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Data transformation framework for LinkML data models

Project description

Koza - a data transformation framework

Pyversions PyPi Github Action



Disclaimer: Koza is in beta - we are looking for testers!


  • Transform csv, json, yaml, jsonl, and xml and converting them to a target csv, json, or jsonl format based on your dataclass model.
  • Koza also can output data in the KGX format
  • Write data transforms in semi-declarative Python
  • Configure source files, expected columns/json properties and path filters, field filters, and metadata in yaml
  • Create or import mapping files to be used in ingests (eg id mapping, type mappings)
  • Create and use translation tables to map between source and target vocabularies


Koza is available on PyPi and can be installed via pip/pipx:

[pip|pipx] install koza


NOTE: As of version 0.2.0, there is a new method for getting your ingest's KozaApp instance. Please see the updated documentation for details.

See the Koza documentation for usage information

Try the Examples


Give Koza a local or remote csv file, and get some basic information (headers, number of rows)

koza validate \
  --file \
  --delimiter ' '

Sending a json or jsonl formatted file will confirm if the file is valid json or jsonl

koza validate \
  --file ./examples/data/ZFIN_PHENOTYPE_0.jsonl.gz \
  --format jsonl
koza validate \
  --file ./examples/data/ddpheno.json.gz \
  --format json


Run the example ingest, "string/protein-links-detailed"

koza transform \
  --source examples/string/protein-links-detailed.yaml \
  --global-table examples/translation_table.yaml

koza transform \
  --source examples/string-declarative/protein-links-detailed.yaml \
  --global-table examples/translation_table.yaml

Note: Koza expects a directory structure as described in the above example
with the source config file and transform code in the same directory:

├── ...
│   ├── your_source
│   │   ├── your_ingest.yaml
│   │   └──
│   └── some_translation_table.yaml
└── ...

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