def run(self, state: State) -> None:
"""Add release information to justification for selected packages."""
justification_addition = []
for resolved_package_tuple in state.resolved_dependencies.values():
conf_matched = self._conf_map.get(resolved_package_tuple[0])
if not conf_matched:
continue
version = conf_matched["package_version"].get("version")
if version is not None and resolved_package_tuple[
1] not in SpecifierSet(version):
continue
index_url = conf_matched["package_version"].get("index_url")
if index_url is not None and resolved_package_tuple[2] != index_url:
continue
justification_addition.append({
"type":
"INFO",
"message":
f"Release notes for package {resolved_package_tuple[0]!r}",
"link":
self._construct_release_notes_url(
organization=conf_matched["organization"],
repository=conf_matched["repository"],
tag_version_prefix=conf_matched.get("tag_version_prefix"),
locked_version=resolved_package_tuple[1],
),
})
state.add_justification(justification_addition)
def test_add_state_order_single(self) -> None:
"""Test adding states to beam and order during addition when score is same - iteration is relevant."""
beam = Beam(width=1)
state01 = State(
score=0.0,
latest_version_offset=0,
iteration=1,
iteration_states_added=0,
)
state01.add_justification([{"state": "01"}])
beam.add_state(state01)
state02 = State(
score=0.0,
latest_version_offset=0,
iteration=0,
iteration_states_added=0,
)
state02.add_justification([{"state": "02"}])
beam.add_state(state02)
assert list(beam.iter_states()) == [state01]
assert list(beam.iter_states_sorted(reverse=True)) == [state01]
assert list(beam.iter_states_sorted(reverse=False)) == [state01]
def run(self, state: State) -> None:
"""Add release information to justification for selected packages."""
justification_addition = []
for resolved_package_tuple in state.resolved_dependencies.values():
conf_package_version = self.configuration["package_version"]
if not conf_package_version or resolved_package_tuple[
0] != conf_package_version["name"]:
continue
version = conf_package_version.get("version")
if version is not None and resolved_package_tuple[
1] not in SpecifierSet(version):
continue
develop = conf_package_version.get("develop")
if develop is not None:
package_version = self.context.get_package_version(
resolved_package_tuple)
if not package_version:
# This is a programming error as the give dependency has to be registered in the context.
_LOGGER.error(
"No matching package version for %r registered in the context",
resolved_package_tuple)
continue
if package_version.develop != develop:
continue
index_url = conf_package_version.get("index_url")
if not self._index_url_check(index_url, resolved_package_tuple[2]):
continue
if self._configuration["prescription"]["run"]:
# Can happen if prescription states criteria that match multiple times. We add
# justification only once in such cases.
continue
self._configuration["prescription"]["run"] = True
release_notes_conf = self.configuration["release_notes"]
justification_addition.append({
"type":
"INFO",
"message":
f"Release notes for package {resolved_package_tuple[0]!r}",
"link":
self._construct_release_notes_url(
organization=release_notes_conf["organization"],
repository=release_notes_conf["repository"],
tag_version_prefix=release_notes_conf.get(
"tag_version_prefix"),
locked_version=resolved_package_tuple[1],
),
"package_name":
resolved_package_tuple[0],
})
state.add_justification(justification_addition)
def test_justification(self, final_state: State) -> None:
"""Test manipulation with state justification."""
assert final_state.justification == [{"foo": "bar"}]
final_state.add_justification([{"hello": "thoth"}])
assert final_state.justification == [{
"foo": "bar"
}, {
"hello": "thoth"
}]
def final_state() -> State:
"""A fixture for a final state."""
state = State(
score=0.5,
resolved_dependencies=OrderedDict(
{"daiquiri": ("daiquiri", "1.6.0", "https://pypi.org/simple")}),
unresolved_dependencies=OrderedDict(),
advised_runtime_environment=None,
)
state.add_justification([{"foo": "bar"}])
return state
def final_state() -> State: # noqa: D401
"""A fixture for a final state."""
state = State(
score=0.5,
resolved_dependencies={
"daiquiri": ("daiquiri", "1.6.0", "https://pypi.org/simple")
},
unresolved_dependencies={},
advised_runtime_environment=None,
)
state.add_justification(AdviserTestCase.JUSTIFICATION_SAMPLE_1)
return state
def test_run_justification_noop(self) -> None:
"""Test no operation when justification is present."""
