Source code for pyface.data_view.abstract_data_model

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""" Provides an AbstractDataModel ABC for Pyface data models.

This module provides an ABC for all data view data models.  This specifies
the API that the data view widgets expect, and which the underlying
data is adapted to by the concrete implementations.  Data models are intended
to be toolkit-independent, and be able to adapt any approximately tabular or
nested data structure to what the data view system expects.
"""
from abc import abstractmethod

from traits.api import ABCHasStrictTraits, Event, Instance

from .data_view_errors import DataViewSetError
from .index_manager import AbstractIndexManager


[docs]class AbstractDataModel(ABCHasStrictTraits): """ Abstract base class for Pyface data models. The data model API is intended to provide a common API for hierarchical and tabular data. This class is concerned with the structure, type and values provided by the data, but not with how the data is presented. Row and column indices are represented by sequences (usually lists) of integers, specifying the index at each level of the hierarchy. The root row and column are represented by empty lists. Subclasses need to implement the ``get_column_count``, ``can_have_children`` and ``get_row_count`` methods to return the number of columns in a particular row, as well as the hierarchical structure of the rows. Appropriate observers should be set up on the underlaying data so that the ``structure_changed`` event is fired when the values returned by these methods would change. Subclasses also have to implement the ``get_value`` and ``get_value_type`` methods. These expect a row and column index, with root values treated specially: the root row corresponds to the values which will be displayed in the column headers of the view, and the root column corresponds to the values which will be displayed in the row headers of the view. The ``get_value`` returns an arbitrary Python object corresponding to the cell being viewed, and the ``get_value_type`` should return an instance of an ``AbstractValueType`` that adapts the raw value to the data channels that the data view expects (eg. text, color, icons, editable value, etc.). Implementations should ensure that the ``values_changed`` event fires whenever the data, or the way the data is presented, is updated. If the data is to be editable then the subclass should override the ``set_value`` method. It should attempt to change the underlying data as a side-effect or raise DataViewSetError on failure (for example, setting an invalid value). If the underlying data structure cannot be listened to internally (such as a numpy array or Pandas data frame), ``set_value`` should also fire the ``values_changed`` event with appropriate values. In the cases where the underlying data structure cannot be observed by the usual traits mechanisms, the end-user of the code may be responsible for ensuring that the ``structure_changed`` and ``values_changed`` events are fired appropriately. """ #: The index manager that helps convert toolkit indices to data view #: indices. This should be an IntIndexManager for non-hierarchical data #: or a TupleIndexManager for hierarchical data. index_manager = Instance(AbstractIndexManager) #: Event fired when the structure of the data changes. structure_changed = Event() #: Event fired when value changes without changes to structure. This #: should be set to a 4-tuple of (start_row_index, start_column_index, #: end_row_index, end_column_index) indicated the subset of data which #: changed. These end values are inclusive, unlike standard Python #: slicing notation. values_changed = Event() # Data structure methods
[docs] @abstractmethod def get_column_count(self): """ How many columns in the data view model. Returns ------- column_count : non-negative int The number of columns that the data view provides. This count should not include the row header. """ raise NotImplementedError()
[docs] @abstractmethod def can_have_children(self, row): """ Whether or not a row can have child rows. The root row should always return True. Parameters ---------- row : sequence of int The indices of the row as a sequence from root to leaf. Returns ------- can_have_children : bool Whether or not the row can ever have child rows. """ raise NotImplementedError()
[docs] @abstractmethod def get_row_count(self, row): """ How many child rows the row currently has. Parameters ---------- row : sequence of int The indices of the row as a sequence from root to leaf. Returns ------- row_count : non-negative int The number of child rows that the row has. """ raise NotImplementedError()
# Data value methods
[docs] @abstractmethod def get_value(self, row, column): """ Return the Python value for the row and column. The values for column headers are returned by calling this method with row equal to (). The values for row headers are returned by calling this method with column equal to (). Parameters ---------- row : sequence of int The indices of the row as a sequence from root to leaf. column : sequence of int The indices of the column as a sequence of length 0 or 1. Returns ------- value : any The value represented by the given row and column. Raises ------- DataViewGetError If the value cannot be accessed in an expected way. If this is raised then the error will be ignored and not logged by the data view infrastructure. """ raise NotImplementedError()
[docs] def can_set_value(self, row, column): """ Whether the value in the indicated row and column can be set. The default method assumes the data is read-only and always returns False. Whether or a column header can be set is returned by calling this method with row equal to (). Whether or a row header can be set is returned by calling this method with column equal to (). Parameters ---------- row : sequence of int The indices of the row as a sequence from root to leaf. column : sequence of int The indices of the column as a sequence of length 0 or 1. Returns ------- can_set_value : bool Whether or not the value can be set. """ return False
[docs] def set_value(self, row, column, value): """ Set the Python value for the row and column. The default method assumes the data is read-only and always returns False. The values for column headers can be set by calling this method with row equal to (). The values for row headers can be set by calling this method with column equal to (). Parameters ---------- row : sequence of int The indices of the row as a sequence from root to leaf. column : sequence of int The indices of the column as a sequence of length 0 or 1. value : any The new value for the given row and column. Raises ------- DataViewSetError If the value cannot be set. """ raise DataViewSetError()
[docs] @abstractmethod def get_value_type(self, row, column): """ Return the value type of the given row and column. The value type for column headers are returned by calling this method with row equal to (). The value types for row headers are returned by calling this method with column equal to (). Parameters ---------- row : sequence of int The indices of the row as a sequence from root to leaf. column : sequence of int The indices of the column as a sequence of length 0 or 1. Returns ------- value_type : AbstractValueType or None The value type of the given row and column, or None if no value should be displayed. """ raise NotImplementedError()
# Convenience methods
[docs] def is_row_valid(self, row): """ Return whether or not the given row index refers to a valid row. A row index is valid if every value in the tuple is between 0 and the number of child rows of the parent. Parameters ---------- row : sequence of int The row to check as indices of the row from root to leaf. Returns ------- valid : bool Whether or not the row index is valid. """ for i, index in enumerate(row): parent = row[:i] if not self.can_have_children(parent): return False if not 0 <= index < self.get_row_count(parent): return False return True
[docs] def is_column_valid(self, column): """ Return whether or not the given column index refers to a valid column. A column index is valid if it is the root, or the value is between 0 and the number of columns in the model. Parameters ---------- column : sequence of int The column to check. Returns ------- valid : bool Whether or not the column index is valid. """ if len(column) == 1: return 0 <= column[0] < self.get_column_count() return len(column) == 0
[docs] def iter_rows(self, start_row=()): """ Iterator that yields rows in preorder. Parameters ---------- start_row : sequence of int The row to start at. The iterator will yeild the row and all descendant rows. Yields ------ row_index : sequence of int The current row index. """ start_row = tuple(start_row) yield start_row if self.can_have_children(start_row): for row in range(self.get_row_count(start_row)): yield from self.iter_rows(start_row + (row,))
[docs] def iter_items(self, start_row=()): """ Iterator that yields rows and columns in preorder. This yields pairs of row, column for all rows in preorder and and all column indices for all rows, including (). Columns are iterated in order. Parameters ---------- start_row : sequence of int The row to start iteration from. Yields ------ row_index, column_index The current row and column indices. """ for row in self.iter_rows(start_row): yield row, () for column in range(self.get_column_count()): yield row, (column,)