koza 0.3.1

Data transformation framework for LinkML data models

Koza - a data transformation framework

Documentation

Disclaimer: Koza is in beta; we are looking for beta testers

Overview

• 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

Installation

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

[pip|pipx] install koza

Usage

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

Validate

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

koza validate \
  --file https://raw.githubusercontent.com/monarch-initiative/koza/main/examples/data/string.tsv \
  --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 \
  --compression gzip

Transform

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 (examples/ingest_name/ingest.yaml)