state = State()
assert not state.justification
state.add_justification([{"type": "INFO", "message": "Foo bar"}])
unit = NoObservationWrap()
unit.run(state)
assert len(state.justification) == 1
assert set(state.justification[0].keys()) == {"type", "message"}
def run(self, state: State) -> None:
"""Run main entry-point for wrap units to filter and score packages."""
if not self._run_state(state):
return None
justification = self.run_prescription.get("justification")
if justification:
state.add_justification(justification)
advised_manifest_changes = self.run_prescription.get(
"advised_manifest_changes")
if advised_manifest_changes:
state.advised_manifest_changes.append(advised_manifest_changes)
self._run_base()
def state() -> State:
"""A fixture for a non-final state."""
state = State(
score=0.1,
unresolved_dependencies=OrderedDict(
{"flask": ("flask", "1.1.1", "https://pypi.org/simple")}
),
resolved_dependencies=OrderedDict(
{"hexsticker": ("hexsticker", "1.0.0", "https://pypi.org/simple")}
),
advised_runtime_environment=RuntimeEnvironment.from_dict(
{"python_version": "3.6"}
),
)
state.add_justification([{"foo": "bar"}, {"bar": "baz"}])
return state
def _get_state() -> State:
"""Create a fixture for a non-final state."""
unresolved_dependency = ("flask", "1.1.1", "https://pypi.org/simple")
unresolved_dependencies = {
id(unresolved_dependency): unresolved_dependency
}
state = State(
score=0.1,
unresolved_dependencies={"flask": unresolved_dependencies},
resolved_dependencies={
"hexsticker": ("hexsticker", "1.0.0", "https://pypi.org/simple")
},
advised_runtime_environment=RuntimeEnvironment.from_dict(
{"python_version": "3.6"}),
)
state.add_justification(AdviserTestCase.JUSTIFICATION_SAMPLE_1)
return state
def test_add_state_order_single(self) -> None:
"""Test adding states to beam and order during addition when score is same - iteration is relevant."""
beam = Beam(width=1)
state01 = State(
score=0.0,
iteration=1,
)
state01.add_justification(self.JUSTIFICATION_SAMPLE_1)
beam.add_state(state01)
state02 = State(
score=0.0,
iteration=0,
)
state02.add_justification(self.JUSTIFICATION_SAMPLE_2)
beam.add_state(state02)
assert list(beam.iter_states()) == [state01]
assert list(beam.iter_states_sorted(reverse=True)) == [state01]
assert list(beam.iter_states_sorted(reverse=False)) == [state01]
def run(self, state: State) -> None:
"""Run main entry-point for wrap units to filter and score packages."""
if not self._run_state(state):
return None
prescription_conf = self._configuration["prescription"]
if not prescription_conf["run"]:
justification = self.run_prescription.get("justification")
if justification:
state.add_justification(justification)
advised_manifest_changes = self.run_prescription.get(
"advised_manifest_changes")
if advised_manifest_changes:
state.advised_manifest_changes.append(advised_manifest_changes)
try:
self._run_base()
finally:
prescription_conf["run"] = True
def test_add_state_order_multi(self) -> None:
"""Test adding states to beam and order during addition when score is same."""
beam = Beam(width=2)
state01 = State(score=0.0, iteration=0, iteration_states_added=0)
state01.add_justification([{"state": "01"}])
beam.add_state(state01)
state02 = State(score=0.0, iteration=0, iteration_states_added=1)
state02.add_justification([{"state": "02"}])
beam.add_state(state02)
state03 = State(score=0.0, iteration=1, iteration_states_added=0)
state03.add_justification([{"state": "03"}])
beam.add_state(state03)
state04 = State(score=0.0, iteration=1, iteration_states_added=1)
state04.add_justification([{"state": "04"}])
beam.add_state(state04)
assert list(beam.iter_states_sorted()) == [state03, state04]
assert list(beam.iter_states_sorted(reverse=True)) == [state03, state04]
assert list(beam.iter_states_sorted(reverse=False)) == [state04, state03]
def test_add_state_order_multi(self) -> None:
"""Test adding states to beam and order during addition when score is same."""
beam = Beam(width=2)
state01 = State(score=0.0)
state01.add_justification(self.JUSTIFICATION_SAMPLE_1)
beam.add_state(state01)
state02 = State(score=0.0)
state02.add_justification(self.JUSTIFICATION_SAMPLE_2)
beam.add_state(state02)
state03 = State(score=0.0)
state03.add_justification(self.JUSTIFICATION_SAMPLE_3)
beam.add_state(state03)
assert list(beam.iter_states_sorted()) == [state01, state02]
assert list(beam.iter_states_sorted(reverse=True)) == [state01, state02]
assert list(beam.iter_states_sorted(reverse=False)) == [state01, state02]
def test_justification(self, final_state: State) -> None:
"""Test manipulation with state justification."""
