[{"_1":2,"_200":-5,"_201":-5},"loaderData",{"_3":4,"_13":14,"_20":21,"_173":174},"root",{"_5":-5,"_6":-7,"_7":8,"_9":-7,"_10":11,"_12":-7},"currentUser","primaryEmail","siteVerification","6LeIxAcTAAAAAJcZVRqyHh71UMIEGNQ_MXjiZKhI","toast","enableDev",false,"incidentStatus","routes/_layout",{"_15":-5,"_16":11,"_17":11,"_18":19},"username","isBillingDecouplingSeatCount","isSearchBoxExperimentEnabled","isAskGordonEnabled",true,"routes/_layout.r.$namespace.$reponame",{"_22":23,"_24":-5,"_25":11,"_26":11,"_27":28,"_29":30,"_31":-5,"_32":11,"_33":34,"_90":91,"_114":115,"_166":-5,"_167":11,"_168":11,"_169":11,"_170":-5,"_171":172},"canonicalUrl","https://hub.docker.com/r/unjudge/inginious-c-datascience/tags","mcpServer","canSeeDockerfile","canSeeAutobuilds","namespace","unjudge","reponame","inginious-c-datascience","cloudBuildSource","isAutobuildsAvailable","repo",{"_35":36,"_45":46,"_48":49,"_50":51,"_52":11,"_53":54,"_55":56,"_57":58,"_38":30,"_27":28,"_60":61,"_62":47,"_63":64,"_65":66,"_67":68,"_69":-5,"_70":64,"_71":72,"_73":11,"_74":28,"_75":76,"_81":11,"_82":83,"_87":28,"_88":89},"categories",[37,42],{"_38":39,"_40":41},"name","Languages & frameworks","slug","languages-and-frameworks",{"_38":43,"_40":44},"Data science","data-science","content_types",[47],"image","date_registered","2019-09-05T20:17:54.781638Z","description","","is_private","last_updated","2025-03-31T16:54:21.571857Z","last_modified","2024-10-16T13:48:34.145251Z","media_types",[59],"application/vnd.docker.container.image.v1+json","pull_count",2151,"repository_type","star_count",0,"status",1,"status_description","active","source","collaborator_count","full_description","# UNCode containers\n\n[![Build Status](https://travis-ci.com/JuezUN/INGInious-containers.svg?branch=master)][travis_url]\n[![License](https://img.shields.io/github/license/JuezUN/INGInious-containers?style=plastic)][license_url]\n[![Contributors](https://img.shields.io/github/contributors/JuezUN/INGInious-containers?style=plastic)][contributors_url]\n[![GitHub issues](https://img.shields.io/github/issues/JuezUN/INGInious-containers?style=plastic)][issues_url]\n[![Codacy Badge](https://app.codacy.com/project/badge/Grade/1ab17130fe6d4f14b79c933c059b3e4c)][codacy_url]\n[![CLA assistant](https://cla-assistant.io/readme/badge/JuezUN/INGInious-containers)][cla_url]\n[![Gitter](https://badges.gitter.im/uncode-unal/community.svg)][gitter_url]\n\nThis repository contains all different grading containers for UNCode which are available on [Docker Hub][docker_hub_uncode].\n\nNot all the containers are used for UNCode, some of them where created for [INGInious-containers][inginious_url], thus,\nonly the ones we have developed and use are explained here.\n\n## Containers:\n\nThe image below shows the hierarchy of the different containers:\n\n![containers hierarchy diagram](images/UNCode-containers-diagram.png)\n\n### [unjudge/inginious-c-base][unjudge/inginious-c-base_url]\n\nThe code related to this container is in the [main repository][base_container_github_url]. This container contains all\n the logic to run the submissions and send back the feedback to the student.\n\n### [unjudge/uncode-c-base][unjudge/uncode-c-base_url]\n\nThis container is not directly in charge of evaluating a student's submission, it contains code that all the other\n containers use to evaluate the submission in the correct environment. The code is in `grading/uncode`. This container\n also contains the translations for different grading containers\n\n### [unjudge/inginious-c-multilang][unjudge/inginious-c-multilang_url]\n\nThis container is in charge of evaluating C/C++, Java 7/8 and Python3 submissions as well as custom input executions.\n Here are accepted either single code submission or file project submissions. The code is in `grading/multilang`.