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Benchling_Write_Object

Node​

Node Description​

Writes data stored in Ganymede cloud storage to Benchling custom entity, as specified by input object names and SQL query

Passes Benchling ID to user-defined function for retrieving Benchling API data.

Node Attributes​

  • src_input_or_output_bucket
    • Specify "input" or "output" for the Ganymede cloud storage bucket to read from.
    • "input" contains files ingested into a flow; "output" contains processed data.
  • input_object_names
    • Semicolon-delimited list of objects to retrieve to the execute function

Notes​

Usage requires configuration of a Benchling application in the relevant Benchling tenant.

Prior to usage, the secrets below must be configured in your Ganymede environment. More information on acquiring these credentials can be found here.

  • benchling_url: URL for Benchling tenant; has form https://<tenant>.benchling.com
  • benchling_app_client_id: Client_ID; has form xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
  • benchling_client_secret: Client_Secret; has form cs_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Secrets can be configured by clicking on your username in the upper-right hand of the Ganymede application, then selecting Environment Settings and navigating to the Secrets tab. If you need assistance, please don't hesitate to reach out to Ganymede.

User-Defined Python​

Uploads data to Benchling

If new custom entities are created, returns DataFrame associated with custom entity

Parameters​

  • data : dict[str, bytes]
    • Data to retrieve from Ganymede cloud storage
  • df_sql_result : pd.DataFrame | list[pd.DataFrame]
    • Tabular results of user-defined SQL query
  • benchling_context : BenchlingContext
    • Benchling context variable, which stores Benchling connection information
  • ganymede_context : GanymedeContext
    • Ganymede context variable, which stores flow run metadata

Returns​

NodeReturn Object containing data to store in data lake and/or file storage.