assert final_state.justification == self.JUSTIFICATION_SAMPLE_1
final_state.add_justification(self.JUSTIFICATION_SAMPLE_2)
assert final_state.justification == list(
chain(self.JUSTIFICATION_SAMPLE_1, self.JUSTIFICATION_SAMPLE_2))
def test_from_final_state(self, context: Context) -> None:
"""Test instantiating product from a final state."""
state = State(
score=0.5,
resolved_dependencies=OrderedDict(
{
"daiquiri": ("daiquiri", "1.6.0", "https://pypi.org/simple"),
"numpy": ("numpy", "1.17.4", "https://pypi.org/simple"),
"tensorflow": ("tensorflow", "2.0.0", "https://pypi.org/simple"),
}
),
unresolved_dependencies=OrderedDict(),
advised_runtime_environment=RuntimeEnvironment.from_dict(
{"python_version": "3.6"}
),
)
state.add_justification([{"foo": "bar"}])
pypi = Source("https://pypi.org/simple")
pv_daiquiri_locked = PackageVersion(
name="daiquiri", version="==1.6.0", index=pypi, develop=False
)
pv_numpy_locked = PackageVersion(
name="numpy", version="==1.17.4", index=pypi, develop=False
)
pv_tensorflow_locked = PackageVersion(
name="tensorflow", version="==2.0.0", index=pypi, develop=False
)
context.should_receive("get_package_version").with_args(
("daiquiri", "1.6.0", "https://pypi.org/simple"), graceful=False
).and_return(pv_daiquiri_locked).ordered()
context.graph.should_receive("get_python_package_hashes_sha256").with_args(
"daiquiri", "1.6.0", "https://pypi.org/simple"
).and_return(["000"]).ordered()
context.should_receive("get_package_version").with_args(
("numpy", "1.17.4", "https://pypi.org/simple"), graceful=False
).and_return(pv_numpy_locked).ordered()
context.graph.should_receive("get_python_package_hashes_sha256").with_args(
"numpy", "1.17.4", "https://pypi.org/simple"
).and_return(["111"]).ordered()
context.should_receive("get_package_version").with_args(
("tensorflow", "2.0.0", "https://pypi.org/simple"), graceful=False
).and_return(pv_tensorflow_locked).ordered()
context.graph.should_receive("get_python_package_hashes_sha256").with_args(
"tensorflow", "2.0.0", "https://pypi.org/simple"
).and_return(["222"]).ordered()
pv_daiquiri = PackageVersion(
name="daiquiri", version="*", index=pypi, develop=False
)
pv_tensorflow = PackageVersion(
name="tensorflow", version=">=2.0.0", index=pypi, develop=False
)
project = flexmock()
project.should_receive("iter_dependencies").with_args(
with_devel=True
).and_return([pv_daiquiri, pv_tensorflow]).once()
context.project = project
context.dependencies = {
"daiquiri": {
("daiquiri", "1.6.0", "https://pypi.org/simple"): set(),
},
"numpy": {
("numpy", "1.17.4", "https://pypi.org/simple"): set()
},
"tensorflow": {
("tensorflow", "2.0.0", "https://pypi.org/simple"): {
("numpy", "1.17.4", "https://pypi.org/simple")
}
},
}
context.dependents = {
"daiquiri": {
("daiquiri", "1.6.0", "https://pypi.org/simple"): set(),
},
"numpy": {
("numpy", "1.17.4", "https://pypi.org/simple"): {
(("tensorflow", "2.0.0", "https://pypi.org/simple"), "fedora", "31", "3.7")
}
},
"tensorflow": {
("tensorflow", "2.0.0", "https://pypi.org/simple"): set()
},
}
context.graph.should_receive("get_python_environment_marker").with_args(
"tensorflow",
"2.0.0",
"https://pypi.org/simple",
dependency_name="numpy",
dependency_version="1.17.4",
os_name="fedora",
os_version="31",
python_version="3.7",
).and_return("python_version >= '3.7'").once()
product = Product.from_final_state(state=state, context=context)
