# Tables

## List tables in structured sheet

`structured_sheets.tables.list(strstructured_sheet_id, TableListParams**kwargs)  -> SyncCursorIDPage[TableResponse]`

**get** `/v1/structured-sheets/{structured_sheet_id}/tables`

List all tables extracted from the structured sheet. Only available when conversion status is 'completed'.

### Parameters

- `structured_sheet_id: str`

  The unique identifier of the structured sheet conversion.

- `after: Optional[str]`

  A cursor for pagination. Use the `last_id` from a previous response to fetch the next page of results.

- `limit: Optional[int]`

  Maximum number of tables to return per page.

### Returns

- `class TableResponse: …`

  Response representing a table extracted from a structured sheet.

  This is returned from GET (retrieve) and list table endpoints.
  Table names use a composite format: {normalized_sheet_name}__{table_name}.

  - `id: str`

    The unique identifier for this table.

  - `created_at: datetime`

    The timestamp when this table was created.

  - `name: str`

    Composite table name: {normalized_sheet_name}__{table_name}. Uses lowercase snake_case. Aggregation tables end with '__aggregations'. Two special metadata tables exist per structured sheet: '__deeptable_workbook_metadata' (workbook provenance info) and '__deeptable_table_overview' (summary of all tables). Example: 'staffing__head_count' or 'staffing__head_count__aggregations'.

  - `object: Literal["table"]`

    The object type, which is always 'table'.

    - `"table"`

  - `sheet_name: str`

    The original Excel sheet name this table came from.

  - `structured_sheet_id: str`

    The ID of the structured sheet this table belongs to.

  - `type: Literal["relational", "aggregation", "tableless", "metadata"]`

    The type of table (relational, aggregation, tableless, or metadata).

    - `"relational"`

    - `"aggregation"`

    - `"tableless"`

    - `"metadata"`

### Example

```python
import os
from deeptable import DeepTable

client = DeepTable(
    api_key=os.environ.get("DEEPTABLE_API_KEY"),  # This is the default and can be omitted
)
page = client.structured_sheets.tables.list(
    structured_sheet_id="ss_01kfxgjd94fn9stqm42nejb627",
)
page = page.data[0]
print(page.id)
```

#### Response

```json
{
  "data": [
    {
      "id": "tbl_01kfxgjd94fn9stqm45rqr2pnz",
      "created_at": "2026-01-15T10:35:00Z",
      "name": "staffing__head_count",
      "object": "table",
      "sheet_name": "Staffing",
      "structured_sheet_id": "ss_01kfxgjd94fn9stqm42nejb627",
      "type": "relational"
    },
    {
      "id": "tbl_02abc2def3ghjkmnpqrs4uvwxz",
      "created_at": "2026-01-15T10:35:00Z",
      "name": "staffing__head_count__aggregations",
      "object": "table",
      "sheet_name": "Staffing",
      "structured_sheet_id": "ss_01kfxgjd94fn9stqm42nejb627",
      "type": "aggregation"
    }
  ],
  "has_more": false,
  "object": "list",
  "first_id": "tbl_01kfxgjd94fn9stqm45rqr2pnz",
  "last_id": "tbl_02abc2def3ghjkmnpqrs4uvwxz"
}
```

## Retrieve a table

`structured_sheets.tables.retrieve(strtable_id, TableRetrieveParams**kwargs)  -> TableResponse`

**get** `/v1/structured-sheets/{structured_sheet_id}/tables/{table_id}`

Get details of a specific table extracted from the structured sheet. Only available when conversion status is 'completed'.

### Parameters

- `structured_sheet_id: str`

  The unique identifier of the structured sheet conversion.

- `table_id: str`

  The unique identifier of the table.

### Returns

- `class TableResponse: …`

  Response representing a table extracted from a structured sheet.

  This is returned from GET (retrieve) and list table endpoints.
  Table names use a composite format: {normalized_sheet_name}__{table_name}.

  - `id: str`

    The unique identifier for this table.

  - `created_at: datetime`

    The timestamp when this table was created.

