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lastFile:src/skore/project.py

src/skore/project.py

@@ -1,30 +1,123 @@
-Path = None
-Item = None
+""""""
+
+import json
+from pathlib import Path
+from typing import Any, List
+
 
 def get_filepath_from_project_name(project_name) -> Path:
     return None
 
+
+class Item:
+    """An item in the project."""
+
+
+class JSONItem(Item):
+    """An item that is a JSON serializable Python object."""
+
+    def __init__(self, value):
+        self.value = json.dumps(value)
+
+
+class DataFrameItem(Item):
+    """An item that is a pandas or polars data frame."""
+
+
+class NumpyArrayItem(Item):
+    """An item that is a Numpy Array."""
+
+
+class MediaItem(Item):
+    """An item that is a media object."""
+
+
+class ScikitLearnModelItem(Item):
+    """An item that is a Scikit-Learn model."""
+
+    def __init__(self, value):
+        self.value = value
+
+    @staticmethod
+    def transform(value):
+        return html
+
+
 class Transformer:
     @staticmethod
     def transform(value) -> Item:
-        ...
+        """Transform a value into an Item."""
+        # Get the class of the value as a string
+        value_class = type(value).__name__
+
+        # Map the class name to the corresponding Item subclass
+        item_class_map = {
+            "dict": JSONItem,
+            "list": JSONItem,
+            "tuple": JSONItem,
+            "int": JSONItem,
+            "float": JSONItem,
+            "str": JSONItem,
+            "bool": JSONItem,
+            # TODO: Add
+            # pandas.DataFrame 	DataFrameItem
+            # polars.DataFrame 	DataFrameItem
+            # numpy.ndarray 	NumpyArrayItem
+            # matplotlib.figure.Figure 	MediaItem (as SVG)
+            # PIL.Image.Image 	MediaItem (as PNG)
+            # altair.Chart 	MediaItem (as Vega-Lite JSON)
+            # bytes + media type 	MediaItem
+            # str + media type 	MediaItem
+            # Scikit-learn model 	ScikitLearnModelItem
+        }
+
+        # Check if the value's class is in our mapping
+        if value_class in item_class_map:
+            return item_class_map[value_class](value)
+
+        # For scikit-learn models, we need to check if it's a BaseEstimator
+        if hasattr(value, "fit") and hasattr(value, "predict"):
+            return ScikitLearnModelItem(value)
+
+        # If we don't have a specific Item subclass for this type,
+        # we'll use the base Item class
+        return Item(value)
+
 
 class Project:
+    """A project is a collection of items that are stored in a storage."""
+
     def __init__(self, transformer, storage):
         self.transformer = transformer
         self.storage = storage
 
     def put(self, key, value):
+        """Put a value into the project."""
         self.storage.save(
             key,
             self.transformer.transform(value),
         )
 
     def put_item(self, key, item):
+        """Put an item into the project."""
         self.storage.save(
             key,
             item,
         )
 
+    def get(self, key) -> Any:
+        """Get an item from the project."""
+
+    def get_item(self, key) -> Item:
+        """Get an item from the project."""
+
+    def list_keys(self) -> List[str]:
+        """List all keys in the project."""
+
+    def delete_item(key: str):
+        """Delete an item from the project."""
+
+
 def load(project_name: str) -> Project:
+    """Load a project from a file."""
     filepath = get_filepath_from_project_name(project_name)