{"id":16853629,"url":"https://github.com/sim51/docker-data-science-training","last_synced_at":"2025-04-10T23:03:52.529Z","repository":{"id":142401784,"uuid":"172760677","full_name":"sim51/docker-data-science-training","owner":"sim51","description":null,"archived":false,"fork":false,"pushed_at":"2019-04-16T09:58:15.000Z","size":4,"stargazers_count":2,"open_issues_count":0,"forks_count":5,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-10T23:03:47.856Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Shell","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sim51.png","metadata":{"files":{"readme":"README.adoc","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2019-02-26T17:47:35.000Z","updated_at":"2023-03-20T12:24:14.000Z","dependencies_parsed_at":null,"dependency_job_id":"1c01c912-82f8-441f-9d84-00506bde6a75","html_url":"https://github.com/sim51/docker-data-science-training","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sim51%2Fdocker-data-science-training","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sim51%2Fdocker-data-science-training/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sim51%2Fdocker-data-science-training/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sim51%2Fdocker-data-science-training/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sim51","download_url":"https://codeload.github.com/sim51/docker-data-science-training/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248312142,"owners_count":21082638,"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":"2024-10-13T13:52:31.820Z","updated_at":"2025-04-10T23:03:52.517Z","avatar_url":"https://github.com/sim51.png","language":"Shell","funding_links":[],"categories":[],"sub_categories":[],"readme":"= Docker environment for the data science training\n\n== Launch the environment\n\n=== On all environment\n\n==== Step 1 : Download neo4j plugins\n\nFirst you need to download the latest version of those plugins, and put them inside the `plugins` directory  : \n\n* APOC : https://github.com/neo4j-contrib/neo4j-apoc-procedures/releases/\n* Graph Algos : https://github.com/neo4j-contrib/neo4j-graph-algorithms/releases/\n  \nFor example, the current when I write this file are : \n\n* https://github.com/neo4j-contrib/neo4j-graph-algorithms/releases/download/3.5.3.1/graph-algorithms-algo-3.5.3.1.jar\n* https://github.com/neo4j-contrib/neo4j-apoc-procedures/releases/download/3.5.0.2/apoc-3.5.0.2-all.jar \n\n==== Step 2 : Clone the training repository\n\nIn this directory, just clone the training repository : `git clone https://github.com/mneedham/data-science-training`\n\n==== Step 3 : Launch docker \n\nYou just have to run `docker-compose up`\n\n=== On linux\n\nOn linux you can directly run the script `run.sh`, it will download everything you need and also run the `docker-compose up` command for you.\n\n\n== Use the environment\n\nYour Neo4j database is available on your laptop at this url http://localhost:7474/browser with the following login/password -\u003e neo4j / admin\nBut inside other container (like the jupyter one) your should use `bolt://data-science-training-neo4j`.\n\nJupyter is available at the following url http://localhost:8888/\nTo login, you will need to search the token in the docker logs something. You should see something similar to that : `[I 17:39:57.299 NotebookApp] http://(9d6f11a3c1a1 or 127.0.0.1):8888/?token=04833158d59cd1ac094602f9b097822a904fa285607e1c59`\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsim51%2Fdocker-data-science-training","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsim51%2Fdocker-data-science-training","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsim51%2Fdocker-data-science-training/lists"}