plots: data conversion: adjust for viewer backend (iterative#8421)

* plots: vega: converter: support multi series data split and props inference

Fixes: iterative#7754, iterative#8399
Related: iterative/studio#4369

* plots: converter: make converter infer x and y labels if not provided

* plots: vega: converter: roll back to datapoints format

* plots: vega: converter: refactor

* plots: infer labels on

* plots: get_plot_id: fix naming

* plots: vega: converter: notes regarding converting

dvc/render/convert.py

@@ -14,14 +14,14 @@
 
 
 def _get_converter(
-    renderer_class, props
+    renderer_class, renderer_id, props, data
 ) -> Union[VegaConverter, ImageConverter]:
     from dvc_render import ImageRenderer, VegaRenderer
 
     if renderer_class.TYPE == VegaRenderer.TYPE:
-        return VegaConverter(props)
+        return VegaConverter(renderer_id, data, props)
     if renderer_class.TYPE == ImageRenderer.TYPE:
-        return ImageConverter(props)
+        return ImageConverter(renderer_id, data, props)
 
     raise ValueError(f"Invalid renderer class {renderer_class}")
 

dvc/render/converter/__init__.py

@@ -1,9 +1,19 @@
-from typing import Dict, Optional
+from typing import Any, Dict, List, Optional, Tuple
 
 
 class Converter:
-    def __init__(self, plot_properties: Optional[Dict] = None):
-        self.plot_properties = plot_properties or {}
+    def __init__(
+        self,
+        plot_id: str,
+        data: Dict[str, Any] = None,
+        properties: Optional[Dict] = None,
+    ):
+        self.plot_id = plot_id
+        self.properties = properties or {}
+        self.data = data or {}
 
-    def convert(self, data, revision: str, filename: str, **kwargs):
+    def convert(self) -> Tuple[List[Tuple[str, str, Any]], Dict]:
+        raise NotImplementedError
+
+    def flat_datapoints(self, revision: str) -> Tuple[List[Dict], Dict]:
         raise NotImplementedError

dvc/render/converter/image.py

@@ -1,6 +1,6 @@
 import base64
 import os
-from typing import TYPE_CHECKING, Dict, List, Tuple
+from typing import TYPE_CHECKING, Any, Dict, List, Tuple
 
 from dvc.render import FILENAME_FIELD, REVISION_FIELD, SRC_FIELD
 
@@ -34,25 +34,33 @@ def _encode_image(
         base64_str = base64.b64encode(image_data).decode()
         return f"data:image;base64,{base64_str}"
 
-    def convert(
-        self, data, revision: str, filename: str, **kwargs
-    ) -> Tuple[List[Dict], Dict]:
+    def convert(self) -> Tuple[List[Tuple[str, str, Any]], Dict]:
+        datas = []
+        for filename, image_data in self.data.items():
+            datas.append((filename, "", image_data))
+        return datas, self.properties
+
+    def flat_datapoints(self, revision: str) -> Tuple[List[Dict], Dict]:
         """
         Convert the DVC Plots content to DVC Render datapoints.
         Return both generated datapoints and updated properties.
         """
-        path = self.plot_properties.get("out")
-        if path:
-            if not os.path.isdir(path):
-                os.makedirs(path, exist_ok=True)
-            src = self._write_image(
-                os.path.abspath(path), revision, filename, data
-            )
-        else:
-            src = self._encode_image(data)
-        datapoint = {
-            REVISION_FIELD: revision,
-            FILENAME_FIELD: filename,
-            SRC_FIELD: src,
-        }
-        return [datapoint], self.plot_properties
+        path = self.properties.get("out")
+        datapoints = []
+        datas, properties = self.convert()
+        for filename, _, image_data in datas:
+            if path:
+                if not os.path.isdir(path):
+                    os.makedirs(path, exist_ok=True)
+                src = self._write_image(
+                    os.path.abspath(path), revision, filename, image_data
+                )
+            else:
+                src = self._encode_image(image_data)
+            datapoint = {
+                REVISION_FIELD: revision,
+                FILENAME_FIELD: filename,
+                SRC_FIELD: src,
+            }
+            datapoints.append(datapoint)
+        return datapoints, properties