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# Using the LSST DM Stack from Python - Firefly edition
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The Jupyter Notebook in this repository is a self-guided tutorial that walks the reader through writing a simple processing script using LSST Data Management Python libraries. This tutorial was originally set up for the LSST2017 Project
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and Community Workshop.
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The `tutorial-firefly.ipynb` notebook is a modified form of the notebook that gives Firefly equivalents to the
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matplotlib displays used in the original version. This notebook is based on the "answers" version of the tutorial,
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in which the solutions to the exercises have been included.
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As of mid-December 2017, the necessary Firefly packages are included in `lsst_distrib`. It is possible to
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run the notebook in a Docker container, following the
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[developer instructions for Docker](https://pipelines.lsst.io/install/docker.html#docker-tags).
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Here are Docker commands used to test this notebook:
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```
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docker run -itd -p 9745:9745 -v `pwd`:/home/vagrant/mnt --name lsst2 lsstsqre/centos:7-stack-lsst_distrib-d_2017_12_14
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docker exec -it lsst2 /bin/bash
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```
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Then in the shell inside the container:
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```
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source loadLSST.bash
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conda install jupyter notebook ipython
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cd /home/vagrant/mnt/lsst2017
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jupyter notebook --ip 0.0.0.0 --port 9745
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```
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Then on the host machine, open a browser to [http://localhost:9745](http://localhost:9745).
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