1.8.0

Highlights

• Support MDX properties in execute_mdx_dataframe.
  This allows to query data and attribute data with a single query into one shared data frame.

from TM1py import TM1Service

with TM1Service(address="", port=12354, user="admin", password="apple", ssl=True) as tm1:
    mdx = """
    SELECT
    {Tm1SubsetAll([Region])} PROPERTIES [Region].[Currency] ON COLUMNS,
    {Tm1SubsetAll([Year])} ON ROWS
    FROM [Sales]
    """

    data = tm1.cells.execute_mdx_dataframe(mdx, include_attributes=True)

	Year	Region	Currency	Value
0	2021	US	USD	18
1	2021	UK	GBP	4

• write_async and write_async_dataframe functions with max_workers argument.
  This is essentially an easy way to speed up TM1 writeback through parallelization.

from TM1py import TM1Service

with TM1Service(address="", port=12354, ssl=True, user="admin", password="apple") as tm1:
    cells = {
        ('e1', 'e1'): 1,
        ('e1', 'e2'): 2,
        ('e2', 'e1'): 3,
        ('e2', 'e2'): 4,
        ('e3', 'e1'): 5,
        ('e3', 'e2'): 6,
    }

    tm1.cells.write_async(cube_name="c1", cells=cells, slice_size=1, max_workers=6)

from pandas import DataFrame

from TM1py import TM1Service

with TM1Service(address="", port=12354, ssl=True, user="admin", password="apple") as tm1:
    data = DataFrame({
        'd1': ['e1', 'e1', 'e2', 'e2', 'e3', 'e3'],
        'd2': ['e1', 'e2', 'e1', 'e2', 'e1', 'e2'],
        'value': [1, 2, 3, 4, 5, 6],
    })

    tm1.cells.write_dataframe_async(cube_name="c1", data=data, slice_size_of_dataframe=1, max_workers=6)

• TM1 git support #447
  TM1py now allows you to manage the TM1 git repository. You can manage the TM1 database with git and TM1py.

• New authentication mode based on cam_passport. Can be used from Jupyter within Cognos Analytics.

from ca_data_connector.ca_lib import OnPremSession

session = OnPremSession()
session.initialize()
passport = session.get_cookies()['cam_passport']

with TM1Service(address=address, port=port, ssl=ssl, cam_passport=passport) as tm1:
    print(tm1.server.get_server_name())

New Features

• AuditLog queries 3771dad
• Changes to tm1.power_bi.execute_mdx function to provide data to PBI in the most friendly way #476
• Improvement on PowerBI dimension retrieval function to fetch attribute for a parent instead of parent element name #478
• Support MDX PROPERTIES in execute_mdx_dataframe #470
• Introduce a new cancel_at_timeout argument to abort TM1 operation once the timeout is reached
• Support process debugging a83da11
• New arguments on execute_mdx, execute_view: skip_cell_properties, element_unique_names to control shape of response dictionary f751edf, 6d9e520
• TM1 git support #447
• New write_dataframe_async function 94081eb
• New write_async function 3969c1d
• Create, read, update, delete servers on admin host #296
• New re_authenticate function in TM1Service 2028d3d
• Better delta log requests aeed032
• Allow login with cam_passport f070c06

Fixes

• Never attempt to delete leaves hierarchy a0aa152
• Make install with pandas work with zsh c458e40
• Fix encoding of ui-data property 6438309
• Fix deactivate / activate chore #515
• Accept float as timeout 2d0c555
• Fix is_admin property in User class d9ed1b2
• Fix documentation on readthedocs
• Remove linebreaks when writing with ti #568
• Include empty strings suppression in extract_cellset_raw 01eb4a7
• Allow parameters on unbound processes 144db38
• Improve kwargs delegation through call stack ee70f54
• Allow WITH MEMBERS combined with include_attributes=True in execute_mdx_dataframe function #593
• Allow WITH MEMBERS combined with display_attribute=True in execute_mdx_dataframe_shaped function #593
• Skip sandbox dimension in cubes.get #595

Acknowledgments

Big thanks to @lapstue, @kaleming, @beckyconning, @macsir, @jrobinsonAG, @tomasfelcman, @cwffonseca for contributing code to this release, and many others for reporting bugs and requesting features.

How to upgrade TM1py

To upgrade TM1py, just use the following command:

pip install TM1py --upgrade