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AIoT Studio

AIoT Studio is the official library to develop datasources and dependency sets for mnubo's AIoT Studio.

Installation

Requirements

  • Python 2.7 or Python 3.4 and up
  • requests
  • pandas ≥ 0.20
  • numpy

$ pip install aiot-studio

Simple datasource usage

from aiotstudio.datasource import search_df, log

def execute(parameters):
    log.info("Hello aiot-studio")
             
    result = search_df({
        "from": "event",
        "select": [{"count": "*"}]
    })
    return result

Configuration

The library needs to be configured with your mnubo API credentials. The credentials can be shared as follows (by decreasing order of priority):

  • Environment variables: MNUBO_CLIENT_ID, MNUBO_CLIENT_SECRET, MNUBO_API_URL
  • Local config file: application.conf at the root of the project or anywhere indicated by the MNUBO_CONFIG_FILE environment variable
  • Global config file: ~/.settings/mnubo/application.conf (or C:\Users\<username>\.settings\mnubo\application.conf on Windows)

For the last two options, the configuration file should look like this:

[DEFAULT]
mnubo_client_id = {API_CLIENT_ID}
mnubo_client_secret = {API_CLIENT_SECRET}
mnubo_api_url = https://prod.api.mnubo.com

Available methods

  • search(query): returns the search result as a JSON
  • search_df(query): returns the search result as a Pandas DataFrame
  • log: Python logger: will appear in the "Logs" app, use log.info, log.warning or log.error instead of print
  • blob_store_bucket_names(): returns the bucket names available
  • blob_store_fetch(bucket_name, object_name): grabs the object from the bucket

Notes:

  • All "search" methods expect a MQL query as described in the search API documentation
  • Blob store methods are only available when the code runs inside mnubo's architecture, using it locally would throw a FeatureUnavailableError

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