\n\n### [unjudge/inginious-c-datascience][unjudge/inginious-c-datascience_url]\n\nAs this container inherits from the multilang container, it does not add any different way to evaluate the submission,\n the difference of this container is that it allows submission that uses python modules commonly used in data science,\n such as Pandas, Numpy, among others. The `Dockerfile` is in `grading/data_science`.\n\n### [unjudge/inginious-c-notebook][unjudge/inginious-c-notebook_url]\n\nContainer in charge of grading notebook submissions, for that, it receives a `.ipynb` file with the student's code. Thus,\n this is a different grading environment which can be selected in the task settings on UNCode. The code is located in\n `grading/notebook`. \n\n\n### [unjudge/hdl-uncode][unjudge/hdl-uncode_url]\n\nSubmissions with Verilog and VHDL code are graded inside this container. The code is in `grading/hdl`.\n\n## Getting started\n\n### Built with\n\nEach mentioned grading environment is developed with [Python (with pip) 3.5+][python_url].\n\n### Build containers\n\nTo build a container to test changes, run the next command:\n```bash\ndocker build -t ./grading/\n```\n\n\n### Utility Scripts\n\nIn order to facilitate testing, development and deployment, there are several different ways to build and manage the images on this repository.\nIf you want to clean build an image (deleting the image if it exists before build) use ```clean-build-container.sh```\n\n```bash\n./clean-build-container.sh \n```\n\nIf you want to clean build all main images of uncode (uncode-base, multilang, hdl, notebook, data science)(deleting the images if they exists before build) use\n```clean-build-main-containers.sh```\n\n```bash\n./clean-build-main-containers.sh\n```\n\nIf you want to manage the images in order to manipulate the registries in DockerHub, run the following scripts:\n\nTo pull all the grading images with the specified tag (if flag -t i not passed the default tag is latest):\n```bash\n./pull-registry-images.sh -t \n```\nTo tag all the grading images with the specified tag (if flag -t i not passed the default tag is latest):\n```bash\n./tag-registry-images.sh -t \n```\nTo push all the grading images with the specified tag to unjudge registry on DockerHub(if flag -t i not passed the default tag is latest):\n```bash\n./push-registry-images.sh -t \n```\n\n\n### Run tests\n\nTests have been developed for the multilang container, in case you they have changed, you can run them as follows:\n```bash\ndocker run -v /grading/:/python_lib/grading \\\n -v /tests/:/python_lib/tests \\\n ingi/inginious-c-multilang /bin/sh -c \"mkdir -p /task/student; export PYTHONPATH=/python_lib:$PYTHONPATH; cd /python_lib && pip3 install pytest && pytest tests\"\n```\nWhere `` is the absolute path the multilang container code, for instance: `/home/user/Desktop/INGInious-containers/grading/multilang`.\n It must be the absolute path, otherwise it will fail to start.\n \n### Translate messages\n\nIt is possible to translate the messages returned from the containers. This adds support for internationalization (i18n). This is quite similar to the way it is done in the frontend.\nThis is done using the module `gettext` which installs the function `_()` in python to make it accessible in all the code, also, the messages are extracted and compiled using `pybabel`.\nThe i18n related files per language, are located in `grading/uncode/lang/`.\n\n**Note**: Every time a Pull Request is done to master, an automatic check is done to verify that the i18n files are up to date.\n\n#### 1. Mark a message as translatable\n\nTo mark a message as translatable, use the function `_(\"Message to translate\")`, which encloses the string to translate.