feat: add table exporters

docling_core/types/doc/base.py

@@ -4,8 +4,9 @@
 #
 
 """Define common models across CCS objects."""
-from typing import Annotated, Literal, Optional, Union
+from typing import Annotated, List, Literal, Optional, Union
 
+import pandas as pd
 from pydantic import BaseModel, Field, PositiveInt, StrictStr
 
 from docling_core.search.mapping import es_field
@@ -152,6 +153,102 @@ class Table(BaseCell):
     data: Optional[list[list[Union[GlmTableCell, TableCell]]]] = None
     model: Optional[str] = None
 
+    def _get_tablecell_span(self, cell: TableCell, ix: int):
+        if cell.spans is None:
+            span = set()
+        else:
+            span = set([s[ix] for s in cell.spans])
+        if len(span) == 0:
+            return 1, None, None
+        return len(span), min(span), max(span)
+
+    def export_to_dataframe(self) -> pd.DataFrame:
+        """Export the table as a Pandas DataFrame."""
+        if self.data is None or self.num_rows == 0 or self.num_cols == 0:
+            return pd.DataFrame()
+
+        # Count how many rows are column headers
+        num_headers = 0
+        for i, row in enumerate(self.data):
+            if len(row) == 0:
+                raise RuntimeError(f"Invalid table. {len(row)=} but {self.num_cols=}.")
+
+            any_header = False
+            for cell in row:
+                if cell.obj_type == "col_header":
+                    any_header = True
+                    break
+
+            if any_header:
+                num_headers += 1
+            else:
+                break
+
+        # Create the column names from all col_headers
+        columns: Optional[List[str]] = None
+        if num_headers > 0:
+            columns = ["" for _ in range(self.num_cols)]
+            for i in range(num_headers):
+                for j, cell in enumerate(self.data[i]):
+                    col_name = cell.text
+                    if columns[j] != "":
+                        col_name = f".{col_name}"
+                    columns[j] += col_name
+
+        # Create table data
+        table_data = [[cell.text for cell in row] for row in self.data[num_headers:]]
+
+        # Create DataFrame
+        df = pd.DataFrame(table_data, columns=columns)
+
+        return df
+
+    def export_to_html(self) -> str:
+        """Export the table as html."""
+        body = ""
+        nrows = self.num_rows
+        ncols = self.num_cols
+
+        if self.data is None:
+            return ""
+        for i in range(nrows):
+            body += "<tr>"
+            for j in range(ncols):
+                cell: TableCell = self.data[i][j]
+
+                rowspan, rowstart, rowend = self._get_tablecell_span(cell, 0)
+                colspan, colstart, colend = self._get_tablecell_span(cell, 1)
+
+                if rowstart is not None and rowstart != i:
+                    continue
+                if colstart is not None and colstart != j:
+                    continue
+
+                if rowstart is None:
+                    rowstart = i
+                if colstart is None:
+                    colstart = j
+
+                content = cell.text.strip()
+                label = cell.obj_type
+                celltag = "td"
+                if label in ["row_header", "row_multi_header", "row_title"]:
+                    pass
+                elif label in ["col_header", "col_multi_header"]:
+                    celltag = "th"
+
+                opening_tag = f"{celltag}"
+                if rowspan > 1:
+                    opening_tag += f' rowspan="{rowspan}"'
+                if colspan > 1:
+                    opening_tag += f' colspan="{colspan}"'
+
+                body += f"<{opening_tag}>{content}</{celltag}>"
+            body += "</tr>"
+        body = f"<table>{body}</table>"
+
+        return body
+
 
 # FIXME: let's add some figure specific data-types later
 class Figure(BaseCell):