glaium-sdk 0.1.2

Glaium SDK in Python for managing your Systems and Optimization

Glaium SDK

Install

Classes & Methods

Optimizer

optimizer(api_token,user,pw)

params:

• api_token - Glaium API token for the organization
• user - Username (manager or owner) for the organization
• pw - Password for user login

return: json {error_code:response}

• error code: 0 (ok) or not 0 (error)
• response: {}

optimizer.model( oper, name)

params:

• oper - Operation type:
  • get - Load a specific Model. Current available models:
    • Mobile Gaming
    • AdTech
    • SaaS (coming soon)
    • eCommerce (coming soon)
  • set - Update or save the current systems set in a new or existent Model.
  • del - Delete a specific Model.
• name - Name for the model

return: json {error_code:response}

• error code: 0 (ok) or not 0 (error)
• response - json containing all systems (agents) from the model: {agent_name_1:agent_id_1,…agent_name_N:agent_id_N}

optimizer.goal(name, description, objective, constraints, resources)

params:

• name - Goal name
• description - Goal description
• objective - json containing {’system’:system_id, ’target’:’metric_name’, ’comparison’: comparison operator (>, ≥, =, ≤, <) , ’outcome’: value expected, ’by’:date}
• constraints - json containing {system_id_1:conditionals,…,system_id_N:conditionals}
• resources - json containing {system_id_1:{resource_1:availability, … resource_N:availability}, … system_id_N:{resource_1:availability, … resource_N:availability}}

return: json {error_code:response}

• error code: 0 ok or not 0 error
• response - goal_id

System (Agents)

system(oper,name)

params:

• oper - Operation type: add or del
• name - Name for the system (agent)

return: json {error_code:response}

• error code: 0 ok or not 0 error
• response - system_id (ok) or error message

system.config(system_id, inputs, output, frequency, duration, constraints, resources)

params:

• inputs - json containing {system_id_1:units needed,…,system_id_N:units needed}
  • units needed - An specific amount (float) or np.inf for all that is available
• output - json containing {’name’: output_name, ‘unity’: type of unity, ’cumulative’:yes/no for accumulation between cycles, ‘returns’; yes/no for returning units from other systems}
• frequency - when to start each cycle: ‘every hour’, ‘daily’, ‘every other day’, ‘every 1st day of month’…
• duration - max duration to use as watchdog timer.
• constraints - conditionals formula
• resources - json containing {system_id_1:{resource_1:usage, … resource_N:usage}, … system_id_N:{resource_1:usage, … resource_N:usage}}

return: json {error_code:response}

• error code: 0 (ok) or not 0 (error)
• response - None (ok) or error message

system.optimization(system_id )

params:

• system_id

return: json {error_code:response}

• error code: 0 (ok) or not 0 (error)
• response - json containing {’next_cycle’ : cycle number, ‘next_when’: datetime to start next cycle, ‘output’ : units expected for output, ‘inputs’: {‘input_1_name’ : units suggested for input 1, … ’input_N_name’ : units suggested for input N}}

system.start(system_id, cycle)

params:

• system_id - Id of the system (agent) starting its process
• cycle (optional) - number of cycle starting

return: json {error_code:response}

• error code: 0 (ok) or not 0 (error)
• response - None (ok) or error message

system.stop( system_id, status, stock, cycle)

params:

• system_id - Id of the system (agent) starting its process
• status - json containing {status_type:status_msg}
  • status_type: ok, halt (motive of halting process), hands-up (requires human intervention for <status_msg>) and error (type of error)
• stock - current volume of units available in the output
• cycle (optional) - number of cycle starting

return: json {error_code:response}

• error code: 0 (ok) or not 0 (error)
• response - None (ok) or error message

system.performance(system_id)

params:

• system_id - Id of the system (agent) requesting performance information

return: json {error_code:response}

• error code: 0 (ok) or not 0 (error)
• response - json containing {’effectiveness’:%, ‘efficiency’:%, ‘average_duration’: number of seconds}

Data

data.integration( oper, integration)

params:

• oper - Operation type
  • add - Add one or more new Integration(s)
  • del - Delete one or more existent Integration(s)
• integration - json containing {name:integrator,… name_N:integrator}
  • name - Name of the Integration
  • integrator - Type of the Integration. See https://glaium.io/integrators/ for list available. Optional for del operation.

return: json {error_code:response}

• error code: 0 (ok) or not 0 (error)
• response - None (ok) or error message

data.pull(metrics,dimensions,conditional,period)

params:

• metrics - Numeric primitives (float)
• dimensions - Categorical primitives (string)
• conditional - formula
• period - initial and end datetimes or temporal expressions ("last 10 days", "end of year", "next 2 months", "yesterday", …)

return: json {error_code:response}

• error code: 0 (ok) or not 0 (error)
• response - pd.DataFrame (ok) or error message

data.normalize(data,primitive,how)

params:

• data - pd.DataFrame
• primitive - Primitive to normalize
• how - json containing {’normalization_function’:’params’,…} with the following available functions:
  • automatic: list of terms to detect
  • custom: json containing {search_value:replace_value,…}
  • conditional: json containing {’if_condition’:value,…’else’:default_value}

return: json {error_code:response}

• error code: 0 (ok) or not 0 (error)
• response - pd.DataFrame (ok) or error message

data.push(data, integrations, when, frequency)

params:

• data - pd.DataFrame
• integrations - list of Integrations to push data to
• when - datetime to push data to the list of integrations.
• frequency - temporal expression. Ex: ‘every hour’, ‘daily’, ‘every other day’, ‘every 1st day of month’…

return: json {error_code:response}

• error code: 0 (ok) or not 0 (error)
• response - None or error message