Substrate

Substrate is a tool that allows you to automate the process of deploying visualization tools to different computing environments.

Supported Visualization tools

Supported Environments

Any computing environment capable of running Docker Swarm is a valid deployment target.

Requirements

This tool relies upon Docker Swarm. In order for it to work, the following assumptions are made of each compute node (for AWS deployments, these requirements are handled automatically):

  • Docker Engine must be installed.
  • The ports needed by Docker Swarm must be open for communication between nodes. Please review the Docker Swarm docs for more information.
  • You must be able to connect to each node over SSH with a private key available in ~/.ssh.

Getting Started

To install run

pip install seelabutk-substrate

then launch a visualization tool via a CLI using

substrate 'tool_name' start
substrate 'tool_name' stop

or via Python using

from substrate import Substrate

stack = Substrate('tool_name')
stack.start()
stack.stop()

Valid tool names:

  • hello_world (this will just host the provided data sources as static files)
  • nc_slicer
  • ospray_studio
  • tapestry
  • braid

Configuration

Substrate is configured using substrate.config.yaml. The tool will look for this file starting in your current working directory then look for it in parent folders. You can also provide a path with

substrate tapestry start -c /path/to/substrate.config.yaml

or

stack = Substrate('tool_name', path='path/to/substrate.config.yaml')

The options for the configuration file can be found here.

Each tool has static files that are needed to run it. Defaults are provided, but if needed or desired they can be modified. Here are links to get the default files for Tapestry and Braid.

For more information on configuring each tool, please refer to each tools documentation:

Uploading to PyPI

To upload to prepare a new release, run the following commands:

python -m build
python -m twine upload dist/*

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.9.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for evilkermit from gravatar.com evilkermit

Credits

Author: John Duggan

License

CC-BY-4.0

Requires

Python >=3.7

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

seelabutk-substrate-1.2.0.tar.gz (15.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

seelabutk_substrate-1.2.0-py3-none-any.whl (20.0 kB view details)

Uploaded Python 3

File details

Details for the file seelabutk-substrate-1.2.0.tar.gz.

File metadata

  • Download URL: seelabutk-substrate-1.2.0.tar.gz
  • Upload date:
  • Size: 15.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.10.5

File hashes

Hashes for seelabutk-substrate-1.2.0.tar.gz
Algorithm Hash digest
SHA256 b5b649bb5395fac47e33e26014314b1a2c6a2b21a41a3c30535d19f899f6688e
MD5 fa02fc3779de5b112a2bb989f199c928
BLAKE2b-256 ab5a361412b60cc5bda7253bd4503ee66d237d17182e3d0ab505d2345d5d3d5b

See more details on using hashes here.

File details

Details for the file seelabutk_substrate-1.2.0-py3-none-any.whl.

File metadata

File hashes

Hashes for seelabutk_substrate-1.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 f49c4a7bb98ba82b4ed881cd84fb4ea395b21b777f69325ebd4ca2e009d80131
MD5 97cf42275790f0d33221634c8c2e3abb
BLAKE2b-256 006773969c2c9c94e533d63039623e7178607013683c7be53504e799dfcd2711

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page