refactoring helper classes into random-sets
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evilchili
parent
2752c788ed
commit
2a110c7284
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@ -14,6 +14,7 @@ typer = "^0.9.0"
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rich = "^13.7.0"
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pyyaml = "^6.0.1"
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csv2md = "^1.2.0"
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random_sets = { git = "file:///home/greg/dev/random-sets", branch="main" }
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[tool.poetry.dev-dependencies]
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pytest = "^7.4.3"
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@ -1,4 +1,4 @@
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from rolltable import tables
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from rolltable.types import RollTable
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import typer
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from enum import Enum
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from rich import print
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@ -46,7 +46,7 @@ def create(
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CLI for creating roll tables.
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"""
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rt = tables.RollTable([Path(s).read_text() for s in sources], frequency=frequency, die=die, hide_rolls=hide_rolls)
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rt = RollTable([Path(s).read_text() for s in sources], frequency=frequency, die=die, hide_rolls=hide_rolls)
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if output == OUTPUT_FORMATS.yaml:
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print(rt.as_yaml())
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@ -1,151 +1,8 @@
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import yaml
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import random
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from csv2md.table import Table
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from collections.abc import Iterable
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from typing import Optional, List, IO, Union
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class DataSource:
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"""
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Represents a yaml data source used to generate roll tables.
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Attributes:
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source - the IO source to parse
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frequency - the frequency distribution to apply
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headers - an array of header strings
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data - The parsed YAML data
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Methods:
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load_source - Read and parse the source, populating the attributes
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"""
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def __init__(self, source: IO, frequency: str = 'default') -> None:
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"""
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Initialize a DataSource instance.
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Args:
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source - an IO object to read source from
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frequency - the name of the frequency distribution to use; must
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be defined in the source file's metadata.
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"""
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self.source = source
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self.frequency = frequency
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self.headers = []
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self.frequencies = None
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self.data = None
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self.metadata = None
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self.load_source()
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def load_source(self) -> None:
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"""
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Cache the yaml source and the parsed or generated metadata.
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"""
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if self.data:
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return
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self.read_source()
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self.init_headers()
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self.init_frequencies()
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def read_source(self) -> None:
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self.data = yaml.safe_load(self.source)
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self.metadata = self.data.pop('metadata', {})
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def init_headers(self) -> None:
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if 'headers' in self.metadata:
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self.headers = self.metadata['headers']
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def init_frequencies(self) -> None:
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num_keys = len(self.data.keys())
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default_freq = num_keys / 100
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frequencies = {
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'default': dict([(k, default_freq) for k in self.data.keys()])
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}
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if 'frequencies' in self.metadata:
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frequencies.update(**self.metadata['frequencies'])
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self.frequencies = frequencies[self.frequency]
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def random_frequencies(self, count: int = 1) -> list:
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"""
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Choose random option names from the frequency table.
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"""
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weights = []
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options = []
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for (option, weight) in self.frequencies.items():
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weights.append(weight)
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options.append(option)
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return random.choices(options, weights=weights, k=count)
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def random_values(self, count: int = 1) -> list:
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"""
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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.get_entries(option, rand=True) for option in self.random_frequencies(count)
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]
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def as_dict(self) -> dict:
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"""
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Return the contents of the data source as a dict.
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"""
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data = dict()
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for name in self.data.keys():
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entries = self.get_entries(name, rand=False)
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items = {(k, v) for k, v in zip(self.headers, entries)}
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data[name] = dict(items)
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return data
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def get_entries(self, option, rand: bool = False) -> list:
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"""
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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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flattened = [option]
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if not self.data[option]:
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return flattened
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if hasattr(self.data[option], 'keys'):
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# if the option is a dict, we assume the values are lists; we select a random item
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# and prepend the key to the value list as our random selection. For example, given:
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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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# 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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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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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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for (k, v) in choice.items():
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if type(v) is list:
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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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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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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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from typing import Optional, List, Union
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from random_sets.datasources import DataSource
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class RollTable:
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@ -1,6 +1,6 @@
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import pytest
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from rolltable import tables
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from rolltable import types
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fixture_metadata = """
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metadata:
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@ -137,80 +137,80 @@ dict:
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@pytest.mark.parametrize('fixture', fixture_lists_and_dicts)
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def test_lists_and_dicts(fixture):
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t = tables.RollTable([fixture], die=1)
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t = types.RollTable([fixture], die=1)
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assert(str(t))
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def test_combined_tables():
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combined = tables.RollTable([fixture_combined_A, fixture_combined_B], die=6)
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combined = types.RollTable([fixture_combined_A, fixture_combined_B], die=6)
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assert str(combined)
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def test_table_end_to_end():
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assert str(tables.RollTable([fixture_source]))
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assert str(types.RollTable([fixture_source]))
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def test_table_end_to_end_with_metadata():
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assert str(tables.RollTable([fixture_metadata + fixture_source]))
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assert str(types.RollTable([fixture_metadata + fixture_source]))
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def test_table_frequency():
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t = tables.RollTable([fixture_metadata + fixture_source], frequency='nondefault')
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t = types.RollTable([fixture_metadata + fixture_source], frequency='nondefault')
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assert t._data[0].frequencies['Option 1'] == 0.0
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assert t._data[0].frequencies['Option 2'] == 0.1
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assert t._data[0].frequencies['Option 3'] == 0.9
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def test_one_option():
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t = tables.RollTable([fixture_one_choice], die=1)
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t = types.RollTable([fixture_one_choice], die=1)
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assert t._values == [['option 1', 'choice 1', 'description 1']]
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def test_collapsed():
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t = tables.RollTable([fixture_repeated_choices], die=6)
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t = types.RollTable([fixture_repeated_choices], die=6)
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assert len(list(t.rows)) == 2 # (+1 for headers)
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def test_not_collapsed():
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t = tables.RollTable([fixture_repeated_choices], die=6)
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t = types.RollTable([fixture_repeated_choices], die=6)
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assert len(list(t.expanded_rows)) == 7 # (+1 for headers)
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def test_no_descriptions():
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t = tables.RollTable([fixture_no_descriptions], die=1)
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t = types.RollTable([fixture_no_descriptions], die=1)
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assert 'd1' in str(t)
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assert 'option 1' in str(t)
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def test_no_options():
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t = tables.RollTable([fixture_no_options])
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t = types.RollTable([fixture_no_options])
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assert str(t)
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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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types.RollTable([fixture_no_options]),
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types.RollTable([fixture_one_choice]),
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types.RollTable([fixture_metadata + fixture_source]),
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types.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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assert repr(tables.RollTable([fixture_no_options]))
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assert repr(tables.RollTable([fixture_one_choice]))
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assert repr(tables.RollTable([fixture_metadata + fixture_source]))
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assert repr(tables.RollTable([fixture_source]))
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assert repr(types.RollTable([fixture_no_options]))
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assert repr(types.RollTable([fixture_one_choice]))
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assert repr(types.RollTable([fixture_metadata + fixture_source]))
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assert repr(types.RollTable([fixture_source]))
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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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tables.RollTable([fixture_no_options]),
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tables.RollTable([fixture_lists_and_dicts]),
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types.RollTable([fixture_no_options]),
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types.RollTable([fixture_one_choice]),
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types.RollTable([fixture_metadata + fixture_source]),
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types.RollTable([fixture_source]),
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types.RollTable([fixture_no_options]),
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types.RollTable([fixture_lists_and_dicts]),
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])
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def test_as_dict(table):
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for src in table.datasources:
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