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Copy file name to clipboardExpand all lines: README.md
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|`delete`|`delete(logical_name, list[id], use_bulk_delete=True)`|`Optional[str]`| Delete many with async BulkDelete or sequential single-record delete. |
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|`query_sql`|`query_sql(sql)`|`list[dict]`| Constrained read-only SELECT via `?sql=`. |
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|`create_table`|`create_table(logical_name, schema, solution_unique_name=None)`|`dict`| Creates custom table + columns. Requires logical name with publisher prefix (e.g. `new_sampleitem`) and column names with same prefix (e.g. `{"new_code": "string"}`). Pass `solution_unique_name` to attach the table to a specific solution instead of the default solution. |
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|`create_column`|`create_column(tablename, columns)`|`list[str]`| Adds columns using a `{name: type}` mapping with publisher prefix (e.g. `{"new_category": "string"}`). Returns schema names for the created columns. |
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|`get_table_info`|`get_table_info(schema_name)`| `dict | None` | Basic table metadata by schema name (e.g. `new_SampleItem`). Friendly names not auto-converted. |
|`delete_table`|`delete_table(tablename)`|`None`| Drops custom table. Accepts friendly or schema name; friendly converted to `new_<PascalCase>`. |
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|`delete_column`|`delete_column(tablename, columns)`|`list[str]`| Deletes one or more columns; returns schema names (accepts string or list[str]). |
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|`create_columns`|`create_columns(logical_name, columns)`|`list[str]`| Adds columns using a `{name: type}` mapping with publisher prefix (e.g. `{"new_category": "string"}`). Returns logical names for the created columns. |
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|`get_table_info`|`get_table_info(logical_name)`| `dict | None` | Basic table metadata by logical name (e.g. `new_sampleitem`). Lookup is case-insensitive. |
|`delete_table`|`delete_table(logical_name)`|`None`| Drops custom table by logical name with publisher prefix (e.g. `new_sampleitem`). |
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|`delete_columns`|`delete_columns(logical_name, columns)`|`list[str]`| Deletes one or more columns; returns logical names (accepts string or list[str]). |
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|`PandasODataClient.create_df`|`create_df(logical_name, series)`|`str`| Create one record (returns GUID). |
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|`PandasODataClient.update`|`update(logical_name, id, series)`|`None`| Returns None; ignored if Series empty. |
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|`PandasODataClient.get_ids`|`get_ids(logical_name, ids, select=None)`|`DataFrame`| One row per ID (errors inline). |
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# Create a simple custom table and a few columns
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info = client.create_table(
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"SampleItem", #friendly name; defaults to SchemaName new_SampleItem
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"new_sampleitem", #logical name with publisher prefix (e.g., "new_")
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{
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"code": "string",
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"count": "int",
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"amount": "decimal",
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"when": "datetime",
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"active": "bool",
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"status": Status,
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"new_code": "string",
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"new_count": "int",
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"new_amount": "decimal",
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"new_when": "datetime",
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"new_active": "bool",
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"new_status": Status,
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},
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solution_unique_name="my_solution_unique_name", # optional: associate table with this solution
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