The script makes an API GET call to {{TCO_URL}}/v2/catalog/metric-entities and fetches all the metric entities which is then converted into JSON Schema and a relevant Python class is generated for every metric entity segregated based on the domain in a package structure.
The script generate_catalog_metrics.py can be used to generate Metric Model classes as shown below:
python3 generate_catalog_metrics.py --host <host_name> --port <port>
python3 generate_catalog_metrics.py --host 10.225.67.98 --port 30002
The generated Catalog Metric Python classes are present under /collector-sdk/models/ folder
json_data = generatePythonClasses(arguments.host, arguments.port, arguments.user, arguments.pwd, arguments.protocol)
builder = SchemaBuilder()
# Load the json string to a variable
entity = json_data["entity"]
schema = {}
for e in entity:
builder.add_object(e)
schema = builder.to_schema()
#Create a Title field in the schema equal to metricType from Json Data. metricType = e["metricType"]
schema["title"] = metricType
fileName = snakecase(metricType)
#If File name starts with a digit, append underscore at the prefix.
if fileName is not None and fileName[0].isdigit():
fileName = "_" + fileName
domain = snakecase(e["domain"])
dir_path = "models/"+ domain + "/"
Path(dir_path).mkdir(parents=True, exist_ok=True)
if arguments.host is None or arguments.port is None:
print("Host and Port cannot be empty")
else:
file_path = dir_path + fileName +".py"
if not os.path.exists(file_path) or Config.override_generated_class:
generate_python_file(schema, Path(file_path))
By default, username = admin, password = changeme, protocol = https, override flag is set to True (the script overrides and creates the classes each time)
Sample generated Python class -
from typing import List
from models.metric import TCOMetric
class processor(TCOMetric):
class metrics(list):
class items(TCOMetric):
def __init__(self, values: dict = None):
values = values if values is not None else {}
self.name: str = values.get("name", None)
self.description: str = values.get("description", None) self.unit: str = values.get("unit", None)
def __repr__(self):
return "items[" + ", ".join((f"name: {repr(self.name)}", f"description: {repr(self.description)}", f"unit: {repr(self.unit)}",)) + "]"
def __init__(self, values: list = None): super().__init__()
values = values if values is not None else []
self[:] = [self.items(value) for value in values]
class properties(list):
class items(TCOMetric):
def __init__(self, values: dict = None):
values = values if values is not None else {}
self.name: str = values.get("name", None)
self.description: str = values.get("description", None)
def __repr__(self):
return "items[" + ", ".join((f"name: {repr(self.name)}", f"description: {repr(self.description)}",)) + "]"
def __init__(self, values: list = None): super().__init__()
values = values if values is not None else []
self[:] = [self.items(value) for value in values]
class tags(list):
class items(TCOMetric):
def __init__(self, values: dict = None):
values = values if values is not None else {}
self.name: str = values.get("name", None)
self.description: str = values.get("description", None)
def __repr__(self):
return "items[" + ", ".join((f"name: {repr(self.name)}", f"description: {repr(self.description)}",)) + "]"
def __init__(self, values: list = None): super().__init__()
values = values if values is not None else []
self[:] = [self.items(value) for value in values]
def __init__(self, values: dict = None):
values = values if values is not None else {}
self.domain: str = values.get("domain", None)
self.sub_domains: List[str] = values.get("sub_domains", None) self.description: str = values.get("description", None) self.metricType: str = values.get("metricType", None)
self.metrics: List[items] = self.metrics(values=values.get("metrics"))
self.properties: List[items] = self.properties(values=values.get("properties"))
self.tags: List[items] = self.tags(values=values.get("tags")) self.tco_internal: List[str] = values.get("tco_internal", None) self.is_base_model: bool = values.get("is_base_model", None)
def __repr__(self):
return "processor[" + ", ".join((f"domain: {repr(self.domain)}", f"sub_domains: {repr(self.sub_domains)}",
f"description: {repr(self.description)}",
f"metricType: {repr(self.metricType)}",
f"metrics: {repr(self.metrics)}",
f"properties: {repr(self.properties)}",
f"tags: {repr(self.tags)}",
f"tco_internal: {repr(self.tco_internal)}",
f"is_base_model: {repr(self.is_base_model)}", )) + "]"
