Installation¶

The installation process to get Georges up and running is relatively simple: the whole library is ready to be installed with pip and with conda.

However, as the georges submodules (in particular the georges.manzoni tracking code) are optimized to work with the Intel distribution for Python, detailed installation instructions are provided to install :mod: georges with Conda. This is the recommended way for the installation.

The Georges’ git repository is hosted on Github and on Gitlab (IBA internal).

Obtaining the Georges source code with Git¶

Simply clone the repository:

git clone https://github.com/chernals/georges

Or internally from IBA (replace username with your SSO login):

git clone git@gitlab.sw.goiba.net:username/georges.git

You can either stay on the bleeding-edge master branch or you can checkout a release tag:

git checkout tags/2018.2

Dependencies¶

A coherent set of dependencies is listed in the Conda environment.txt file as well as in the setup.py file (for setuptools and pip). In this way, installation using either conda or pip is possible. Note that the pip requirement file requirements.txt contains a single dot ., which refers to the dependency list provided in the setup.py file.

A typical user should not worry about those dependencies: they are properly managed either with conda (see next section) or with pip (see below).

Installation with Anaconda and the Intel Python Distribution libraries¶

The installation procedure which follows creates a conda environment based on the Intel distribution for Python with all the necessary dependencies included and managed via conda itself (this ensures that all the dependencies are, if possible, based on the Intel channel and not managed with pip). Georges is then installed using pip from that conda environment. The dependencies are coherent and the pip installation of Georges will find all the dependencies listed in setup.py to be already installed in the conda environment.

Install Conda for your operating system, follow the instructions for
- Linux
- macOS
- Windows
Obtain a copy of the git repository (see previous section)
Create a dedicated conda environment (default name is ipy3 for Intel Python 3)
```
cd path/to/georges
conda env create -f environment.yml
```
Activate the environment
```
conda activate ipy3
```

Install Georges using pip from the conda environment

# Typical installation
pip install .

# Install with pip in editable mode to get access to the modifications on the git repository
pip install -e .

Georges can be subsequently updated by running

cd path/to/georges
git pull origin master
pip install --upgrade georges

Installation with pip¶

In case Georges needs to be installed with the system Python or a Python installation that is not managed with conda, the following simple steps can be followed to use pip directly. All the dependencies are then managed with pip. Please note that this will typically not enable the Intel optimization, resulting in slower code execution for the :mod: manzoni module.

Obtain a copy of the git repository (see previous section)

Install Georges with pip:

# Typical installation
pip install .

# Install with pip in editable mode to get access to the modifications on the git repository
pip install -e .

Georges can be subsequently updated by running

cd path/to/georges
git pull origin master
pip install --upgrade georges

Using Georges with Jupyter Notebook¶

Georges can be used with Jupyter notebooks. No special care is needed.

If you installed Georges within the conda environment, simply run (note that it is not advised to put all your notebook within the git structure):

cd somewhere/good/for/notebooks
jupyter notebook

Georges distribution with Docker¶

TODO

A Docker image is made available to provide an easy access to a complete Jupyter Notebook + madx + georges environment.

Use the Dockerfile to build the image:

docker build .

or, to register the image as well:

docker build -t username/georges .

You can run a container with

docker run -it username/georges

then connect to http://localhost:8888 to access the Jupyter Notebook interface.

The image includes a complete Anaconda Python3 environment with the most common packages. The latest MAD-X development release is available in /usr/local/bin/madx.