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Benchling_Warehouse_Query

Node​

Node Description​

Query Benchling Warehouse Postgres database, process data in Python, and upload results to Ganymede data lake

Notes​

Prior to usage, the following secrets must be configured in your Ganymede environment:

  • benchling_postgres_host: Host for Benchling warehouse database. Of the form: postgres-warehouse.<tenant>.benchling.com
  • benchling_postgres_username: Username for Benchling warehouse database. Note that this is not the same as your Benchling username.
  • benchling_postgres_password: Password for Benchling warehouse database. Note that this is not the same as your Benchling password.

To generate Benchling warehouse credentials, click on your icon in the lower-right hand corner of Benchling, then select "Settings". On the right-hand side of the page, click on the "Create Credentials" button in the Warehouse Credentials section of the page. For more information, check out the detailed instructions in Benchling documentation.

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​

Process tabular data from user-defined SQL query, writing results back to data lake

Parameters​

  • df_sql_result : pd.DataFrame | list[pd.DataFrame]
  • Table(s) or list of tables retrieved from user-defined SQL query
  • 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