assert product.score == state.score
assert product.justification == state.justification
assert product.advised_runtime_environment == state.advised_runtime_environment
assert product.project.to_dict() == {
"requirements": {
"packages": {
"daiquiri": {"index": "pypi-org", "version": "*"},
"tensorflow": {"index": "pypi-org", "version": ">=2.0.0"},
},
"dev-packages": {},
"source": [
{
"url": "https://pypi.org/simple",
"verify_ssl": True,
"name": "pypi-org",
}
],
},
"requirements_locked": {
"_meta": {
"sources": [
{
"url": "https://pypi.org/simple",
"verify_ssl": True,
"name": "pypi-org",
}
],
"requires": {},
"hash": {
"sha256": "c3a2f42932b6e5cd30f5664b11eda605f5fbd672f1b88729561d0d3edd10b5d9"
},
"pipfile-spec": 6,
},
"default": {
"daiquiri": {
"version": "==1.6.0",
"hashes": ["sha256:000"],
"index": "pypi-org",
},
"numpy": {
"version": "==1.17.4",
"hashes": ["sha256:111"],
"index": "pypi-org",
"markers": "python_version >= '3.7'",
},
"tensorflow": {
"version": "==2.0.0",
"hashes": ["sha256:222"],
"index": "pypi-org",
},
},
"develop": {},
},
"runtime_environment": {
"hardware": {"cpu_family": None, "cpu_model": None},
"operating_system": {"name": None, "version": None},
"python_version": None,
"cuda_version": None,
"name": None,
},
}
def test_from_final_state(self, context: Context) -> None:
"""Test instantiating product from a final state."""
state = State(
score=0.5,
resolved_dependencies={
"daiquiri": ("daiquiri", "1.6.0", "https://pypi.org/simple"),
"numpy": ("numpy", "1.17.4", "https://pypi.org/simple"),
"tensorflow": ("tensorflow", "2.0.0", "https://pypi.org/simple"),
},
unresolved_dependencies={},
advised_runtime_environment=RuntimeEnvironment.from_dict({"python_version": "3.6"}),
)
state.add_justification(self.JUSTIFICATION_SAMPLE_1)
pypi = Source("https://pypi.org/simple")
pv_daiquiri_locked = PackageVersion(name="daiquiri", version="==1.6.0", index=pypi, develop=False)
pv_numpy_locked = PackageVersion(name="numpy", version="==1.17.4", index=pypi, develop=False)
pv_tensorflow_locked = PackageVersion(name="tensorflow", version="==2.0.0", index=pypi, develop=False)
context.should_receive("get_package_version").with_args(
("daiquiri", "1.6.0", "https://pypi.org/simple"), graceful=False
).and_return(pv_daiquiri_locked).ordered()
context.graph.should_receive("get_python_package_hashes_sha256").with_args(
"daiquiri", "1.6.0", "https://pypi.org/simple"
).and_return(["000"]).ordered()
context.should_receive("get_package_version").with_args(
("numpy", "1.17.4", "https://pypi.org/simple"), graceful=False
).and_return(pv_numpy_locked).ordered()
context.graph.should_receive("get_python_package_hashes_sha256").with_args(
"numpy", "1.17.4", "https://pypi.org/simple"
).and_return(["111"]).ordered()
context.should_receive("get_package_version").with_args(
("tensorflow", "2.0.0", "https://pypi.org/simple"), graceful=False
).and_return(pv_tensorflow_locked).ordered()
context.graph.should_receive("get_python_package_hashes_sha256").with_args(
"tensorflow", "2.0.0", "https://pypi.org/simple"
).and_return(["222"]).ordered()
pv_daiquiri = PackageVersion(name="daiquiri", version="*", index=pypi, develop=False)
pv_tensorflow = PackageVersion(name="tensorflow", version=">=2.0.0", index=pypi, develop=False)
project = flexmock(
pipfile=Pipfile.from_string(self._PIPFILE),
runtime_environment=RuntimeEnvironment.from_dict({"operating_system": {"name": "rhel"}}),
