By wrapping the IBM Planning Analytics (TM1) REST API in a concise Python framework, TM1py facilitates Python developments for TM1.
Interacting with TM1 programmatically has never been easier.
with TM1Service(address='localhost', port=8001, user='admin', password='apple', ssl=True) as tm1:
subset = Subset(dimension_name='Month', subset_name='Q1', elements=['Jan', 'Feb', 'Mar'])
tm1.subsets.create(subset, private=True)
TM1py offers handy features to interact with TM1 from Python, such as
- Read data from cubes through cube views and MDX Queries
- Write data into cubes
- Execute processes and chores
- Execute loose statements of TI
- CRUD features for TM1 objects (cubes, dimensions, subsets, etc.)
- Query and kill threads
- Query MessageLog and TransactionLog
- Generate MDX Queries from existing cube views
- Python (3.5 or higher)
- TM1 (10.2.2 FP 5 or higher)
pip install TM1py
from TM1py.Services import TM1Service
with TM1Service(address='localhost', port=8001, user='admin', password='apple', ssl=True) as tm1:
for chore in tm1.chores.get_all():
chore.reschedule(hours=-1)
tm1.chores.update(chore)
Code Documentation: http://tm1py.readthedocs.io/en/latest/
Detailed Installation instructions: https://github.com/MariusWirtz/TM1py-samples
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