Reimplement AnalysisResultTable

qiskit_experiments/database_service/utils.py

@@ -19,10 +19,9 @@
 from abc import ABC, abstractmethod
 from collections import OrderedDict
 from datetime import datetime, timezone
-from typing import Callable, Tuple, List, Dict, Any, Union, Type, Optional
+from typing import Callable, Tuple, Dict, Any, Union, Type, Optional
 import json
 
-import pandas as pd
 import dateutil.parser
 import pkg_resources
 from dateutil import tz
@@ -278,199 +277,3 @@ def append(self, value):
         """Append to the list."""
         with self._lock:
             self._container.append(value)
-
-
-class ThreadSafeDataFrame(ThreadSafeContainer):
-    """Thread safe data frame.
-
-    This class wraps pandas dataframe with predefined column labels,
-    which is specified by the class method `_default_columns`.
-    Subclass can override this method to provide default labels specific to its data structure.
-
-    This object is expected to be used internally in the ExperimentData.
-    """
-
-    def __init__(self, init_values=None):
-        """ThreadSafeContainer constructor."""
-        self._columns = self._default_columns()
-        self._extra = []
-        super().__init__(init_values)
-
-    @classmethod
-    def _default_columns(cls) -> List[str]:
-        return []
-
-    def _init_container(self, init_values: Optional[Union[Dict, pd.DataFrame]] = None):
-        """Initialize the container."""
-        if init_values is None:
-            return pd.DataFrame(columns=self.get_columns())
-        if isinstance(init_values, pd.DataFrame):
-            input_columns = list(init_values.columns)
-            if input_columns != self.get_columns():
-                raise ValueError(
-                    f"Input data frame contains unexpected columns {input_columns}. "
-                    f"{self.__class__.__name__} defines {self.get_columns()} as default columns."
-                )
-            return init_values
-        if isinstance(init_values, dict):
-            return pd.DataFrame.from_dict(
-                data=init_values,
-                orient="index",
-                columns=self.get_columns(),
-            )
-        raise TypeError(f"Initial value of {type(init_values)} is not valid data type.")
-
-    def get_columns(self) -> List[str]:
-        """Return current column names.
-
-        Returns:
-            List of column names.
-        """
-        with self._lock:
-            return self._columns.copy()
-
-    def add_columns(self, *new_columns: str, default_value: Any = None):
-        """Add new columns to the table.
-
-        This operation mutates the current container.
-
-        Args:
-            new_columns: Name of columns to add.
-            default_value: Default value to fill added columns.
-        """
-        with self._lock:
-            # Order sensitive
-            new_columns = [c for c in new_columns if c not in self.get_columns()]
-            if len(new_columns) == 0:
-                return
-
-            # Update columns
-            for new_column in new_columns:
-                self._container.insert(len(self._container.columns), new_column, default_value)
-            self._columns.extend(new_columns)
-            self._extra.extend(new_columns)
-
-    def clear(self):
-        """Remove all elements from this container."""
-        with self._lock:
-            self._container = self._init_container()
-            self._columns = self._default_columns()
-            self._extra = []
-
-    def container(
-        self,
-        collapse_extra: bool = True,
-    ) -> pd.DataFrame:
-        """Return bare pandas dataframe.
-
-        Args:
-            collapse_extra: Set True to show only default columns.
-
-        Returns:
-            Bare pandas dataframe. This object is no longer thread safe.
-        """
-        with self._lock:
-            container = self._container.copy()
-
-        if collapse_extra:
-            return container[self._default_columns()]
-        return container
-
-    def drop_entry(
-        self,
-        index: str,
-    ):
-        """Drop entry from the dataframe.
-
-        Args:
-            index: Name of entry to drop.
-
-        Raises:
-            ValueError: When index is not in this table.
-        """
-        with self._lock:
-            if index not in self._container.index:
-                raise ValueError(f"Table index {index} doesn't exist in this table.")
-            self._container.drop(index, inplace=True)
-
-    def get_entry(
-        self,
-        index: str,
-    ) -> pd.Series:
-        """Get entry from the dataframe.
-
-        Args:
-            index: Name of entry to acquire.
-
-        Returns:
-            Pandas Series of acquired entry. This doesn't mutate the table.
-
-        Raises:
-            ValueError: When index is not in this table.
-        """
-        with self._lock:
-            if index not in self._container.index:
-                raise ValueError(f"Table index {index} doesn't exist in this table.")
-
-            return self._container.loc[index]
-
-    def add_entry(
-        self,
-        index: str,
-        **kwargs,
-    ) -> pd.Series:
-        """Add new entry to the dataframe.
-
-        Args:
-            index: Name of this entry. Must be unique in this table.
-            kwargs: Description of new entry to register.
-
-        Returns:
-            Pandas Series of added entry. This doesn't mutate the table.
-
-        Raises:
-            ValueError: When index is not unique in this table.
-        """
-        with self._lock:
-            if index in self._container.index:
-                raise ValueError(f"Table index {index} already exists in the table.")
-
-            if kwargs.keys() - set(self.get_columns()):
-                self.add_columns(*kwargs.keys())
-
-            template = dict.fromkeys(self.get_columns())
-            template.update(kwargs)
-
-            if not isinstance(index, str):
-                index = str(index)
-            self._container.loc[index] = list(template.values())
-
-            return self._container.iloc[-1]
-
-    def _repr_html_(self) -> Union[str, None]:
-        """Return HTML representation of this dataframe."""
-        with self._lock:
-            # Remove underscored columns.
-            return self._container._repr_html_()
-
-    def __json_encode__(self) -> Dict[str, Any]:
-        with self._lock:
-            return {
-                "class": "ThreadSafeDataFrame",
-                "data": self._container.to_dict(orient="index"),
-                "columns": self._columns,
-                "extra": self._extra,
-            }
-
-    @classmethod
-    def __json_decode__(cls, value: Dict[str, Any]) -> "ThreadSafeDataFrame":
-        if not value.get("class", None) == "ThreadSafeDataFrame":
-            raise ValueError("JSON decoded value for ThreadSafeDataFrame is not valid class type.")
-
-        instance = object.__new__(cls)
-        # Need to update self._columns first to set extra columns in the dataframe container.
-        instance._columns = value.get("columns", cls._default_columns())
-        instance._extra = value.get("extra", [])
-        instance._lock = threading.RLock()
-        instance._container = instance._init_container(init_values=value.get("data", {}))
-        return instance