Source code for pydash.collections

"""
Functions that operate on lists and dicts.

.. versionadded:: 1.0.0
"""

from functools import cmp_to_key
import random

import pydash as pyd

from .helpers import callit, cmp, getargcount, iterator, iteriteratee


__all__ = (
    "at",
    "count_by",
    "every",
    "filter_",
    "find",
    "find_last",
    "flat_map",
    "flat_map_deep",
    "flat_map_depth",
    "for_each",
    "for_each_right",
    "group_by",
    "includes",
    "invoke_map",
    "key_by",
    "map_",
    "nest",
    "order_by",
    "partition",
    "pluck",
    "reduce_",
    "reduce_right",
    "reductions",
    "reductions_right",
    "reject",
    "sample",
    "sample_size",
    "shuffle",
    "size",
    "some",
    "sort_by",
)


[docs]def at(collection, *paths): """ Creates a list of elements from the specified indexes, or keys, of the collection. Indexes may be specified as individual arguments or as arrays of indexes. Args: collection (list|dict): Collection to iterate over. *paths (mixed): The indexes of `collection` to retrieve, specified as individual indexes or arrays of indexes. Returns: list: filtered list Example: >>> at([1, 2, 3, 4], 0, 2) [1, 3] >>> at({'a': 1, 'b': 2, 'c': 3, 'd': 4}, 'a', 'c') [1, 3] >>> at({'a': 1, 'b': 2, 'c': {'d': {'e': 3}}}, 'a', ['c', 'd', 'e']) [1, 3] .. versionadded:: 1.0.0 .. versionchanged:: 4.1.0 Support deep path access. """ return pyd.properties(*paths)(collection)
[docs]def count_by(collection, iteratee=None): """ Creates an object composed of keys generated from the results of running each element of `collection` through the iteratee. Args: collection (list|dict): Collection to iterate over. iteratee (mixed, optional): Iteratee applied per iteration. Returns: dict: Dict containing counts by key. Example: >>> results = count_by([1, 2, 1, 2, 3, 4]) >>> assert results == {1: 2, 2: 2, 3: 1, 4: 1} >>> results = count_by(['a', 'A', 'B', 'b'], lambda x: x.lower()) >>> assert results == {'a': 2, 'b': 2} >>> results = count_by({'a': 1, 'b': 1, 'c': 3, 'd': 3}) >>> assert results == {1: 2, 3: 2} .. versionadded:: 1.0.0 """ ret = {} for result in iteriteratee(collection, iteratee): ret.setdefault(result[0], 0) ret[result[0]] += 1 return ret
[docs]def every(collection, predicate=None): """ Checks if the predicate returns a truthy value for all elements of a collection. The predicate is invoked with three arguments: ``(value, index|key, collection)``. If a property name is passed for predicate, the created :func:`pluck` style predicate will return the property value of the given element. If an object is passed for predicate, the created :func:`.matches` style predicate will return ``True`` for elements that have the properties of the given object, else ``False``. Args: collection (list|dict): Collection to iterate over. predicate (mixed, optional): Predicate applied per iteration. Returns: bool: Whether all elements are truthy. Example: >>> every([1, True, 'hello']) True >>> every([1, False, 'hello']) False >>> every([{'a': 1}, {'a': True}, {'a': 'hello'}], 'a') True >>> every([{'a': 1}, {'a': False}, {'a': 'hello'}], 'a') False >>> every([{'a': 1}, {'a': 1}], {'a': 1}) True >>> every([{'a': 1}, {'a': 2}], {'a': 1}) False .. versionadded:: 1.0.0 .. versionchanged: 4.0.0 Removed alias ``all_``. """ if predicate: cbk = pyd.iteratee(predicate) collection = (cbk(item) for item in collection) return all(collection)
[docs]def filter_(collection, predicate=None): """ Iterates over elements of a collection, returning a list of all elements the predicate returns truthy for. Args: collection (list|dict): Collection to iterate over. predicate (mixed, optional): Predicate applied per iteration. Returns: list: Filtered list. Example: >>> results = filter_([{'a': 1}, {'b': 2}, {'a': 1, 'b': 3}], {'a': 1}) >>> assert results == [{'a': 1}, {'a': 1, 'b': 3}] >>> filter_([1, 2, 3, 4], lambda x: x >= 3) [3, 4] .. versionadded:: 1.0.0 .. versionchanged:: 4.0.0 Removed alias ``select``. """ return [value for is_true, value, _, _ in iteriteratee(collection, predicate) if is_true]
[docs]def find(collection, predicate=None): """ Iterates over elements of a collection, returning the first element that the predicate returns truthy for. Args: collection (list|dict): Collection to iterate over. predicate (mixed, optional): Predicate applied per iteration. Returns: mixed: First element found or ``None``. Example: >>> find([1, 2, 3, 4], lambda x: x >= 3) 3 >>> find([{'a': 1}, {'b': 2}, {'a': 1, 'b': 2}], {'a': 1}) {'a': 1} .. versionadded:: 1.0.0 .. versionchanged:: 4.0.0 Removed aliases ``detect`` and ``find_where``. """ search = (value for is_true, value, _, _ in iteriteratee(collection, predicate) if is_true) return next(search, None)
