def test_to_dict(self, pipeline_config: PipelineConfig) -> None:
"""Test serialization of pipeline configuration."""
assert pipeline_config.to_dict() == {
"boots": [{"name": "Boot1", "configuration": {"some_parameter": -0.2}}],
"sieves": [{"name": "Sieve1", "configuration": {"flying_circus": 1969}}],
"steps": [{"name": "Step1", "configuration": {"guido_retirement": 2019}}],
"strides": [
{
"name": "Stride1",
"configuration": {
"linus": {
"residence": "oregon",
"children": 3,
"parents": ["nils", "anna"],
}
},
}
],
"wraps": [
{
"name": "Wrap1",
"configuration": {
"thoth": [2018, 2019],
"cities": ["Brno", "Bonn", "Boston", "Milan"],
},
}
],
}
def test_to_dict(self, pipeline_config: PipelineConfig) -> None:
"""Test conversion to a dict."""
report = Report(count=3, pipeline=pipeline_config)
project = flexmock()
project_dict = {"aresto momentum": "avada kedavra"}
project.should_receive("to_dict").with_args(
keep_thoth_section=True).and_return(
project_dict).twice() # In test and in the report.
product = Product(
project=project,
score=0.666,
justification=[{
"gryffindor": "le gladium leviosa"
}],
advised_runtime_environment=RuntimeEnvironment.from_dict(
{"python_version": "3.6"}),
)
report.add_product(product)
assert report.product_count() == 1
assert list(report.iter_products()) == [product]
assert report.to_dict() == {
"pipeline": pipeline_config.to_dict(),
"products": [product.to_dict()],
"stack_info": [],
"resolver_iterations": 0,
"accepted_final_states_count": 0,
"discarded_final_states_count": 0,
}
def test_to_dict(self, pipeline_config: PipelineConfig) -> None:
"""Test serialization of pipeline configuration."""
pipeline_dict = pipeline_config.to_dict()
assert pipeline_dict == {
"boots": [{
"configuration": {
"package_name": "flask",
"some_parameter": -0.2
},
"name": "Boot1",
"unit_run": False
}],
"pseudonyms": [{
"configuration": {
"another_parameter": 0.33,
"package_name": "tensorflow"
},
"name": "Pseudonym1",
"unit_run": False,
}],
"sieves": [{
"configuration": {
"flying_circus": 1969,
"package_name": "tensorflow"
},
"name": "Sieve1",
"unit_run": False,
}],
"steps": [{
"configuration": {
"guido_retirement": 2019,
"package_name": "tensorflow",
"multi_package_resolution": False,
},
"name": "Step1",
"unit_run": False,
}],
"strides": [{
"configuration": {
"linus": {
"children": 3,
"parents": ["nils", "anna"],
"residence": "oregon"
},
"package_name": None,
},
"name": "Stride1",
"unit_run": False,
}],
"wraps": [{
"configuration": {
"cities": ["Brno", "Bonn", "Boston", "Milan"],
"thoth": [2018, 2019],
"package_name": None,
},
"name": "Wrap1",
"unit_run": False,
}],
}
def test_to_dict_metadata(self, pipeline_config: PipelineConfig) -> None:
"""Test conversion to a dict with passed metadata."""
report = Report(count=3, pipeline=pipeline_config)
project = flexmock()
project_dict = {"aresto momentum": "avada kedavra"}
project.should_receive("to_dict").with_args(
keep_thoth_section=True).and_return(project_dict)
product = Product(
project=project,
score=0.666,
justification=[{
"gryffindor": "le gladium leviosa"
}],
advised_runtime_environment=RuntimeEnvironment.from_dict(
{"python_version": "3.6"}),
)
report.add_product(product)
stack_info = [{"type": "WARNING", "message": "Hello, metadata"}]
stack_info_metadata = {
"thoth.adviser": {
"stack_info": stack_info,
}
}
report.set_stack_info([{"foo": "bar"}])
assert "THOTH_ADVISER_METADATA" not in os.environ
os.environ["THOTH_ADVISER_METADATA"] = json.dumps(stack_info_metadata)
try:
assert report.product_count() == 1
assert list(report.iter_products()) == [product]
assert report.to_dict() == {
"pipeline": pipeline_config.to_dict(),
"products": [product.to_dict()],
"stack_info": list(chain(stack_info, report.stack_info)),
"resolver_iterations": 0,
"accepted_final_states_count": 0,
"discarded_final_states_count": 0,
}
except Exception:
os.environ.pop("THOTH_ADVISER_METADATA")
raise