\n\n#### 2. Extract marked messages\n\nTo extract the marked messages as translatable from the files, run the next command.\n\n```bash\npybabel extract -o messages.pot .\n```\n\n#### 3. Update messages \n\nTo update the messages files for each language, run the next command. After that, you can add translate the messages in the language you want to translate in `grading/uncode/lang/`.\n\n```bash\npybabel update -i messages.pot -d grading/uncode/lang/\n```\n\n#### 4. Compile messages \n\nFinally, the messages need to be compiled to correctly load the translations, run the next command:\n\n```bash\npybabel compile -d grading/uncode/lang/\n```\n\n## Documentation\n\nFor additional documentation, please refer to the [Wiki][uncode_wiki_url].\n\n## Roadmap\n\nSee the [UNCode GitHub Project][project_url] for a list of proposed features for UNCode, known issues and how they are\n being tackled.\n\n## Contributing\n\nGo to [CONTRIBUTING][contributing_url] to see the guidelines and how to start contributing to UNCode.\n\n## License\n\nDistributed under the AGPL-3.0 License. See [LICENSE][license_url] for more information.\n\n## Contact\n\nIn case of technical questions, please use the [gitter communication channel][gitter_url].\n\nIn case you want to host your course on our deployment, email us on: \n\nUNCode: \n\nProject page: \n\n[license_url]: https://github.com/JuezUN/INGInious-containers/blob/master/LICENSE\n[travis_url]: https://travis-ci.com/github/JuezUN/INGInious-containers\n[codacy_url]: https://www.codacy.com/gh/JuezUN/INGInious-containers/dashboard?utm_source=github.com&utm_medium=referral&utm_content=JuezUN/INGInious-containers&utm_campaign=Badge_Grade\n[uncode_url]: https://uncode.unal.edu.co/courselist\n[contributors_url]: https://github.com/JuezUN/INGInious-containers/graphs/contributors\n[issues_url]: https://github.com/JuezUN/INGInious-containers/issues\n[cla_url]: https://cla-assistant.io/JuezUN/INGInious-containers\n[gitter_url]:https://gitter.im/uncode-unal/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge\n[docker_hub_uncode]: https://hub.docker.com/r/unjudge\n[inginious_url]: https://github.com/UCL-INGI/INGInious-containers\n[python_url]: https://www.python.org/\n[uncode_wiki_url]: https://github.com/JuezUN/INGInious/wiki\n[project_url]: https://github.com/orgs/JuezUN/projects/3\n[contributing_url]: https://github.com/JuezUN/INGInious-containers/blob/master/CONTRIBUTING.md\n[base_container_github_url]: https://github.com/JuezUN/INGInious/tree/master/base-containers/base\n[unjudge/inginious-c-base_url]: https://hub.docker.com/r/unjudge/inginious-c-base\n[unjudge/uncode-c-base_url]: https://hub.docker.com/r/unjudge/uncode-c-base\n[unjudge/inginious-c-multilang_url]: https://hub.docker.com/r/unjudge/inginious-c-multilang\n[unjudge/inginious-c-datascience_url]: https://hub.docker.com/r/unjudge/inginious-c-datascience\n[unjudge/inginious-c-notebook_url]: https://hub.docker.com/r/unjudge/inginious-c-notebook\n[unjudge/hdl-uncode_url]: https://hub.docker.com/r/unjudge/hdl-uncode","has_starred","hub_user","immutable_tags_settings",{"_77":11,"_78":79},"enabled","rules",[80],".*","is_automated","permissions",{"_84":19,"_85":11,"_86":11},"read","write","admin","user","storage_size",64893370334,"orgData",{"_92":93,"_94":95,"_96":97,"_98":28,"_99":100,"_101":102,"_103":104,"_105":106,"_107":108,"_109":51,"_110":51,"_111":112,"_113":19},"id","12e9c3f9e99646cc834383d99cf6de0f","uuid","12e9c3f9-e996-46cc-8343-83d99cf6de0f","type","organization","orgname","full_name","UNCode","location","Bogotá, Colombia","company","Universidad Nacional De 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unjudge/inginious-c-datascience

Tags for unjudge/inginious-c-datascience