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Docker images to support Machine Learning (ML) in Python
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- [ ![ Docker Cloud Build Status] ( https://img.shields.io/docker/cloud/build/artificialintelligence /python-jupyter )] ( https://hub.docker.com/repository/docker/artificialintelligence /python-jupyter/general )
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+ [ ![ Docker Cloud Build Status] ( https://img.shields.io/docker/cloud/build/infrahelpers /python-jupyter )] ( https://hub.docker.com/repository/docker/infrahelpers /python-jupyter/general )
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[ ![ Docker Repository on Quay] ( https://quay.io/repository/artificialintelligence/python-jupyter/status " Docker Repository on Quay ")] ( https://quay.io/repository/artificialintelligence/python-jupyter )
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# Overview
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[ That project] ( https://github.com/machine-learning-helpers/docker-python-jupyter )
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produces
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- [ Docker images] ( https://hub.docker.com/repository/docker/artificialintelligence /python-jupyter ) ,
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+ [ Docker images] ( https://hub.docker.com/repository/docker/infrahelpers /python-jupyter ) ,
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which provide ready-to-use Artificial Intelligence (AI) / Machine Learning (ML)
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Python Jupyter environments on a few well known and stable Linux distributions
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- (_ e.g._ , [ CentOS 7 ] ( https://wiki.centos.org/Manuals/ReleaseNotes/CentOS7 ) ,
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- [ CentOS 8 ] ( https://wiki.centos.org/Manuals/ReleaseNotes/CentOSLinux8 ) ,
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- [ Debian 9 (Stretch )] ( https://www.debian.org/releases/stretch / ) ,
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+ (_ e.g._ , [ CentOS 8 ] ( https://wiki.centos.org/Manuals/ReleaseNotes/CentOSLinux8 ) ,
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+ [ CentOS 7 ] ( https://wiki.centos.org/Manuals/ReleaseNotes/CentOS7 ) ,
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+ [ Debian 11 (Bullseye )] ( https://www.debian.org/releases/bullseye / ) ,
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[ Debian 10 (Buster)] ( https://www.debian.org/releases/buster/ ) ,
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+ [ Ubuntu 20.04 LTS (Focal Fossa)] ( https://releases.ubuntu.com/20.04/ ) ,
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[ Ubuntu 18.04 LTS (Bionic Beaver)] ( https://releases.ubuntu.com/18.04/ ) and
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- [ Ubuntu 20 .04 LTS (Focal Fossa )] ( https://releases.ubuntu.com/20 .04/ ) ).
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+ [ Ubuntu 16 .04 LTS (Xenial Xerus )] ( https://releases.ubuntu.com/16 .04/ ) ).
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The Docker images just add some Jupyter notebook and data set samples
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on top of other
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- [ general purpose C++/Python Docker images] ( https://hub.docker.com/repository/docker/cpppythondevelopment/base ) ,
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+ [ general purpose C++/Python Docker images] ( https://hub.docker.com/repository/docker/infrahelpers/cpppython/general ) ,
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produced by a
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[ dedicated project on GitHub] ( https://github.com/cpp-projects-showcase/docker-images )
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and available on
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- [ Docker Hub] ( https://hub.docker.com/repository/docker/cpppythondevelopment/base )
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+ [ Docker Hub] ( https://hub.docker.com/repository/docker/infrahelpers/cpppython/general )
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too.
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The Python virtual environments are installed thanks to Pyenv and ` pipenv ` ,
@@ -59,16 +60,19 @@ clusters or services (_e.g._,
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[ IBM/RedHat OpenShift v4] ( https://www.redhat.com/en/openshift-4 ) or
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[ Google GKE] ( https://cloud.google.com/kubernetes-engine ) ).
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Those images are available on their own
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- [ Docker Hub repository] ( https://hub.docker.com/repository/docker/artificialintelligence /python-light/ ) .
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+ [ Docker Hub repository] ( https://hub.docker.com/repository/docker/infrahelpers /python-light/ ) .
