Compression of Resources
It can be argued that applying compression to data resources can make data package publishing more cost-effective and sustainable. Compressing data resources gives publishers the benefit of reduced storage and bandwidth costs and gives consumers the benefit of shorter download times.
Implementations
- tabulator-py (Gzip and Zip support)
- datapackage-connector (Gzip support)
- datapackage-m (Gzip support)
Specification
All compressed resources MUST
have a path
that allows the compression
property to be inferred. If the compression can’t be inferred from the path
property (e.g. a custom file extension is used) then the compression
property MUST
be used to specify the compression.
Supported compression types:
- gz
- zip
Example of a compressed resource with implied compression:
Example of a compressed resource with the compression
property:
:::tip NOTE Resource properties e.g. bytes, hash etc apply to the compressed object — not to the original uncompressed object. :::