DuploCtl

Duplo Ctl

This is the main IoC container for the Duplo CLI. It manages configuration, resources, clients, formatters, and models. HTTP and auth behavior live in pluggable client classes loaded via the client extension point system.

Using injected client to load a service.

from duplocloud.controller import DuploCtl
from duplocloud.resource import DuploResource
from duplocloud.errors import DuploError

class DuploSomeService(DuploResource):
  def __init__(self, duplo: DuploCtl):
    super().__init__(duplo)
    self.tenent_svc = duplo.service('tenant')

Instantiation

These are a few static methods which instantiate new instances a few different ways. You can also just use the normal init constructor method to build it up manually.

__init__

DuploCtl Constructor

Creates an instance of a duplocloud client configured for a certain portal. All of the arguments are optional and can be set in the environment or in the config file. The types of each of the arguments are annotated types that are used by argparse to create the command line arguments.

Parameters:

Name	Type	Description	Default
host	HOST	The host of the Duplo instance.	None
token	TOKEN	The token to use for authentication.	None
tenant	TENANT	The tenant to use.	None
tenant_id	TENANT_ID	The tenant id to use.	None
home_dir	HOME_DIR	The home directory for the client.	None
config_file	CONFIG	The config file for the client.	None
cache_dir	CACHE_DIR	The cache directory for the client.	None
version	VERSION	The version of the client.	False
interactive	INTERACTIVE	The interactive mode for the client.	False
ctx	CONTEXT	The context to use.	None
nocache	NOCACHE	The nocache flag for the client.	False
browser	BROWSER	The browser to use for interactive login.	None
isadmin	ISADMIN	The admin flag for the client.	False
query	QUERY	The query to use.	None
output	OUTPUT	The output format for the client.	'json'
loglevel	LOGLEVEL	The log level for the client.	'WARN'

Returns:

Name	Type	Description
duplo	DuploCtl	An instance of a DuploCtl.

from_env staticmethod

From Environment

Create a DuploCtl from environment variables. This is the most common way to create a DuploCtl.

New Client From Environment

duplo, args = DuploCtl.from_env()

Returns:

Name	Type	Description
duplo	DuploCtl	An instance of a DuploCtl.

from_args staticmethod

DuploCtl from Arguments

Create a DuploCtl from an array of global client arguments.

Parameters:

Name	Type	Description	Default
args	str	An array of global client arguments aligning with the DuploCtl constructor.	()

Returns:

Name	Type	Description
duplo	DuploCtl	An instance of DuploCtl.

from_creds staticmethod

Create a DuploCtl from credentials.

Parameters:

Name	Type	Description	Default
host	str	The host of the Duplo instance.	required
token	str	The token to use for authentication.	required
tenant	str	The tenant to use.	required

Returns:

Name	Type	Description
duplo	DuploCtl	The DuploCtl.

Properties

These are the properties of the DuploCtl class.

token: str property writable

Token

Returns the configured token value from args/env/context. May be None.

host: str property

Get Host

Get the host from the Duplo config. This is accessed as a lazy loaded property. If the host is some kind of falsey value, it will attempt to use the context.

Returns:

Type	Description
str	The host as a string.

tenant: str property writable

Get Tenant

Get the tenant from the Duplo config. This is accessed as a lazy loaded property. If the tenant is some kind of falsey value, it will attempt to use the context.

Returns:

Type	Description
str	The tenant as a string.

settings: dict property

Get Config

Get the Duplo config as a dict. This is accessed as a lazy loaded property.

Returns:

Name	Type	Description
settings	dict	The config as a dict.

context: dict property

Get Config Context

Get the current context from the Duplo config. This is accessed as a lazy loaded property.

Returns:

Type	Description
dict	The context as a dict.

config: dict property

Injection

Duploctl is a plugin framework which takes advantage of the Python entrypoints system in the pyproject.toml file. This allows you to inject your own custom classes into the DuploCtl class.

load

Load Resource

Load a resource class from the entry points.

Parameters:

Name	Type	Description	Default
kind	str	The name of the service.	required

Returns:

Name	Type	Description
kind	T	The instantiated service with a reference to this client.

load_client

Load Client

Load and cache a client singleton via the client extension point system.

Parameters:

Name	Type	Description	Default
name	str	The name of the client.	'duplo'

Returns:

Type	Description
	The client instance.

load_formatter

Load Formatter

Load a Formatter function from the entry points.

Parameters:

Name	Type	Description	Default
name	str	The name of the format.	'string'

Returns: The class of the format.

load_model

Load Model

Load a Pydantic model class by name from the duplocloud_sdk. Returns None if the model is not found.

Parameters:

Name	Type	Description	Default
model_name	str	The name of the Pydantic model class (e.g. "AddTenantRequest").	required

Returns:

Type	Description
	The Pydantic model class, or None if not found.

Methods

format

Format data.

Parameters:

Name	Type	Description	Default
data		The data to format.	required
output	str	The output format to use. Defaults to self.output.	None

Returns: The formatted data as a string, or the raw data when output is None.

filter

Query data

Uses the jmespath library to query data. An explicit query override can be passed per invocation, otherwise falls back to the global self.query property.

Parameters:

Name	Type	Description	Default
data		The data to query.	required
query	str	Optional JMESPath query override.	None

Returns: The queried data.

jsonpatch

Json Patch

Apply a json patch to a resource.

Parameters:

Name	Type	Description	Default
patches		The patches to apply.	required

Returns: The patched resource as a JSON object.

validate_model

Validate Model

Validate data against a Pydantic model class. Takes the model class directly (not a name string). Does not check the global validate flag — callers decide when to call this. Raises DuploInvalidError if validation fails.

Parameters:

Name	Type	Description	Default
model		The Pydantic model class.	required
data	dict	The dict to validate.	required

Returns:

Type	Description
dict	The validated and serialized dict.

Raises:

Type	Description
DuploInvalidError	If the data fails model validation.

use_context

Use Context

Use the specified context from the Duplo config.

Parameters:

Name	Type	Description	Default
name	str	The name of the context to use.	None

logger_for

Create a Default Logger

Create a default logger for the given name. This will create a logger with the name 'duplo' and add a console output handler.

Parameters:

Name	Type	Description	Default
name	str	The name of the logger.	None

Returns: The logger.

build_command

Context Args

Build a comamnd using the current context.

Returns:

Type	Description
list[str]	The context args as a dict.

__call__

Run a service command.

Choose a resource name and pass it's params in. Each resource has a unique set of arguments and therefore there is no need to try and define anything beyond a resource name and an optional query. Everything else is processed by the resource itself in it's own call method. Not all resources have commands and only execute their call method.

Parameters:

Name	Type	Description	Default
resource	str	The name of the resource.	None
args		The arguments to the resource.	()
query	str	Optional JMESPath query override for this invocation.	None
kwargs		Additional keyword arguments passed to the command.	{}

Returns: The result of the command.