)
project.should_receive("iter_dependencies").with_args(with_devel=True).and_return(
[pv_daiquiri, pv_tensorflow]
).once()
context.project = project
context.dependencies = {
"daiquiri": {
("daiquiri", "1.6.0", "https://pypi.org/simple"): set(),
},
"numpy": {("numpy", "1.17.4", "https://pypi.org/simple"): set()},
"tensorflow": {
("tensorflow", "2.0.0", "https://pypi.org/simple"): {("numpy", "1.17.4", "https://pypi.org/simple")}
},
}
context.dependents = {
"daiquiri": {
("daiquiri", "1.6.0", "https://pypi.org/simple"): set(),
},
"numpy": {
("numpy", "1.17.4", "https://pypi.org/simple"): {
(
("tensorflow", "2.0.0", "https://pypi.org/simple"),
"fedora",
"31",
"3.7",
)
}
},
"tensorflow": {("tensorflow", "2.0.0", "https://pypi.org/simple"): set()},
}
context.graph.should_receive("get_python_environment_marker").with_args(
"tensorflow",
"2.0.0",
"https://pypi.org/simple",
dependency_name="numpy",
dependency_version="1.17.4",
os_name="fedora",
os_version="31",
python_version="3.7",
marker_evaluation_result=True,
).and_return("python_version >= '3.7'").once()
assert "THOTH_ADVISER_METADATA" not in os.environ
metadata_justification = {"thoth.adviser": {"justification": [{"bar": "baz"}]}}
os.environ["THOTH_ADVISER_METADATA"] = json.dumps(metadata_justification)
try:
product = Product.from_final_state(state=state, context=context)
finally:
os.environ.pop("THOTH_ADVISER_METADATA")
assert product.score == state.score
assert product.justification == list(
chain(metadata_justification["thoth.adviser"]["justification"], state.justification)
)
assert product.advised_runtime_environment == state.advised_runtime_environment
assert product.project.to_dict() == {
"constraints": [],
"requirements": {
"packages": {
"daiquiri": {"index": "pypi-org-simple", "version": "*"},
"tensorflow": {"index": "pypi-org-simple", "version": ">=2.0.0"},
},
"dev-packages": {},
"requires": {"python_version": "3.7"},
"source": [
{
"url": "https://pypi.org/simple",
"verify_ssl": True,
"name": "pypi-org",
},
{
"url": "https://pypi.org/simple",
"verify_ssl": True,
"name": "pypi-org-simple",
},
],
"thoth": {
"allow_prereleases": {"black": True},
},
},
"requirements_locked": {
"_meta": {
"sources": [
{"name": "pypi-org", "url": "https://pypi.org/simple", "verify_ssl": True},
{
"url": "https://pypi.org/simple",
"verify_ssl": True,
"name": "pypi-org-simple",
},
],
"requires": {"python_version": "3.7"},
"hash": {"sha256": "6cc8365e799b949fb6cc564cea2d8e0e8a782ab676a006e65abbe14621b93381"},
"pipfile-spec": 6,
},
"default": {
"daiquiri": {
"version": "==1.6.0",
"hashes": ["sha256:000"],
"index": "pypi-org-simple",
},
"numpy": {
"version": "==1.17.4",
"hashes": ["sha256:111"],
"index": "pypi-org-simple",
"markers": "python_version >= '3.7'",
},
"tensorflow": {
"version": "==2.0.0",
"hashes": ["sha256:222"],
"index": "pypi-org-simple",
},
},
"develop": {},
},
"runtime_environment": {
"hardware": {"cpu_family": None, "cpu_model": None, "gpu_model": None},
"operating_system": {"name": "rhel", "version": None},
"python_version": None,
"cuda_version": None,
"labels": None,
"cudnn_version": None,
"name": None,
"platform": None,
"base_image": None,
"mkl_version": None,
"openblas_version": None,
"openmpi_version": None,
"recommendation_type": None,
},
}
def test_from_final_state(self, context: Context) -> None:
"""Test instantiating product from a final state."""
