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License](https://img.shields.io/pypi/l/TM1py)\n![PyPI - Version](https://img.shields.io/pypi/v/TM1py)\n![Pepy Total Downloads](https://img.shields.io/pepy/dt/TM1py)\n\u003c/h1\u003e\n\nTM1py is the python package for IBM Planning Analytics (TM1).\n\n``` python\nwith TM1Service(address='localhost', port=8001, user='admin', password='apple', ssl=True) as tm1:\n    subset = Subset(dimension_name='Month', subset_name='Q1', elements=['Jan', 'Feb', 'Mar'])\n    tm1.subsets.create(subset, private=True)\n```\n\nFeatures\n=======================\n\nTM1py offers handy features to interact with TM1 from Python, such as\n\n- Functions to read data from cubes through cube views or MDX queries (e.g. `tm1.cells.execute_mdx`)\n- Functions to write data to cubes (e.g. `tm1.cells.write`)\n- Functions to update dimensions and hierarchies (e.g. `tm1.hierarchies.get`)\n- Functions to update metadata, clear or write to cubes directly from pandas dataframes  (e.g. `tm1.elements.get_elements_dataframe`)\n- Async functions to easily parallelize your read or write operations (e.g. `tm1.cells.write_async`)\n- Functions to execute TI process or loose statements of TI (e.g. `tm1.processes.execute_with_return`)\n- CRUD features for all TM1 objects (cubes, dimensions, subsets, etc.)\n\nRequirements\n=======================\n\n- [Python](https://www.python.org/downloads/) (3.7 or higher)\n- [TM1/Planning Analytics](https://www.ibm.com/products/planning-analytics) (v11 or higher)\n\nOptional Python Packages\n=======================\n\n- pandas\n- networkx\n\nInstall\n=======================\n\n\u003e without pandas\n\n    pip install tm1py\n    \n\u003e with pandas\n\n    pip install \"tm1py[pandas]\"\n\nUsage\n=======================\n\n\u003e TM1 11 on-premise\n\n``` python\nfrom TM1py.Services import TM1Service\n\nwith TM1Service(address='localhost', port=8001, user='admin', password='apple', ssl=True) as tm1:\n    print(tm1.server.get_product_version())\n```\n\n\u003e TM1 11 on IBM cloud\n\n``` python\nwith TM1Service(\n        base_url='https://mycompany.planning-analytics.ibmcloud.com/tm1/api/tm1/',\n        user=\"non_interactive_user\",\n        namespace=\"LDAP\",\n        password=\"U3lSn5QLwoQZY2\",\n        ssl=True,\n        verify=True,\n        async_requests_mode=True) as tm1:\n    print(tm1.server.get_product_version())\n```\n\n\u003e TM1 12 PAaaS\n\n``` python\nfrom TM1py import TM1Service\n\nparams = {\n    \"base_url\": \"https://us-east-1.planninganalytics.saas.ibm.com/api/\u003cTenantId\u003e/v0/tm1/\u003cDatabaseName\u003e/\",\n    \"user\": \"apikey\",\n    \"password\": \"\u003cTheActualApiKey\u003e\",\n    \"async_requests_mode\": True,\n    \"ssl\": True,\n    \"verify\": True\n}\n\nwith TM1Service(**params) as tm1:\n    print(tm1.server.get_product_version())\n```\n\n\u003e TM1 12 on-premise \u0026 Cloud Pak For Data\n\n``` python\nwith TM1Service(\n        address=\"tm1-ibm-operands-services.apps.cluster.your-cluster.company.com\",\n        instance=\"your instance name\",\n        database=\"your database name\",\n        application_client_id=\"client id\",\n        application_client_secret=\"client secret\",\n        user=\"admin\",\n        ssl=True) as tm1:\n\n    print(tm1.server.get_product_version())\n```\n\n\u003e TM1 12 on-premise with access token\n\n``` python\nparams = {\n    \"base_url\": \"https://pa12.dev.net/api/\u003cInstanceId\u003e/v0/tm1/\u003cDatabaseName\u003e\",\n    \"user\": \"8643fd6....8a6b\",\n    \"access_token\":\"\u003cTheActualAccessToken\u003e\",\n    \"async_requests_mode\": True,\n    \"ssl\": True,\n    \"verify\": True\n}\n\nwith TM1Service(**params) as tm1:\n    print(tm1.server.get_product_version())\n```\n\nDocumentation\n=======================\n\n\u003chttps://tm1py.org/\u003e\n\nIssues\n=======================\n\nIf you find issues, sign up in GitHub and open an Issue in this repository\n\nContribution\n=======================\n\nTM1py is an open source project. It thrives on contribution from the TM1 community.\nIf you find a bug or feel like you can contribute please fork the repository, update the code and then create a pull request so we can merge in the changes.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcubewise-code%2Ftm1py","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcubewise-code%2Ftm1py","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcubewise-code%2Ftm1py/lists"}