{"id":23586709,"url":"https://github.com/pythonhealthdatascience/stress_update","last_synced_at":"2025-11-03T11:30:26.703Z","repository":{"id":252263972,"uuid":"808585235","full_name":"pythonhealthdatascience/stress_update","owner":"pythonhealthdatascience","description":"A review and update of the Strengthening the Reporting of Empirical Simulation Studies guidelines for DES, SD, and ABS.","archived":false,"fork":false,"pushed_at":"2024-10-25T15:55:24.000Z","size":4495,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-10-25T16:06:41.589Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://pythonhealthdatascience.github.io/stress_update/","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/pythonhealthdatascience.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-05-31T11:26:05.000Z","updated_at":"2024-10-25T15:55:28.000Z","dependencies_parsed_at":"2024-09-06T15:36:16.747Z","dependency_job_id":"b4b5cc69-0585-47e3-bb08-9308fcd46fac","html_url":"https://github.com/pythonhealthdatascience/stress_update","commit_stats":null,"previous_names":["pythonhealthdatascience/stress_update"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonhealthdatascience%2Fstress_update","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonhealthdatascience%2Fstress_update/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonhealthdatascience%2Fstress_update/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonhealthdatascience%2Fstress_update/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pythonhealthdatascience","download_url":"https://codeload.github.com/pythonhealthdatascience/stress_update/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239412446,"owners_count":19634016,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":[],"created_at":"2024-12-27T04:13:46.652Z","updated_at":"2025-11-03T11:30:26.267Z","avatar_url":"https://github.com/pythonhealthdatascience.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# The STRESS guidelines: a 1st review and update\n\n 🏗 **WORK IN PROGRESS** (STRESS review and update 2024/25) 🏗️   \n\n## Overview\n\nA review and update of the Strengthening the Reporting of Empirical Simulation Studies guidelines for DES, SD, and ABS.  It aims to improve the STRESS reporting guidelines and provide additional support for Hybrid Simulation.\n\n## Authors\n\n[![ORCID: Monks](https://img.shields.io/badge/Tom_Monks_ORCID-0000--0003--2631--4481-brightgreen)](https://orcid.org/0000-0003-2631-4481)\n\nTo - do add FA, et al ORCID badges\n\n## Funding\n\n\u003e TODO: Add in statement about FM funding from BS.\n\n\n## Instructions to run the code\n\n### To download code and run locally\n\n#### Downloading the code\n\nEither clone the repository using git or click on the green \"code\" button and select \"Download Zip\".\n\n```bash\ngit clone https://github.com/pythonhealthdatascience/stress_update\n```\n\n\u003e this assumes you have installed git and [setup SSH](https://docs.github.com/en/authentication/connecting-to-github-with-ssh)\n\n#### Installing dependencies\n\nAll dependencies can be found in [`environment.yml`]() and are pulled from conda-forge.  To run the code locally, we recommend installing [miniforge](https://github.com/conda-forge/miniforge).\n\n\u003e miniforge is FOSS alternative to Anaconda and miniconda that uses conda-forge as the default channel for packages. It installs both conda and mamba (a drop in replacement for conda) package managers.  We recommend mamba for faster resolving of dependencies and installation of packages. \n\nnavigating your terminal (or cmd prompt) to the directory containing the repo and issuing the following command:\n\n\u003e if you are using conda then replace `mamba` with `conda`.\n\n```\nmamba env create -f environment.yml\n```\n\n\nActivate the mamba environment using the following command:\n\n```\nmamba activate stress\n```\n\n## Auto-formatting code in notebooks\n\nThe `stress` environment contains code linting and formatting tools: `nbqa`, `flake8` and `black`. Use `nbqa` and `black` to autoformat jupyter notebooks from a terminal or cmd prompt:\n\n```bash\nnbqa black notebooks/\u003cinsert-notebook-name\u003e.ipynb\n```\n\nUse `flake8` to issue a report about code quality:\n\n```bash\nnbqa flake8 notebooks/\u003cinsert-notebook-name\u003e.ipynb\n```\n\u003e Some notes on linting code: https://www.pythonhealthdatascience.com/content/001_setup/prereq/05_pep8.html\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpythonhealthdatascience%2Fstress_update","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpythonhealthdatascience%2Fstress_update","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpythonhealthdatascience%2Fstress_update/lists"}