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The Seeq SDK for Python

Project description

The seeq Python library is used to interface with Seeq Server (http://www.seeq.com).

Execute pip install seeq to make it available for import.

seeq.spy

The Seeq Spy module is a friendly set of functions that are optimized for use with Jupyter, Pandas and NumPy.

The Spy module is the best choice if you're trying to do any of the following:

  • Search for signals, conditions, scalars, assets
  • Pull data out of Seeq
  • Import data in a programmatic way (when Seeq Workbench's CSV Import capability won't cut it)
  • Calculate new data in Python and push it into Seeq
  • Create an asset model

To start exploring the Spy module, execute the following lines of code in Jupyter:

from seeq import spy
spy.docs.copy()

Your Jupyter folder will now contain a Spy Documentation folder that has a Tutorial and Command Reference notebook that will walk you through common activities.

For more advanced tasks, you may need to use the SDK module described below.

seeq.sdk

The Seeq SDK module is a set of Python bindings for the Seeq Server REST API. You can experiment with the REST API by selecting the API Reference menu item in the upper-right "hamburger" menu of Seeq Workbench.

Login is accomplished with the following pattern:

import seeq
import getpass

api_client = seeq.sdk.ApiClient('http://localhost:34216/api')

# Change this to False if you're getting errors related to SSL
seeq.sdk.Configuration().verify_ssl = True

auth_api = seeq.sdk.AuthApi(api_client)
auth_input = seeq.sdk.AuthInputV1()

# Use raw_input() instead of input() if you're using Python 2
auth_input.username = input('Username:').rstrip().lower()
auth_input.password = getpass.getpass()
auth_input.auth_provider_class = "Auth"
auth_input.auth_provider_id = "Seeq"
auth_api.login(body=auth_input)

The api_client object is then used as the argument to construct any API object you need, such as seeq.sdk.ItemsApi. Each of the root endpoints that you see in the API Reference webpage corresponds to a seeq.sdk.XxxxxApi class.


In case you are looking for the Gencove package, it is available here: https://pypi.org/project/gencove/

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