... | ... | @@ -76,7 +76,7 @@ and then run the container with |
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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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### 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/. You need first to start an interactive shell session
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```bash
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... | ... | @@ -90,6 +90,18 @@ and then start the notebook server |
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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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## Development snapshots
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Continuous snapshots of the most current development version of `graph-tool` are available as the [graph-tool-git](https://hub.docker.com/r/tiagopeixoto/graph-tool-git) docker repository. This repository is updated automatically after every commit is made to the upstream git repository.
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The development version can be installed simply by running:
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```bash
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docker pull tiagopeixoto/graph-tool-git
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```
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And following the same usage instructions as above.
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**WARNING:** The development version may contain bugs! Prefer the stable releases whenever possible.
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# Native installation
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Python modules are usually very easy to install, typically requiring nothing more that `pip install <package>` for basically any operating system. For `graph-tool`, however, the situation is different. This is because, in reality, `graph-tool` is a C++ library wrapped in Python, and it has many C++ dependencies such as [Boost](http://www.boost.org/), [CGAL](http://www.cgal.org/) and [expat](http://expat.sourceforge.net/), which are not installable via Python-only package management systems such as [pip](http://www.pip-installer.org/). Because the module lives between the C++ and Python worlds, its installation is done more like a C++ library rather than a typical python module. This means it inherits some of the complexities common of the C++ world that some Python users do not expect.
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... | ... | |