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Installation
BlobToolKit can be installed using pip or run as a container using Docker/Singularity. For viewing datasets, a local instance of the Viewer can be also be set up using the blobtoolkit-viewer and blobtoolkit-api binaries.
The quickest way to install and use BlobToolKit is using pip install. We recommend first setting up a new conda environment with python=3.9. The advantage of conda is that everything can be installed in a separate user directory, even on a cluster, without affecting anything else installed.
## Install Conda
Conda can be installed on the command line using the Miniconda installer:
curl -L https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh > Miniconda3.sh; chmod +x Miniconda3.sh; ./Miniconda3.sh
You will need to open a new terminal window before using conda as the commands will not be available in the current session
To create and activate a new conda environment called btk with python=3.9:
conda create -y -n btk -c conda-forge python=3.9
conda activate btk
To install blobtoolkit:
pip install "blobtoolkit[full]"
For a more compact install (without pipeline or viewer hosting options) use:
pip install blobtoolkit
To test that the installation worked, type blobtools -h and you should see the help text for that command.
Fetch the latest binaries for macOS or linux from the latest release page:
RELEASE=4.1.5
PLATFORM=linux # or macos
curl -L https://github.com/blobtoolkit/blobtoolkit/releases/download/${RELEASE}/blobtoolkit-api-${PLATFORM} > blobtoolkit-api
curl -L https://github.com/blobtoolkit/blobtoolkit/releases/download/${RELEASE}/blobtoolkit-viewer-${PLATFORM} > blobtoolkit-viewer
chmod 755 blobtoolkit-*
Then start the API with:
BTK_API_PORT=8880 BTK_PORT=8881 BTK_FILE_PATH=/path/to/blobtoolkit/datasets ./blobtoolkit-api
And the viewer with:
BTK_API_PORT=8880 BTK_PORT=8881 ./blobtoolkit-viewer
Then open the viewer in a browser at http://localhost:8881/view/all
If not set the port numbers default to BTK_API_PORT=8000 and BTK_PORT=8001