml
 
 from pyenzyme.enzymeml.core.enzymemldocument import EnzymeMLDocument
 from pyenzyme.enzymeml.core.measurement import Measurement
@@ -17,16 +19,12 @@ def enzmldoc():
 
 @pytest.fixture
 def reaction():
-    return EnzymeReaction.fromJSON(
-        open("./tests/fixtures/reaction_object.json").read()
-    )
+    return EnzymeReaction.fromJSON(open("./tests/fixtures/reaction_object.json").read())
 
 
 @pytest.fixture
 def measurement():
-    return Measurement.fromJSON(
-        open("./tests/fixtures/measurement_object.json").read()
-    )
+    return Measurement.fromJSON(open("./tests/fixtures/measurement_object.json").read())
 
 
 @pytest.fixture
@@ -38,26 +36,31 @@ def measurement_data():
 
 @pytest.fixture
 def replicate():
-    return Replicate.fromJSON(
-        open("./tests/fixtures/replicate_object.json").read()
-    )
+    return Replicate.fromJSON(open("./tests/fixtures/replicate_object.json").read())
 
 
 @pytest.fixture
 def correct_model():
-    parameters = [
-        KineticParameter(name="x", value=10.0, unit="mmole / l")
-    ]
-    return KineticModel(
-        name="SomeModel", equation="s0 * x", parameters=parameters
-    )
+    parameters = [KineticParameter(name="x", value=10.0, unit="mmole / l")]
+    return KineticModel(name="SomeModel", equation="s0 * x", parameters=parameters)
 
 
 @pytest.fixture
 def faulty_model():
-    parameters = [
-        KineticParameter(name="x", value=10.0, unit="mmole / l")
-    ]
-    return KineticModel(
-        name="SomeModel", equation="s10 * x", parameters=parameters
-    )
+    parameters = [KineticParameter(name="x", value=10.0, unit="mmole / l")]
+    return KineticModel(name="SomeModel", equation="s10 * x", parameters=parameters)
+
+
+@pytest.fixture
+def always_pass():
+    return yaml.safe_load(open("./tests/fixtures/validator_always_passes.yaml"))
+
+
+@pytest.fixture
+def should_fail():
+    return yaml.safe_load(open("./tests/fixtures/validator_should_fail.yaml"))
+
+
+@pytest.fixture
+def template_example():
+    return json.loads(open("tests/fixtures/template_result.json").read())

tests/enzymeml/core/test_measurement.py

@@ -4,13 +4,19 @@
 
 
 class TestMeasurement:
-
     def test_content(self):
         """Tests consistency of content"""
 
         measurement = Measurement(
-            name="SomeMeasurement", temperature=100.0, temperature_unit="C", ph=7.0,
-            global_time=[1, 2, 3, 4], global_time_unit="s", id="m0", uri="URI", creator_id="a0"
+            name="SomeMeasurement",
+            temperature=100.0,
+            temperature_unit="C",
+            ph=7.0,
+            global_time=[1, 2, 3, 4],
+            global_time_unit="s",
+            id="m0",
+            uri="URI",
+            creator_id="a0",
         )
 
         assert measurement.name == "SomeMeasurement"
@@ -29,9 +35,7 @@ def test_content(self):
     def test_defaults(self):
         """Test default values"""
 
-        measurement = Measurement(
-            name="SomeMeasurement"
-        )
+        measurement = Measurement(name="SomeMeasurement")
 
         assert not measurement.temperature
         assert not measurement.temperature_unit
@@ -62,12 +66,12 @@ def test_data_export(self, measurement):
 
         # Construct expected DataFrame
         expected_protein = {
-            'p0': {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0},
-            'time': {0: 1.0, 1: 2.0, 2: 3.0, 3: 4.0},
+            "p0": {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0},
+            "time": {0: 1.0, 1: 2.0, 2: 3.0, 3: 4.0},
         }
         expected_reactant = {
-            's0': {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0},
-            'time': {0: 1.0, 1: 2.0, 2: 3.0, 3: 4.0},
+            "s0": {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0},
+            "time": {0: 1.0, 1: 2.0, 2: 3.0, 3: 4.0},
         }
 
