... | ... | @@ -12,7 +12,7 @@ This will download a Docker image based on [Arch GNU/Linux](https://www.archlinu |
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After the image is pulled, you can start an interactive python shell in the container by running:
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```bash
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docker run -it tiagopeixoto/graph-tool ipython
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docker run -it -u user -w /home/user tiagopeixoto/graph-tool ipython
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```
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which will give you a Python 3 environment with `graph-tool` installed:
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```
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```
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and then run the container with
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```bash
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docker run -ti --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix tiagopeixoto/graph-tool ipython
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docker run -ti -u user -w /home/user --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix tiagopeixoto/graph-tool ipython
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```
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## Jupyter notebooks
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To run jupyter notebooks from inside the docker image, you need to forward the necessary ports to the container, so that your native browser can connect to it at http://localhost:8888/:
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```bash
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docker run -p 8888:8888 -p 6006:6006 tiagopeixoto/graph-tool jupyter-notebook
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docker run -p 8888:8888 -p 6006:6006 -u user -w /home/user tiagopeixoto/graph-tool jupyter-notebook --ip 0.0.0.0
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```
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(MacOS and Windows users still need to bind the above ports in the VM, as described [here](https://stackoverflow.com/questions/33636925/how-do-i-start-tensorflow-docker-jupyter-notebook))
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## Modifying the docker image
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If you are interested in modifying or extending the image, you can download the [Dockerfile](/uploads/caf47baea1a337cab16484e59a99615a/Dockerfile).
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If you are interested in modifying or extending the image, you can download the [Dockerfile](/uploads/6f653264723c567aa98e3b7422d0eb95/Dockerfile).
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# Native installation
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... | ... | |