Skip to main content

Visualization recommendation using constraints

Project description

The Draco logo. A set of circles connected by lines depicting the draco star constellation.

Draco v2

PyPi Test code style black codecov Language grade: Python

Work in Progress

Draco is a formal framework for representing design knowledge about effective visualization design as a collection of constraints. You can use Draco to find effective visualization visual designs or validate visualization designs. Draco's constraints are implemented in based on Answer Set Programming (ASP) and solved with the Clingo constraint solver. We also implemented a way to learn weights for the recommendation system directly from the results of graphical perception experiment. Draco v2 is a much imprived version of the first iteration of Draco.

Documentation

Read about Draco in the online book at https://dig.cmu.edu/draco2/. In the documentation, we just refer to Draco without a version.

What's different from Draco v1?

  • Draco v2 is completely written in Python. No more need to run both Python and Node. We still use ASP for the knowledge base.
  • Generalized and extended chart specification format. The new format is more extensible with custom properties.
  • Suport for multiple views and view compostion.
  • High test-coverage, documentation, and updated development tooling.

Contributing

We welcome any input, feedback, bug reports, and contributions. You can learn about setting up your development environment in CONTRIBUTING.md.

Project details


Download files

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

Source Distribution

draco-2.0.0b2.tar.gz (22.2 kB view details)

Uploaded Source

Built Distribution

draco-2.0.0b2-py3-none-any.whl (25.5 kB view details)

Uploaded Python 3

File details

Details for the file draco-2.0.0b2.tar.gz.

File metadata

  • Download URL: draco-2.0.0b2.tar.gz
  • Upload date:
  • Size: 22.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.14 CPython/3.10.5 Darwin/22.0.0

File hashes

Hashes for draco-2.0.0b2.tar.gz
Algorithm Hash digest
SHA256 716a22e1231d10edbe1f754c8d6e4183b2f805d3a53ff294f3ae4850d7a4ef07
MD5 dfdbe163ef251087b5211726044c2c97
BLAKE2b-256 7cb1f7707decd669539601eac3cb0f716bc3de35414070f070f1e825c9a028eb

See more details on using hashes here.

File details

Details for the file draco-2.0.0b2-py3-none-any.whl.

File metadata

  • Download URL: draco-2.0.0b2-py3-none-any.whl
  • Upload date:
  • Size: 25.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.14 CPython/3.10.5 Darwin/22.0.0

File hashes

Hashes for draco-2.0.0b2-py3-none-any.whl
Algorithm Hash digest
SHA256 9fe95d893939276716603c78015d69242658040c2f19287aa7d7ce17e89c5551
MD5 5e0f40eed78e293a86806e7737c58d49
BLAKE2b-256 0305c54c0628b911782525c4de2484bf7a3568d0a698a7a85862426fa3ce694f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page