Python Databrary API Wrapper

This is a Python wrapper around databrary API

Installation

Run the following to install:

pip install pydatabrary

Usage

Databrary API

from pybrary import Pybrary

# Start a Databrary session
pb = Pybrary.get_instance('USERNAME', 'PASSWORD')
# You need to have permissions to the volume, to interact with it
volume_info = pb.get_volume_info(1)
print(volume_info)

Databrary Curation

Generate templates

This will generate for you template files where you can curate your new volume

from pybrary import Curation

# The number of records that you need for your ingest
payload = {
    'participant': 0,
    'pilot': 0,
    'exclusion': 0,
    'condition': 0,
    'group': 0,
    'task': 0,
    'context': 0,
}
records = Curation.generate_records(categories=payload, output='/PATH/TO/OUTPUT/CSV')

# Generate an asset csv file from a local folder
assets = Curation.generate_assets('PATH/TO/FOLDER/', output='/PATH/TO/OUTPUT/CSV')

# Value is the number of containers you wish to generate
containers = Curation.generate_containers(value=2, output='/PATH/TO/OUTPUT/CSV')

Read CSV files

After you edit your CSV files you will have to pass them to Curation to validate them and generate the JSON file needed for your ingest

Only the containers file is required. if you provide assets and records files,Curation will populate asset and record ids found in the container from the provided files.

Note: pybrary will ignore duplicate keys, so make sure to have unique ids for your rows

from pybrary import Curation

volume = Curation.from_files(
    volume_name="TEST", 
    containers_file='PATH/TO/CONTAINER/FILE',
    assets_file='PATH/TO/ASSET/FILE',
    records_file='PATH/TO/RECORD/FILE'
)

Generate the ingest file

from pybrary import Curation

volume = Curation.from_files(
    volume_name="TEST", 
    containers_file='PATH/TO/CONTAINER/FILE',
    assets_file='PATH/TO/ASSET/FILE',
    records_file='PATH/TO/RECORD/FILE'
)
Curation.to_json(volume, '/PATH/TO/JSON/OUTPUT')

Duplicate existing volume

Get your volume from databrary

from pybrary import Curation

volume = Curation.from_databrary(
    volume_id=1,
    username='YOUR_USERNAME',
    password='YOUR_PASSWORD'
)

# You can edit your volume programmatically or dump your volume in
# csv files that you can edit with your text editor
Curation.to_files(
    volume, 
    containers_output='PATH/TO/CONTAINER/FILE',
    assets_output='PATH/TO/ASSET/FILE',
    records_output='PATH/TO/RECORD/FILE'
)
# once your are done you can import your files

Generate the SQL query to execute on the server (Please contact Databray admin)

from pybrary import Curation
# Source is the source volume
# Target is the target volume
Curation.generate_sql_query(volume_id=1)

The SQL query will create a script in /tmp/volume_id.sh that need to be executed prior to the ingest, it will copy the volume's asset into a staging folder.

Note: The staging folder on the server (where files are copied) and the path of the file in the final ingest file must match

Development

Test

pytest

Install Locally

pip install -e .

Build

python -m build

Publish

twine upload dist/*

TODOs

• Generate documentation and add examples.
• Check for duplicate records and asset id.
• check if the record measures are valid.
• Fix utils methods.