acdc-aws-etl-pipeline

Infrastructure and code for the ACDC ETL pipeline and data operations in AWS

Ingestion

DBT

Release Management

Deploying the dictionary

e.g. to testing

# Example 
bash services/dictionary/pull_dict.sh <raw_dictionary_url>
bash services/dictionary/upload_dictionary.py <local_dictionary_path> <s3_target_uri>

# implementation
VERSION=v0.6.1
bash services/dictionary/pull_dict.sh "https://raw.githubusercontent.com/AustralianBioCommons/acdc-schema-json/refs/tags/${VERSION}/dictionary/prod_dict/acdc_schema.json"
python3 services/dictionary/upload_dictionary.py "services/dictionary/schemas/acdc_schema_${VERSION}.json" s3://gen3schema-cad-uat-biocommons.org.au/cad.json

Generating synthetic metadata

  • Run this script to generate synthetic metadata for the studies in the dictionary
# this will generate 30 samples for AusDiab_Simulated and 60 samples for Baker-Biobank_Simulated
bash services/synthetic_data/generate_synth_metadata.sh --studies "AusDiab_Simulated,Baker-Biobank_Simulated" --permute-max-samples "30,60"

uploading synthetic metadata to sheepdog

  • Run this script to upload synthetic metadata to sheepdog
python3 services/synthetic_data/upload_synth_metadata_sheepdog.py

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.5.4)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for harjo391 from gravatar.com harjo391

Credits

Author: JoshuaHarris391

Requires

Python <4.0.0, >=3.9.5

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