4.[Submit a pull request](https://github.com/PointCloudLibrary/pcl/wiki/A-step-by-step-guide-on-preparing-and-submitting-a-pull-request)(PR) with your changes.
4.[Submit a pull request](https://github.com/PointCloudLibrary/pcl/wiki/A-step-by-step-guide-on-preparing-and-submitting-a-pull-request)(PR) with your changes.
5. Watch for Travis to report a build success or failure for your PR on GitHub.
5. Watch for Travis to report a build success or failure for your PR on GitHub.
6. Discuss changes with the maintainers and address any build issues. Version conflicts are the most common problem. You may need to upgrade additional packages to fix build failures.
6. Discuss changes with the maintainers and address any build issues. Version conflicts are the most common problem. You may need to upgrade additional packages to fix build failures.
## Notes
In order to help identifying packages that can be updated you can use the following helper tool.
It will list all the packages installed in the `Dockerfile` that can be updated -- dependencies are filtered to focus only on requested packages.
```bash
$ make check-outdated/base-notebook
# INFO test_outdated:test_outdated.py:80 3/8 (38%) packages could be updated
**You should only enable `sudo` if you trust the user and/or if the container is running on an
**You should only enable `sudo` if you trust the user and/or if the container is running on an
isolated host.**
isolated host.** See [Docker security documentation](https://docs.docker.com/engine/security/userns-remap/) for more information about running containers as `root`.
## Using `pip install` or `conda install` in a Child Docker image
## Using `pip install` or `conda install` in a Child Docker image
[protobuf](https://developers.google.com/protocol-buffers/docs/pythontutorial), and [xlrd](http://www.python-excel.org/) packages
[protobuf](https://developers.google.com/protocol-buffers/docs/pythontutorial), and [xlrd](http://www.python-excel.org/) packages
*[ipywidgets](https://ipywidgets.readthedocs.io/en/stable/)for interactive visualizations in Python notebooks
*[ipywidgets](https://ipywidgets.readthedocs.io/en/stable/)and [ipympl](https://github.com/matplotlib/jupyter-matplotlib) for interactive visualizations and plots in Python notebooks
*[Facets](https://github.com/PAIR-code/facets) for visualizing machine learning datasets
*[Facets](https://github.com/PAIR-code/facets) for visualizing machine learning datasets