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Welcome to the Diaper Data Team! 

Documentation on how to access the infant MongoDB data pipeline. 

Link to the google doc version:  https://docs.google.com/document/d/10mJzJUvUKSlWoK7e-n8yJ-766NdSm0LfIWmDjoRTBQ8/edit

Access infant-mongo-db & Data Pipeline: 

  1. Request an account for biohpc at https://biohpc.cornell.edu/lab/lab.asp
  2. Add or remove users from the access list:

Any user on the access list can add or remove users

[root@cbsujohnson ~]# docker1 access list

Container   UserID

infant-mongo-db ad596

infant-mongo-db sw835

infant-mongo-db ap689

[root@cbsujohnson ~]#

...

[root@cbsujohnson docker]# docker1 access

docker1 access list

   prints current access list

 

docker1 access remove <container name> <user id>

   Removes access for <user id> to <container name>

 

docker1 access add <container name> <user id>

   Adds access for <user id> to <container name>

     3. Steps to get access to the data pipeline

    1. ssh yournetid@cbsujohnson.biohpc.cornell.edu 
    2. enter your password
    3. screen -r 
    4. run the following command:

docker1 run \

  --volume "/workdir/yournetid/get_colors:/home/jovyan/work" \

  -p 8031:8888 \

  --env "GRANT_SUDO=yes" \

  --env "PATH=/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin" \

  --env "DEBIAN_FRONTEND=noninteractive" \

  --env "CONDA_DIR=/opt/conda" \

  --env "SHELL=/bin/bash" \

  --env "NB_USER=jovyan" \

  --env "NB_UID=1000" \

  --env "NB_GID=100" \

  --env "LC_ALL=en_US.UTF-8" \

  --env "LANG=en_US.UTF-8" \

  --env "LANGUAGE=en_US.UTF-8" \

  --env "HOME=/home/jovyan" \

  --env "XDG_CACHE_HOME=/home/jovyan/.cache/" \

  --label "maintainer"="Jupyter Project " \

  --interactive \

  "jupyter/tensorflow-notebook:20221209" \

  "start-notebook.sh"

...

Add the highlighted part of the token to: 

http://cbsujohnson.biohpc.cornell.edu:8031/lab?token=XXX

In this case, it would be:

http://cbsujohnson.biohpc.cornell.edu:8031/lab?token=c7007fb9f1a6aea3c4685328c35741c968d2e24e8821ce2d

Copy this link to your browser, you can then see the jupyter notebook page

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