adding support for flattening entries in a datasource
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@ -83,13 +83,13 @@ class DataSource:
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Return a list of random values from the data set, as a list of lists.
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"""
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return [
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self._random_choice_from_option(option) for option in self.random_frequencies(count)
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self.get_entries(option, rand=True) for option in self.random_frequencies(count)
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]
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def _random_choice_from_option(self, option: str) -> list:
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def get_entries(self, option, rand: bool = True) -> list:
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"""
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Select a random item from the specified option in the data source, and return a flattened
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list of the option, the select item, and the item's value (if any).
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For a random item or each item in the specified option in the data source,
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return a flattened list of the option, the select item, and the item's value (if any).
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"""
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# If there is no data for the specified option, stop now.
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@ -103,14 +103,23 @@ class DataSource:
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#
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# >>> self.data[option] == {'One': ['bar', 'baz'], 'Two': ['qaz', 'qux']}
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#
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# choice might then be: ['One', 'bar', 'baz']
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# choices might then be: ['One', 'bar', 'baz']
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#
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if rand:
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k, v = random.choice(list(self.data[option].items()))
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choice = [k] + v
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choices = [[k] + v]
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else:
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choices = [
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[k] + v for k, v in list(self.data[option].items())
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]
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else:
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# If the option is either a list or a string, just select it.
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choice = random.choice(self.data[option])
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if rand:
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choices = [random.choice(self.data[option])]
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else:
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choices = self.data[option]
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for choice in choices:
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# If the randomly-selected choice is a dict, choose a random item and return a list consisting
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# of the option name, the key, and the value, flattening the # value if it is also a list.
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if hasattr(choice, 'keys'):
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@ -119,18 +128,17 @@ class DataSource:
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flattened.extend([k, *v])
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else:
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flattened.extend([k, v])
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return flattened
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continue
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# if the member is a list, return the flattened list
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if type(choice) is list:
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flattened.extend(choice)
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return flattened
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continue
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# otherwise, return a list consisting of option and choice
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flattened.append(choice)
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return flattened
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class RollTable:
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"""
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Generate a roll table using weighted distributions of random options.
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@ -187,11 +187,14 @@ def test_no_options():
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assert str(t)
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def test_yaml():
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assert tables.RollTable([fixture_no_options]).as_yaml()
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assert tables.RollTable([fixture_one_choice]).as_yaml()
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assert tables.RollTable([fixture_metadata + fixture_source]).as_yaml()
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assert tables.RollTable([fixture_source]).as_yaml()
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@pytest.mark.parametrize('table', [
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tables.RollTable([fixture_no_options]),
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tables.RollTable([fixture_one_choice]),
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tables.RollTable([fixture_metadata + fixture_source]),
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tables.RollTable([fixture_source]),
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])
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def test_yaml(table):
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assert table.as_yaml()
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def test_text():
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