{"id":40172460,"url":"https://github.com/cubewise-code/tm1py-samples","last_synced_at":"2026-01-19T17:07:52.105Z","repository":{"id":24112304,"uuid":"100658638","full_name":"cubewise-code/tm1py-samples","owner":"cubewise-code","description":"Do more with TM1 with these ready to use TM1py samples.","archived":false,"fork":false,"pushed_at":"2021-12-07T10:36:41.000Z","size":28873,"stargazers_count":50,"open_issues_count":3,"forks_count":38,"subscribers_count":37,"default_branch":"master","last_synced_at":"2023-04-26T11:46:04.971Z","etag":null,"topics":["cubewise","planning-analytics","python","tm1","tm1-rest-api","tm1py"],"latest_commit_sha":null,"homepage":"https://github.com/cubewise-code/TM1py","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cubewise-code.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-08-18T01:07:48.000Z","updated_at":"2023-03-28T20:16:18.000Z","dependencies_parsed_at":"2022-07-27T04:32:08.159Z","dependency_job_id":null,"html_url":"https://github.com/cubewise-code/tm1py-samples","commit_stats":null,"previous_names":[],"tags_count":null,"template":null,"template_full_name":null,"purl":"pkg:github/cubewise-code/tm1py-samples","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cubewise-code%2Ftm1py-samples","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cubewise-code%2Ftm1py-samples/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cubewise-code%2Ftm1py-samples/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cubewise-code%2Ftm1py-samples/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cubewise-code","download_url":"https://codeload.github.com/cubewise-code/tm1py-samples/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cubewise-code%2Ftm1py-samples/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28577232,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-19T16:29:19.148Z","status":"ssl_error","status_checked_at":"2026-01-19T16:29:17.772Z","response_time":67,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cubewise","planning-analytics","python","tm1","tm1-rest-api","tm1py"],"created_at":"2026-01-19T17:07:51.431Z","updated_at":"2026-01-19T17:07:52.098Z","avatar_url":"https://github.com/cubewise-code.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ccenter\u003e\u003cimg src=\"https://s3-ap-southeast-2.amazonaws.com/downloads.cubewise.com/web_assets/CubewiseLogos/Final+logos_Samples.png\" \nstyle=\"width: 80%; height: 80%;text-align: center\"/\u003e\u003c/center\u003e\n\nTM1py Samples is a great starting point to get up to speed with TM1py. It contains 60+ ready-to-use TM1py scripts such as:\n\n- load TM1 data into pandas for statistical analysis\n- load FX, Stock and GDP data from external sources into your cubes\n- synchronize cubes from different TM1 instances\n- clean your TM1 models through regular expressions\n- generate MDX Queries from existing cube views\n- analyse Processing Feeders time\n- maintain dimensions and subsets with python\n- ...\n\nAll scripts are split into four categories:\n* **Aministration**: All tasks related to TM1 administration such as sessions, transaction logs...\n* **Data**: Data operation such as getting data out of a view or writing data back to TM1\n* **Metadata**: All operations related to TM1 objects such as creating a new dimension, deleting a view...\n* **Samples**: Groups more advanced scripts such as getting data from web services\n\n# Requirements\n\n- TM1       (10.2.2 FP 5 or higher)\n- TM1py    [Installing TM1py guide](https://code.cubewise.com/tm1py-help-content/installing-tm1py)\n\n# Usage\n\nThe first script you should run is **check.py** which enables you to check if TM1py can connect to your TM1 instance:\n* [Check connectivity with TM1](https://code.cubewise.com/tm1py-help-content/check-connectivity-with-tm1)\n\nTo run a script from a command line, download the TM1py-samples repository, navigate to the script folder and then just use the command **python script_name.py**.\nPython scripts can also be run from [TM1 processes](https://code.cubewise.com/tm1py-help-content/run-tm1py-script-from-tm1-process).\n\n# Documentation about TM1py\n* Help articles: https://code.cubewise.com/tm1py-help\n* All TM1py functions: http://tm1py.readthedocs.io/en/latest/\n\n\n# Other\n\n## Python Tutorial\n\nIf you are not familiar with the Python programming language you might want to look into some basic tutorials,\nbefore starting with TM1py.\nthenewboston offers awesome (and free) Python tutorials on his Youtube Channel\nhttps://www.youtube.com/watch?v=HBxCHonP6Ro\n\n## IDE\n\nPyCharm is likely the best IDE for Python. It offers intelligent code completion, on-the-fly error checking and heaps of other features.\nIt allows you to save time and be more productive.\nJetBrains offers a free Community Edition of PyCharm\nhttps://www.jetbrains.com/pycharm/\n\n\n# Issues\n\nIf you find issues, sign up in Github and open an Issue in this repository\n\n# Contribution\n\nIf you wrote cool sample scripts with TM1py, that might be useful for others, feel free to push them to this repository\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcubewise-code%2Ftm1py-samples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcubewise-code%2Ftm1py-samples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcubewise-code%2Ftm1py-samples/lists"}