def deploy(
self,
api_spec: Dict[str, Any],
force: bool = True,
wait: bool = False,
):
"""
Deploy or update an API.
Args:
api_spec: A dictionary defining a single Cortex API. See https://docs.cortex.dev/v/master/ for schema.
force: Override any in-progress api updates.
wait: Block until the API is ready.
Returns:
Deployment status, API specification, and endpoint for each API.
"""
temp_deploy_dir = util.cli_config_dir() / "deployments" / api_spec["name"]
if temp_deploy_dir.exists():
shutil.rmtree(str(temp_deploy_dir))
temp_deploy_dir.mkdir(parents=True)
cortex_yaml_path = os.path.join(temp_deploy_dir, "cortex.yaml")
with util.open_temporarily(cortex_yaml_path, "w", delete_parent_if_empty=True) as f:
yaml.dump([api_spec], f) # write a list
return self.deploy_from_file(cortex_yaml_path, force=force, wait=wait)
def patch(self, api_spec: dict, force: bool = False) -> dict:
"""
Update the api specification for an API that has already been deployed.
Args:
api_spec: The new api specification to apply
force: Override an already in-progress API update.
"""
cortex_yaml_file = (util.cli_config_dir() / "deployments" /
f"cortex-{str(uuid.uuid4())}.yaml")
with util.open_temporarily(cortex_yaml_file, "w") as f:
yaml.dump([api_spec], f)
args = [
"patch", cortex_yaml_file, "--env", self.env_name, "-o", "json"
]
if force:
args.append("--force")
output = run_cli(args, hide_output=True)
return json.loads(output.strip())
def _create_default_scope(optional_tags: dict = {}) -> sentry_sdk.Scope:
"""
Creates default scope. Adds user ID as tag to the reported event.
Can add optional tags.
"""
scope = sentry_sdk.Scope()
user_id = None
client_id_file_path = util.cli_config_dir() / "client-id.txt"
if not client_id_file_path.is_file():
client_id_file_path.parent.mkdir(parents=True, exist_ok=True)
client_id_file_path.write_text(str(uuid4()))
user_id = client_id_file_path.read_text()
if user_id:
scope.set_user({"id": user_id})
for k, v in optional_tags.items():
scope.set_tag(k, v)
return scope
def create_api(
self,
api_spec: dict,
predictor=None,
task=None,
requirements=[],
conda_packages=[],
project_dir: Optional[str] = None,
force: bool = True,
wait: bool = False,
) -> list:
"""
Deploy an API.
Args:
api_spec: A dictionary defining a single Cortex API. See https://docs.cortex.dev/v/master/ for schema.
predictor: A Cortex Predictor class implementation. Not required for TaskAPI/TrafficSplitter kinds.
task: A callable class/function implementation. Not required for RealtimeAPI/BatchAPI/TrafficSplitter kinds.
requirements: A list of PyPI dependencies that will be installed before the predictor class implementation is invoked.
conda_packages: A list of Conda dependencies that will be installed before the predictor class implementation is invoked.
project_dir: Path to a python project.
force: Override any in-progress api updates.
wait: Streams logs until the APIs are ready.
Returns:
Deployment status, API specification, and endpoint for each API.
"""
if project_dir is not None:
if predictor is not None:
raise ValueError(
"`predictor` and `project_dir` parameters cannot be specified at the same time, please choose one"
)
if task is not None:
raise ValueError(
"`task` and `project_dir` parameters cannot be specified at the same time, please choose one"
)
if project_dir is not None:
cortex_yaml_path = os.path.join(project_dir,
f".cortex-{uuid.uuid4()}.yaml")
with util.open_temporarily(cortex_yaml_path, "w") as f:
yaml.dump([api_spec], f) # write a list
return self._deploy(cortex_yaml_path, force, wait)
api_kind = api_spec.get("kind")
if api_kind == "TrafficSplitter":
if predictor:
raise ValueError(
f"`predictor` parameter cannot be specified for {api_kind} kind"
)
if task:
raise ValueError(
f"`task` parameter cannot be specified for {api_kind} kind"
)
elif api_kind == "TaskAPI":
if predictor:
raise ValueError(
f"`predictor` parameter cannnot be specified for {api_kind} kind"
)
if task is None:
raise ValueError(
f"`task` parameter must be specified for {api_kind} kind")
elif api_kind in ["BatchAPI", "RealtimeAPI"]:
if not predictor:
raise ValueError(
f"`predictor` parameter must be specified for {api_kind}")
if task:
raise ValueError(
f"`task` parameter cannot be specified for {api_kind}")
else:
raise ValueError(
f"invalid {api_kind} kind, `api_spec` must have the `kind` field set to one of the following kinds: {['TrafficSplitter', 'TaskAPI', 'BatchAPI', 'RealtimeAPI']}"
)
if api_spec.get("name") is None:
raise ValueError("`api_spec` must have the `name` key set")
project_dir = util.cli_config_dir() / "deployments" / api_spec["name"]
if project_dir.exists():
shutil.rmtree(str(project_dir))
project_dir.mkdir(parents=True)
cortex_yaml_path = os.path.join(project_dir, "cortex.yaml")
if api_kind == "TrafficSplitter":
# for deploying a traffic splitter
with open(cortex_yaml_path, "w") as f:
yaml.dump([api_spec], f) # write a list
return self._deploy(cortex_yaml_path, force=force, wait=wait)
actual_version = (
f"{sys.version_info.major}.{sys.version_info.minor}.{sys.version_info.micro}"
)
if actual_version != EXPECTED_PYTHON_VERSION:
is_python_set = any(
conda_dep.startswith("python=") or "::python=" in conda_dep
for conda_dep in conda_packages)
if not is_python_set:
conda_packages = [f"python={actual_version}", "pip=19.*"
] + conda_packages
if len(requirements) > 0:
with open(project_dir / "requirements.txt",
"w") as requirements_file:
requirements_file.write("\n".join(requirements))
if len(conda_packages) > 0:
with open(project_dir / "conda-packages.txt", "w") as conda_file:
conda_file.write("\n".join(conda_packages))
if api_kind in ["BatchAPI", "RealtimeAPI"]:
if not inspect.isclass(predictor):
raise ValueError(
"`predictor` parameter must be a class definition")
impl_rel_path = self._save_impl(predictor, project_dir,
"predictor")
if api_spec.get("predictor") is None:
api_spec["predictor"] = {}
if predictor.__name__ == "PythonPredictor":
predictor_type = "python"
if predictor.__name__ == "TensorFlowPredictor":
predictor_type = "tensorflow"
api_spec["predictor"]["path"] = impl_rel_path
api_spec["predictor"]["type"] = predictor_type
if api_kind == "TaskAPI":
if not callable(task):
raise ValueError(
"`task` parameter must be a callable (e.g. a function definition or a class definition called `Task` with a `__call__` method implemented"
)
impl_rel_path = self._save_impl(task, project_dir, "task")
if api_spec.get("definition") is None:
api_spec["definition"] = {}
api_spec["definition"]["path"] = impl_rel_path
with open(cortex_yaml_path, "w") as f:
yaml.dump([api_spec], f) # write a list
return self._deploy(cortex_yaml_path, force=force, wait=wait)