  - `name: str`

    Composite table name: {normalized_sheet_name}__{table_name}. Uses lowercase snake_case. Aggregation tables end with '__aggregations'. Two special metadata tables exist per structured sheet: '__deeptable_workbook_metadata' (workbook provenance info) and '__deeptable_table_overview' (summary of all tables). Example: 'staffing__head_count' or 'staffing__head_count__aggregations'.

  - `object: Literal["table"]`

    The object type, which is always 'table'.

    - `"table"`

  - `sheet_name: str`

    The original Excel sheet name this table came from.

  - `structured_sheet_id: str`

    The ID of the structured sheet this table belongs to.

  - `type: Literal["relational", "aggregation", "tableless", "metadata"]`

    The type of table (relational, aggregation, tableless, or metadata).

    - `"relational"`

    - `"aggregation"`

    - `"tableless"`

    - `"metadata"`

### Example

```python
import os
from deeptable import DeepTable

client = DeepTable(
    api_key=os.environ.get("DEEPTABLE_API_KEY"),  # This is the default and can be omitted
)
table_response = client.structured_sheets.tables.retrieve(
    table_id="tbl_01kfxgjd94fn9stqm45rqr2pnz",
    structured_sheet_id="ss_01kfxgjd94fn9stqm42nejb627",
)
print(table_response.id)
```

#### Response

```json
{
  "id": "tbl_01kfxgjd94fn9stqm45rqr2pnz",
  "created_at": "2026-01-15T10:35:00Z",
  "name": "staffing__head_count",
  "object": "table",
  "sheet_name": "Staffing",
  "structured_sheet_id": "ss_01kfxgjd94fn9stqm42nejb627",
  "type": "relational"
}
```

## Download table data

`structured_sheets.tables.download(strtable_id, TableDownloadParams**kwargs)  -> BinaryResponseContent`

**get** `/v1/structured-sheets/{structured_sheet_id}/tables/{table_id}/download`

Download the table data in the specified format.

Available formats:

- `parquet`: Apache Parquet columnar format (recommended for data analysis)
- `csv`: Comma-separated values (compatible with any spreadsheet application)

### Parameters

- `structured_sheet_id: str`

  The unique identifier of the structured sheet conversion.

- `table_id: str`

  The unique identifier of the table.

- `format: Literal["parquet", "csv"]`

  The format to download the table data in.

  - `"parquet"`

  - `"csv"`

### Returns

- `BinaryResponseContent`

### Example

```python
import os
from deeptable import DeepTable

client = DeepTable(
    api_key=os.environ.get("DEEPTABLE_API_KEY"),  # This is the default and can be omitted
)
response = client.structured_sheets.tables.download(
    table_id="tbl_01kfxgjd94fn9stqm45rqr2pnz",
    structured_sheet_id="ss_01kfxgjd94fn9stqm42nejb627",
    format="parquet",
)
print(response)
content = response.read()
print(content)
```

## Domain Types

### Table Response

- `class TableResponse: …`

  Response representing a table extracted from a structured sheet.

  This is returned from GET (retrieve) and list table endpoints.
  Table names use a composite format: {normalized_sheet_name}__{table_name}.

  - `id: str`

    The unique identifier for this table.

  - `created_at: datetime`

    The timestamp when this table was created.

  - `name: str`

    Composite table name: {normalized_sheet_name}__{table_name}. Uses lowercase snake_case. Aggregation tables end with '__aggregations'. Two special metadata tables exist per structured sheet: '__deeptable_workbook_metadata' (workbook provenance info) and '__deeptable_table_overview' (summary of all tables). Example: 'staffing__head_count' or 'staffing__head_count__aggregations'.

  - `object: Literal["table"]`

    The object type, which is always 'table'.

    - `"table"`

  - `sheet_name: str`

    The original Excel sheet name this table came from.

  - `structured_sheet_id: str`

    The ID of the structured sheet this table belongs to.

  - `type: Literal["relational", "aggregation", "tableless", "metadata"]`

    The type of table (relational, aggregation, tableless, or metadata).

    - `"relational"`

    - `"aggregation"`

    - `"tableless"`

    - `"metadata"`