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#!/usr/bin/python
"""
Copyright 2014 Google Inc.
Use of this source code is governed by a BSD-style license that can be
found in the LICENSE file.
ColumnHeaderFactory class (see class docstring for details)
"""
# Keys used within dictionary representation of each column header.
# NOTE: Keep these in sync with static/constants.js
KEY__HEADER_TEXT = 'headerText'
KEY__HEADER_URL = 'headerUrl'
KEY__IS_FILTERABLE = 'isFilterable'
KEY__IS_SORTABLE = 'isSortable'
KEY__VALUES_AND_COUNTS = 'valuesAndCounts'
class ColumnHeaderFactory(object):
"""Factory which assembles the header for a single column of data."""
def __init__(self, header_text, header_url=None,
is_filterable=True, is_sortable=True,
include_values_and_counts=True):
"""
Args:
header_text: string; text the client should display within column header.
header_url: string; target URL if user clicks on column header.
If None, nothing to click on.
is_filterable: boolean; whether client should allow filtering on this
column.
is_sortable: boolean; whether client should allow sorting on this column.
include_values_and_counts: boolean; whether the set of values found
within this column, and their counts, should be available for the
client to display.
"""
self._header_text = header_text
self._header_url = header_url
self._is_filterable = is_filterable
self._is_sortable = is_sortable
self._include_values_and_counts = include_values_and_counts
def create_as_dict(self, values_and_counts_dict=None):
"""Creates the header for this column, in dictionary form.
Creates the header for this column in dictionary form, as needed when
constructing the JSON representation. Uses the KEY__* constants as keys.
Args:
values_and_counts_dict: dictionary mapping each possible column value
to its count (how many entries in the column have this value), or
None if this information is not available.
"""
asdict = {
KEY__HEADER_TEXT: self._header_text,
KEY__IS_FILTERABLE: self._is_filterable,
KEY__IS_SORTABLE: self._is_sortable,
}
if self._header_url:
asdict[KEY__HEADER_URL] = self._header_url
if self._include_values_and_counts and values_and_counts_dict:
asdict[KEY__VALUES_AND_COUNTS] = values_and_counts_dict
return asdict
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