Jinkō Data Table SDK Workflows

Use this skill for data-table mechanics through the SDK. Data tables can support trial overlays and calibration objectives; the row schema is the same, and fitness-function compatibility is reported by metadata when available.

Scope

• Use client.create_data_table_from_csv() for CSV files or bytes.
• Use client.create_data_table_from_sqlite() for SQLite files or bytes.
• Use client.create_data_table_from_dataframe() for pandas DataFrames.
• Inspect existing data tables with get_data_table(), content(), summary(), validate(), and export().
• Check metadata.public.validForFitnessFunction after creation or inspection when available if the data table needs to be attached through trial/calibration dataTableDesigns.
• For trial workflows that attach data tables through jk-trial, use a data table with validForFitnessFunction: True; point-value overlay tables may upload successfully but fail trial launch sanity.

Project Folder Hygiene

• Prefer creating data tables inside a dedicated Jinkō folder instead of the project root. At the start of a workflow, ask for or propose a folder name, for example YYYY-MM-DD-<experiment-name>.
• Reuse an existing exact-match folder when possible: client.folders.get_by_name(name, exact_match_only=True).
• If the folder does not exist, create it only after user confirmation or when a script is run with --apply.
• Resolve one folder object or folder id, then pass folder=folder to SDK creation calls that support it.