TM1py
A python module for TM1.
Decision gist · record as of 2026-08-14
Yes. TM1py is the standard Python interface to Planning Analytics, actively maintained, widely used (top 15000 PyPI packages), and carries no known security vulnerabilities. Install it if you need to automate TM1 workflows or integrate TM1 data into Python applications. The low install friction and permissive license make it a straightforward choice for enterprise users.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires TM1/Planning Analytics v11 or higher running on-premise or cloud; Python 3.7 or higher.
- Low friction install with a pure-wheel distribution.
- Active maintenance with a recent release (62 days ago) and steady repository activity.
License · maintenance · safety
MIT (permissive) — MIT license is permissive, allowing use in commercial and private projects with minimal restrictions—only requiring attribution.
last release 2026-06-13 (62 days) · last repo commit 2026-06-23 · 222 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 322,911 downloads/mo, #7,606 on PyPI
Alternatives
Verify before relying
pip install tm1py
from TM1py.Services import TM1Service
with TM1Service(address='localhost', port=8001, user='admin', password='apple', ssl=True) as tm1:
print(tm1.server.get_product_version())- Whether optional dependencies (pandas, networkx) are required for specific features or truly optional.
- Performance characteristics when executing large MDX queries or bulk write operations.
- Compatibility details with the latest TM1 12 PAaaS and Cloud Pak For Data deployments.
What it is and what it does
TM1py is a Python client library for IBM Planning Analytics (TM1), a multidimensional database and planning platform. It abstracts the REST API into Pythonic methods for reading and writing cube data, managing dimensions and hierarchies, executing MDX queries, and running TI processes. The package supports both on-premise TM1 installations and cloud deployments (IBM Cloud, PAaaS, Cloud Pak For Data), with connection modes for SSL, LDAP, OAuth, and API keys.
The library is designed for data engineers and analysts who need to automate TM1 workflows from Python—extracting data via MDX or cube views, loading data from pandas DataFrames, updating metadata, and parallelizing operations with async methods. It handles the authentication and HTTP plumbing, leaving you to focus on business logic. Active maintenance and a permissive MIT license make it suitable for production use in enterprise environments.
Use it for
- Automate daily ETL pipelines that read TM1 cube data via MDX and load results into a data warehouse.
- Build Python scripts to bulk-update TM1 dimensions and hierarchies from external data sources.
- Execute TI processes programmatically and retrieve their return values for monitoring or error handling.
- Parallelize large cube write operations using async methods to reduce overall runtime.
- Integrate TM1 data into Jupyter notebooks or pandas workflows for ad-hoc analysis and reporting.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
TM1py is the standard Python interface to Planning Analytics, actively maintained, widely used (top 15000 PyPI packages), and carries no known security vulnerabilities. Install it if you need to automate TM1 workflows or integrate TM1 data into Python applications. The low install friction and permissive license make it a straightforward choice for enterprise users.
Install
tm1py on PyPI
Before you install
Low friction install with a pure-wheel distribution. Active maintenance with a recent release (62 days ago) and steady repository activity. Five runtime dependencies are all well-established packages (requests, ijson, pytz, and two SSPI/MDX-specific libraries).
Requires TM1/Planning Analytics v11 or higher running on-premise or cloud; Python 3.7 or higher.
License in practice
MIT license is permissive, allowing use in commercial and private projects with minimal restrictions—only requiring attribution.
Quickstart
pip install tm1py
from TM1py.Services import TM1Service
with TM1Service(address='localhost', port=8001, user='admin', password='apple', ssl=True) as tm1:
print(tm1.server.get_product_version())Verify before relying
- Whether optional dependencies (pandas, networkx) are required for specific features or truly optional.
- Performance characteristics when executing large MDX queries or bulk write operations.
- Compatibility details with the latest TM1 12 PAaaS and Cloud Pak For Data deployments.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesijsonrequestspytzrequests_negotiate_sspimdxpy |
| Maintenance | Actively maintained 62 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 322,911 / month, #7,606 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: tm1py-2.3.1-py3-none-any.whl
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