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## See also
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- * Python Data Science Docker images for every day use:
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+ * Python Data Science images for every day use:
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+ On GitHub: https://github.com/cpp-projects-showcase/docker-images
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- + On Docker Hub: https://hub.docker.com/repository/docker/artificialintelligence /python-jupyter
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- * Production-ready Python Data Science Docker images:
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+ + On Docker Hub: https://hub.docker.com/repository/docker/infrahelpers /python-jupyter
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+ * Production-ready Python Data Science images:
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+ On GitHub: https://github.com/machine-learning-helpers/docker-python-light
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- + On Docker Hub: https://hub.docker.com/repository/docker/artificialintelligence/python-light
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- * General purpose C++/Python Docker images:
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+ + On Docker Hub: https://hub.docker.com/repository/docker/infrahelpers/python-light
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+ * Production-ready Python cloud images:
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+ + On GitHub: https://github.com/cloud-helpers/cloud-python-images
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+ + On Docker Hub: https://hub.docker.com/repository/docker/infrahelpers/cloud-python
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+ * General purpose C++/Python images:
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+ On GitHub: https://github.com/cpp-projects-showcase/docker-images
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+ On Docker Hub: https://hub.docker.com/repository/docker/cpppythondevelopment/base
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* Native Docker Python images:
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# Simple use
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* Download the Docker image for your preferred Linux distribution (where
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- ` <linux-distrib> ` is one of ` centos7 ` , ` centos8 ` , ` debian9 ` , ` debian10 ` ,
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- ` ubuntu1804 ` or ` ubuntu2004 ` ):
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+ ` <linux-distrib> ` is one of ` centos8 ` , ` centos7 ` , ` debian11 ` , ` debian10 ` ,
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+ ` ubuntu2004 ` , ` ubuntu1804 ` or ` ubuntu1604 ` ):
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``` bash
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- $ docker pull artificialintelligence /python-jupyter:< linux-distrib>
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+ $ docker pull infrahelpers /python-jupyter:< linux-distrib>
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```
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## With the Jupyter notebook and data set samples provided by the Docker images
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* Launch Jupyter Lab within the Docker image (where ` <port> ` corresponds
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to the local port on which Jupyter Lab is launched; the default is 8888):
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``` bash
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- $ docker run -d -p < port> :8888 artificialintelligence /python-jupyter:< linux-distrib>
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+ $ docker run -d -p < port> :8888 infrahelpers /python-jupyter:< linux-distrib>
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```
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## With your own Jupyter notebooks and data sets
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* Launch Jupyter Lab within the Docker image (where ` <port> ` corresponds
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to the local port on which Jupyter Lab is launched; the default is 8888):
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``` bash
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- $ docker run -d -p < port> :8888 -v ${PWD} /notebook/induction:/notebook -v ${PWD} /data/induction:/data artificialintelligence /python-jupyter:< linux-distrib>
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+ $ docker run -d -p < port> :8888 -v ${PWD} /notebook/induction:/notebook -v ${PWD} /data/induction:/data infrahelpers /python-jupyter:< linux-distrib>
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```
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## Interact with Jupyter Lab in a Web browser
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* Build the Docker image (the ` --squash ` option is only available on
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[ Docker Edge] ( http://docs.docker.com/edge/ ) , as of end of 2018):
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``` bash
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- $ docker build -t artificialintelligence /python-jupyter:< linux-distrib> --squash < linux-distrib> /
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+ $ docker build -t infrahelpers /python-jupyter:< linux-distrib> --squash < linux-distrib> /
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$ docker images
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REPOSITORY TAG IMAGE ID CREATED SIZE
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- artificialintelligence /python-jupyter linux-distrib 33a1ad533140 About a minute ago 2.29GB
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+ infrahelpers /python-jupyter linux-distrib 33a1ad533140 About a minute ago 2.29GB
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```
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* (Optional) Push the newly built image to Docker Cloud.
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[ a change on GitHub] ( https://github.com/machine-learning-helpers/docker-python-jupyter/commits/master ) )
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``` bash
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$ docker login
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- $ docker push artificialintelligence /python-jupyter-manual:< linux-distrib>
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+ $ docker push infrahelpers /python-jupyter-manual:< linux-distrib>
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```
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* Shutdown the Docker image
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