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Every source in Rippit, whether an integration, a Snowflake import, a Bulk API upload or an AI table, is a table you query the same way. Worksheets are tables too, so these operations work on them as well.

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How it works

  1. Find a table. list_data_sources lists live data tables, filterable by provider or name. list_worksheets lists saved worksheets.
  2. See its columns. describe_table shows every column, its type and values, plus a data coverage block: the sync window and row count. describe_column covers one column.
  3. Read rows. read_table returns rows, filtered and sorted.
  4. Count and group. aggregate_table counts, sums and groups across the whole table. pivot_table cross-tabulates two dimensions with totals.
  5. Read conversations. read_conversations returns full transcripts for up to 10 tickets at a time, for quotes and examples.

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Good to know

  • Filters and groupings take column ids, not labels. Get them from describe_table.
  • singleSelect values are option ids (opt_*). Use describe_column with search to turn a label into an id before filtering.
  • Results are paged. pagination.nextOffset or pagination.truncated means there is more.
  • Coverage can be limited by the synced period, sampling or an unfinished backfill. Check describe_table before reporting totals.

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Operations

See the operation pages in this section for every parameter.