         assert data["reactants"]["data"].to_dict() == expected_reactant
@@ -99,8 +103,8 @@ def test_data_export_specific_species(self, measurement):
         # Test case with list as argument
         data = measurement.exportData(species_ids=["s0"])
         expected_reactant = {
-            's0': {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0},
-            'time': {0: 1.0, 1: 2.0, 2: 3.0, 3: 4.0}
+            "s0": {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0},
+            "time": {0: 1.0, 1: 2.0, 2: 3.0, 3: 4.0},
         }
 
         assert data["reactants"]["initConc"] == {"s0": (10.0, "mmole / l")}
@@ -113,8 +117,8 @@ def test_data_export_specific_species(self, measurement):
         data = measurement.exportData(species_ids="s0")
         init_conc = data["reactants"]["initConc"]
         expected_reactant = {
-            's0': {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0},
-            'time': {0: 1.0, 1: 2.0, 2: 3.0, 3: 4.0}
+            "s0": {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0},
+            "time": {0: 1.0, 1: 2.0, 2: 3.0, 3: 4.0},
         }
 
         assert data["reactants"]["initConc"] == {"s0": (10.0, "mmole / l")}
@@ -143,7 +147,9 @@ def test_add_replicates(self, measurement, replicate, enzmldoc):
         measurement.addReplicates([replicate, replicate2], enzmldoc)
 
         assert measurement.species_dict["reactants"]["s0"].replicates == [
-            replicate, replicate2]
+            replicate,
+            replicate2,
+        ]
 
     def test_add_data(self, measurement, replicate):
         """Tests the addition of data"""

tests/enzymeml/tools/test_templatereader.py

@@ -0,0 +1,15 @@
+import json
+
+from pyenzyme.enzymeml.core.enzymemldocument import EnzymeMLDocument
+
+
+class TestTemplateReader:
+    def test_template_conversion(self, template_example):
+        """Tests the conversion of the EnzymeML Spreadsheet template"""
+
+        # Convert the template fixture
+        enzmldoc = EnzymeMLDocument.fromTemplate(
+            "./tests/fixtures/EnzymeML_Template_Example.xlsm"
+        )
+
+        assert json.loads(enzmldoc.json()) == template_example

tests/enzymeml/tools/test_validator.py

@@ -0,0 +1,57 @@
+import os
+import yaml
+import pandas as pd
+
+from pyenzyme.enzymeml.tools.validator import EnzymeMLValidator
+from pyenzyme.enzymeml.core.enzymemldocument import EnzymeMLDocument
+
+
+class TestValidation:
+    def test_positive_validation(self, enzmldoc, always_pass):
+        """Tests positive validation with a non-restrictive validation YAML"""
+
+        # Set up validator
+        validator = EnzymeMLValidator(scheme=always_pass)
+
+        # Perform validation
+        report, check = validator.validate(enzmldoc)
+
+        assert check is True
+        assert not report, "Report is not empty"
+
+    def test_negative_validation(self, enzmldoc, should_fail):
+        """Tests negative validation with a restrictive validation YAML"""
+
+        # Set up validator
+        validator = EnzymeMLValidator(scheme=should_fail)
+
+        # Perform validation and assertit failed
+        report, check = validator.validate(enzmldoc)
+
+        assert check is False
+        assert report, "Report is empty"
+
+    def test_creation_to_conversion(self):
+        """Tests the complete path from EnzymeMLDocument class over Spreadhseet back to dict structure"""
+
+        # Generate sheet
+        sheet_path = "./tests/fixtures/"
+        sheet_loc = os.path.join(sheet_path, "EnzymeML_Validation_Template.xlsx")
+        EnzymeMLValidator.generateValidationSpreadsheet(path=sheet_path)
+
+        assert pd.read_excel(sheet_loc).to_dict()
+
+        # Manually create collection and compare it
+        # to the one that will be drawn from the sheet
+        collection = EnzymeMLValidator(scheme={})._get_cls_annotations(
+            EnzymeMLDocument, level="document"
+        )[0]
+        expected = yaml.safe_load(
+            EnzymeMLValidator._dump_validation_template_yaml(collection)
+        )
+        converted = yaml.safe_load(EnzymeMLValidator.convertSheetToYAML(sheet_loc))
+
+        assert converted == expected, "Conversion from spreadsheet is inconsistent"
+
+        # Remove everything
+        os.remove(sheet_loc)