The EdgePrediction library depends on several other Python libraries. A Docker image is provided with all the necessary dependencies preconfigured and is the easiest way to start. Alternatively, a full list is provided below.
- igraph
- numpy
- scipy
- rpy2
The easiest way to get set up is to use a distribution such as anaconda, and then install graph and rpy2 following the same steps as for the Docker image below.
A docker image is provided here (https://hub.docker.com/r/dmb57 /python-image).
Start docker and connect to default machine:
docker-machine start default eval "$(docker-machine env default)"
pull the anaconda image:
docker pull continuumio/anaconda
run the anaconda image and note the id:
docker run -it continuumio/anaconda
In this example, the id is #d60ea25a91b6.
Now we’re working inside the image shell. Install build tools:
apt-get install build-essential
Install igraph with pip:
pip install -i https://pypi.anaconda.org/pypi/simple python-igraph
Install R and rpy2 with conda:
conda install -c r rpy2
To commit these changes to the image, first exit the image shell:
exit
Now commit changes to the base image. Replace YOUR NAME with your name, in quotes. Replace d60ea25a91b6 with the id you noted down above. Replace python-image with whatever you want your new image to be called:
docker commit -m “installed igraph, r, rpy2" -a “YOUR NAME“ d60ea25a91b6 python-image
You should get a sha256 hash in response. To check the image has been saved, run:
docker images
Somewhere in the output you should see your image:
REPOSITORY TAG IMAGE ID CREATED SIZE python-image latest fd36318d71d9 48 seconds ago 2.345 GB
Now you can run this image as:
docker run -it python-image