A library for creating assets from files on disk.

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  • License: MIT License (MIT)
  • Author: Alex Braun
  • Tags asset, project, data
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Project description

Hidebound

Documentation

Installation

pip install hidebound

For Developers

Installation

  1. Install docker
  2. Install docker-machine (if running on macOS or Windows)
  3. Ensure docker-machine has at least 4 GB of memory allocated to it.
  4. cd hidebound
  5. chmod +x bin/hidebound
  6. bin/hidebound start

The service should take a few minutes to start up.

Run bin/hidebound --help for more help on the command line tool.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for the-new-flesh from gravatar.com the-new-flesh

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Alex Braun
  • Tags asset, project, data
Classifiers

Release history Release notifications | RSS feed

0.34.2

0.34.0

0.33.5

0.33.4

0.33.3

0.33.2

0.33.1

0.33.0

0.32.4

0.32.2

0.31.5

0.31.4

0.31.1

0.30.0

0.29.0

0.26.1

0.25.1

0.25.0

0.24.0

0.23.3

0.23.2

0.23.1

0.23.0

0.22.4

0.22.3

0.22.2

0.22.0

0.21.1

0.20.1

0.19.1

0.19.0

0.18.1

0.16.2

0.16.1

0.16.0

0.15.10

0.15.9

0.15.8

0.15.6

0.15.5

0.15.2

0.14.0

0.13.0

0.12.5

0.12.4

0.12.3

0.12.2

0.12.1

0.12.0

0.11.0

0.10.8

0.10.7

0.10.6

0.10.5

0.10.4

0.10.3

0.9.7

0.9.2

0.9.1

0.9.0

0.8.9

0.8.8

0.8.7

0.8.5

0.8.4

0.8.2

0.8.1

0.8.0

0.7.4

0.6.4

0.4.2

This version

0.4.0

0.2.3

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Source Distribution

hidebound-0.4.0.tar.gz (17.4 kB view hashes)

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