The tensorflow docker container is available at https://hub.docker.com/r/tensorflow/tensorflow/ to extend this container with additional libraries such as requests I'm aware of two options.
pip install requestspip install requests to the dockerFile that builds this container Is there an alternative option ? Something like creating the tensorflow/tensorflow container from a dockerFile and then installing requests on this container.
Reading How to extend an existing docker image? to accomplish this create a dockerFile with these contents ? :
FROM tensorflow/tensorflow
RUN pip install requests
Your original assertion is correct, create a new Dockerfile:
FROM tensorflow/tensorflow
RUN pip install requests
now build it (note that the name should be lower case):
docker build -t me/mytensorflow .
run it:
docker run -it me/mytensorflow
execute a shell in it (docker ps -ql gives us an id of the last container to run):
docker exec -it `docker ps -ql` /bin/bash
get logs from it:
docker logs `docker ps -ql`
The ability to extend other images is what makes docker really powerful, in addition you can go look at their Dockerfile:
https://github.com/tensorflow/tensorflow/tree/master/tensorflow/tools/docker
and start from there as well without extending their docker image, this is a best practice for people using docker in production so you know everything is built in-house and not by some hacker sneaking stuff into your infrastructure. Cheers! and happy building
you could enter the running container via:
docker exec -it CONTAINER_ID bin/bash
or if a name is set:
docker exec -it CONTAINER_NAME bin/bash