state = State(
score=0.5,
resolved_dependencies={
"daiquiri": ("daiquiri", "1.6.0", "https://pypi.org/simple"),
"numpy": ("numpy", "1.17.4", "https://pypi.org/simple"),
"tensorflow":
("tensorflow", "2.0.0", "https://pypi.org/simple"),
},
unresolved_dependencies={},
advised_runtime_environment=RuntimeEnvironment.from_dict(
{"python_version": "3.6"}),
)
state.add_justification(self.JUSTIFICATION_SAMPLE_1)
pypi = Source("https://pypi.org/simple")
pv_daiquiri_locked = PackageVersion(name="daiquiri",
version="==1.6.0",
index=pypi,
develop=False)
pv_numpy_locked = PackageVersion(name="numpy",
version="==1.17.4",
index=pypi,
develop=False)
pv_tensorflow_locked = PackageVersion(name="tensorflow",
version="==2.0.0",
index=pypi,
develop=False)
context.should_receive("get_package_version").with_args(
("daiquiri", "1.6.0", "https://pypi.org/simple"),
graceful=False).and_return(pv_daiquiri_locked).ordered()
context.graph.should_receive(
"get_python_package_hashes_sha256").with_args(
"daiquiri", "1.6.0",
"https://pypi.org/simple").and_return(["000"]).ordered()
context.should_receive("get_package_version").with_args(
("numpy", "1.17.4", "https://pypi.org/simple"),
graceful=False).and_return(pv_numpy_locked).ordered()
context.graph.should_receive(
"get_python_package_hashes_sha256").with_args(
"numpy", "1.17.4",
"https://pypi.org/simple").and_return(["111"]).ordered()
context.should_receive("get_package_version").with_args(
("tensorflow", "2.0.0", "https://pypi.org/simple"),
graceful=False).and_return(pv_tensorflow_locked).ordered()
context.graph.should_receive(
"get_python_package_hashes_sha256").with_args(
"tensorflow", "2.0.0",
"https://pypi.org/simple").and_return(["222"]).ordered()
pv_daiquiri = PackageVersion(name="daiquiri",
version="*",
index=pypi,
develop=False)
pv_tensorflow = PackageVersion(name="tensorflow",
version=">=2.0.0",
index=pypi,
develop=False)
project = flexmock(
pipfile=Pipfile.from_string(self._PIPFILE),
runtime_environment=RuntimeEnvironment.from_dict(
{"operating_system": {
"name": "rhel"
}}),
)
project.should_receive("iter_dependencies").with_args(
with_devel=True).and_return([pv_daiquiri, pv_tensorflow]).once()
context.project = project
context.dependencies = {
"daiquiri": {
("daiquiri", "1.6.0", "https://pypi.org/simple"): set(),
},
"numpy": {
("numpy", "1.17.4", "https://pypi.org/simple"): set()
},
"tensorflow": {
("tensorflow", "2.0.0", "https://pypi.org/simple"):
{("numpy", "1.17.4", "https://pypi.org/simple")}
},
}
context.dependents = {
"daiquiri": {
("daiquiri", "1.6.0", "https://pypi.org/simple"): set(),
},
"numpy": {
("numpy", "1.17.4", "https://pypi.org/simple"): {(
("tensorflow", "2.0.0", "https://pypi.org/simple"),
"fedora",
"31",
"3.7",
)}
},
"tensorflow": {
("tensorflow", "2.0.0", "https://pypi.org/simple"): set()
},
}
context.graph.should_receive(
"get_python_environment_marker").with_args(
"tensorflow",
"2.0.0",
"https://pypi.org/simple",
dependency_name="numpy",
dependency_version="1.17.4",
os_name="fedora",
os_version="31",
python_version="3.7",
).and_return("python_version >= '3.7'").once()
product = Product.from_final_state(state=state, context=context)
assert product.score == state.score
assert product.justification == state.justification
assert product.advised_runtime_environment == state.advised_runtime_environment
assert product.project.to_dict() == {
"requirements": {
"packages": {
"daiquiri": {
"index": "pypi-org",
"version": "*"
},
"tensorflow": {
"index": "pypi-org",
"version": ">=2.0.0"
},
},
"dev-packages": {},
"requires": {
"python_version": "3.7"
},
"source": [{
"url": "https://pypi.org/simple",
"verify_ssl": True,
"name": "pypi-org",
}],
},
"requirements_locked": {
"_meta": {
"sources": [{
"url": "https://pypi.org/simple",
"verify_ssl": True,
"name": "pypi-org",
}],
"requires": {
"python_version": "3.7"
},
"hash": {
"sha256":
"f08689732b596fd705a45bbf9ec44c3995b17a1aa6392c46500aeb736c4d4e88"
},
"pipfile-spec":
6,
},
"default": {
"daiquiri": {
"version": "==1.6.0",
"hashes": ["sha256:000"],
"index": "pypi-org",
},
"numpy": {
"version": "==1.17.4",
"hashes": ["sha256:111"],
"index": "pypi-org",
"markers": "python_version >= '3.7'",
},
"tensorflow": {
"version": "==2.0.0",
"hashes": ["sha256:222"],
"index": "pypi-org",
},
},
"develop": {},
},
"runtime_environment": {
"hardware": {
"cpu_family": None,
"cpu_model": None
},
"operating_system": {
"name": "rhel",
"version": None
},
"python_version": None,
"cuda_version": None,
"name": None,
"platform": None,
},
}