2.3.9 Projects

A project is the collection of your labeled sensor data and algorithms used to build your application.

Examples:

client.projects = 'My Project'

client.project.columns()

client.project..metadata_columns()

client.project.labels()
class mplabml.datamanager.projects. Projects(connection)

Base class for a collection of projects.

build_project_dict()

Populates the function_list property from the server

create_project(name)

Creates a project using the name property

Parameters

name (str) – Name of the new project

Returns

project

Raises

ProjectExistsError , if the project already exists on the server –

get_or_create_project(name)

Calls the REST API and gets the project by name; if it does not exist, insert a new project

Parameters

name (str) – Name of the project

Returns

project object

get_project_by_name(name)

Gets a project from the server using its name property

Parameters

name (str) – Name of the project

Returns

project or None if project does not exist

get_projects()

Gets all projects from the server as project objects

Returns

list[project]

new_project(dict={})

Creates a new project

Parameters

dict (dict) – dictionary containing the attributes of the new project

Returns

project

class mplabml.datamanager.project. Project(connection)

Base class for a project.

add_segmenter(name, segmenter, preprocess=None, custom=False)

Saves a segmentation algorithm as the project’s global segmentation setting

Parameters
  • name (str) – Name to call the segmenter

  • segmenter (FunctionCall) – Segmentation call object that the project will use by default

  • preprocess (dict) – Segment transforms to perform before segmenter

  • custom (bool) – A custom segmenter, or one of your server side segmenters

columns()

Returns the sensor columns available in the project.

Returns

A list of string names of the project’s sensor columns

Return type

columns (list[str])

property created_at

Date of the project creation

delete()

Calls the REST API to delete the object

delete_async()

Calls the Async REST API to delete the project

delete_async_status()

Calls the Async REST API to get the status of deleting the project

delete_async_stop()

Calls the Async REST API to stop deleting the project

get_knowledgepack(kp_uuid)

Gets the KnowledgePack(s) created by the sandbox

Returns

A KnowledgePack instance, list of instances or None

initialize_from_dict(dict)

Reads a json dict and populates a single project

Parameters

dict (dict) – contains the project’s ‘name’, ‘uuid’, ‘schema’ and ‘settings’ properties

insert()

Calls the REST API to insert a new object; uses only the name and schema

label_columns()

Returns the label columns available in the project

Returns

A list of string names of the project’s metadata columns

Return type

columns (list[str])

list_knowledgepacks()

Lists all of the knowledgepacks associated with this project

Returns

knowledgepacks on kb cloud

Return type

DataFrame

metadata_columns()

Returns the metadata columns available in the project

Returns

A list of string names of the project’s metadata columns

Return type

columns (list[str])

property name

Name of the project object

property plugin_config

Plugin Config of the project object

refresh()

Calls the REST API, and self populates from the server

property schema

Schema of the project object

property settings

Global settings of the project object

statistics()

Gets all capture statistics for the project

Returns

DataFrame of capture statistics

update()

Calls the REST API to update the object

property uuid

Auto generated unique identifier for the project object