from seeq import spy
import pandas as pd

# Set the compatibility option so that you maximize the chance that SPy will remain compatible with your notebook/script
spy.options.compatibility = 192
# Log into Seeq Server if you're not using Seeq Data Lab:
spy.login(url='http://localhost:34216', credentials_file='../credentials.key', force=False)


Retrieves and modifies access control configuration for signals, conditions, scalars, metrics, workbooks, assets or any other item in Seeq that supports access control.

ACL is an acronym for Access Control List, which is a simple list of users and user groups that have Read, Write and/or Manage access for an item. Access control is often hierarchical in nature, with leaf nodes of an asset tree or workbooks within a folder inheriting the access control of their parent.

Modifying ACLs for Pushed Data

In the following example, we will push some data and then modify the ACLs for that data.

import csv
csv_file = pd.read_csv('Support Files/csv_import_example.csv', parse_dates=['TIME(unitless)'], index_col='TIME(unitless)')
push_results = spy.push(data=csv_file, workbook='SPy Documentation Examples >> spy.acl')

After pushing, we can use the returned DataFrame (push_results) to modify the ACLs:

# This will remove the Everyone group by replacing with only me
spy.acl.push(push_results, {
    'Read': True,
    'Write': True,
    'Manage': True
}, replace=True, disable_inheritance=True)

Modifying ACLs for Pushed Workbooks

You can also modify the access control for the workbook that was created:

spy.acl.push(push_results.spy.workbook_id, {
    'Read': True,
    'Write': True,
    'Manage': True
}, replace=True, disable_inheritance=True)

Alternatively, you can search for workbooks and modify them that way:

workbooks ={'Name': 'spy.acl', 'Path': 'SPy Documentation Examples'})
spy.acl.push(workbooks, {
    'Name': 'Everyone',
    'Read': True,
    'Write': True,
    'Manage': False

Retrieving ACLs

You can use the same approach to retrieve ACLs for a set of items:

pull_acl_df = spy.acl.pull(push_results)

Each entry in the table now has an Access Control column, and each cell in that column is an embedded DataFrame you can access like so:

acl_df =['BITDEP(ft)', 'Access Control']

Detailed Help

All SPy functions have detailed documentation to help you use them. Just execute help(spy.<func>) like you see below.