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Copy file name to clipboardExpand all lines: README.md
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@@ -5,6 +5,7 @@ A minimal Python SDK to use Microsoft Dataverse as a database for Azure AI Found
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- Read (SQL) — Execute read-only T‑SQL via the McpExecuteSqlQuery Custom API. Returns `list[dict]`.
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- OData CRUD — Thin wrappers over Dataverse Web API (create/get/update/delete).
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- Bulk create — Pass a list of records to `create(...)` to invoke the bound `CreateMultiple` action; returns `list[str]` of GUIDs. If `@odata.type` is absent the SDK resolves the logical name from metadata (cached).
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- Bulk update — Call `update_multiple(entity_set, records)` to invoke the bound `UpdateMultiple` action; returns nothing. Each record must include the real primary key attribute (e.g. `accountid`).
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- Retrieve multiple (paging) — Generator-based `get_multiple(...)` that yields pages, supports `$top` and Prefer: `odata.maxpagesize` (`page_size`).
@@ -16,6 +17,7 @@ A minimal Python SDK to use Microsoft Dataverse as a database for Azure AI Found
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- SQL-over-API: T-SQL routed through Custom API endpoint (no ODBC / TDS driver required).
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- Table metadata ops: create simple custom tables with primitive columns (string/int/decimal/float/datetime/bool) and delete them.
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- Bulk create via `CreateMultiple` (collection-bound) by passing `list[dict]` to `create(entity_set, payloads)`; returns list of created IDs.
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- Bulk update via `UpdateMultiple` by calling `update_multiple(entity_set, records)` with primary key attribute present in each record; returns nothing.
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- Retrieve multiple with server-driven paging: `get_multiple(...)` yields lists (pages) following `@odata.nextLink`. Control total via `$top` and per-page via `page_size` (Prefer: `odata.maxpagesize`).
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- Optional pandas integration (`PandasODataClient`) for DataFrame based create / get / query.
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