[docs]def find_last(collection, predicate=None): """ This method is like :func:`find` except that it iterates over elements of a `collection` from right to left. Args: collection (list|dict): Collection to iterate over. predicate (mixed, optional): Predicate applied per iteration. Returns: mixed: Last element found or ``None``. Example: >>> find_last([1, 2, 3, 4], lambda x: x >= 3) 4 >>> results = find_last([{'a': 1}, {'b': 2}, {'a': 1, 'b': 2}],\ {'a': 1}) >>> assert results == {'a': 1, 'b': 2} .. versionadded:: 1.0.0 """ search = ( value for is_true, value, _, _ in iteriteratee(collection, predicate, reverse=True) if is_true ) return next(search, None)
[docs]def flat_map(collection, iteratee=None): """ Creates a flattened list of values by running each element in collection thru `iteratee` and flattening the mapped results. The `iteratee` is invoked with three arguments: ``(value, index|key, collection)``. Args: collection (list|dict): Collection to iterate over. iteratee (mixed, optional): Iteratee applied per iteration. Returns: list: Flattened mapped list. Example: >>> duplicate = lambda n: [[n, n]] >>> flat_map([1, 2], duplicate) [[1, 1], [2, 2]] .. versionadded:: 4.0.0 """ return pyd.flatten(itermap(collection, iteratee=iteratee))
[docs]def flat_map_deep(collection, iteratee=None): """ This method is like :func:`flat_map` except that it recursively flattens the mapped results. Args: collection (list|dict): Collection to iterate over. iteratee (mixed, optional): Iteratee applied per iteration. Returns: list: Flattened mapped list. Example: >>> duplicate = lambda n: [[n, n]] >>> flat_map_deep([1, 2], duplicate) [1, 1, 2, 2] .. versionadded:: 4.0.0 """ return pyd.flatten_deep(itermap(collection, iteratee=iteratee))
[docs]def flat_map_depth(collection, iteratee=None, depth=1): """ This method is like :func:`flat_map` except that it recursively flattens the mapped results up to `depth` times. Args: collection (list|dict): Collection to iterate over. iteratee (mixed, optional): Iteratee applied per iteration. Returns: list: Flattened mapped list. Example: >>> duplicate = lambda n: [[n, n]] >>> flat_map_depth([1, 2], duplicate, 1) [[1, 1], [2, 2]] >>> flat_map_depth([1, 2], duplicate, 2) [1, 1, 2, 2] .. versionadded:: 4.0.0 """ return pyd.flatten_depth(itermap(collection, iteratee=iteratee), depth=depth)
[docs]def for_each(collection, iteratee=None): """ Iterates over elements of a collection, executing the iteratee for each element. Args: collection (list|dict): Collection to iterate over. iteratee (mixed, optional): Iteratee applied per iteration. Returns: list|dict: `collection` Example: >>> results = {} >>> def cb(x): results[x] = x ** 2 >>> for_each([1, 2, 3, 4], cb) [1, 2, 3, 4] >>> assert results == {1: 1, 2: 4, 3: 9, 4: 16} .. versionadded:: 1.0.0 .. versionchanged:: 4.0.0 Removed alias ``each``. """ next((None for ret, _, _, _ in iteriteratee(collection, iteratee) if ret is False), None) return collection
[docs]def for_each_right(collection, iteratee): """ This method is like :func:`for_each` except that it iterates over elements of a `collection` from right to left. Args: collection (list|dict): Collection to iterate over. iteratee (mixed, optional): Iteratee applied per iteration. Returns: list|dict: `collection` Example: >>> results = {'total': 1} >>> def cb(x): results['total'] = x * results['total'] >>> for_each_right([1, 2, 3, 4], cb) [1, 2, 3, 4] >>> assert results == {'total': 24} .. versionadded:: 1.0.0 .. versionchanged:: 4.0.0 Removed alias ``each_right``. """ next( (None for ret, _, _, _ in iteriteratee(collection, iteratee, reverse=True) if ret is False), None, ) return collection
[docs]def group_by(collection, iteratee=None): """ Creates an object composed of keys generated from the results of running each element of a `collection` through the iteratee. Args: collection (list|dict): Collection to iterate over. iteratee (mixed, optional): Iteratee applied per iteration. Returns: dict: Results of grouping by `iteratee`. Example: >>> results = group_by([{'a': 1, 'b': 2}, {'a': 3, 'b': 4}], 'a') >>> assert results == {1: [{'a': 1, 'b': 2}], 3: [{'a': 3, 'b': 4}]} >>> results = group_by([{'a': 1, 'b': 2}, {'a': 3, 'b': 4}], {'a': 1}) >>> assert results == {False: [{'a': 3, 'b': 4}],\ True: [{'a': 1, 'b': 2}]} .. versionadded:: 1.0.0 """ ret = {} cbk = pyd.iteratee(iteratee) for value in collection: key = cbk(value) ret.setdefault(key, []) ret[key].append(value) return ret
[docs]def includes(collection, target, from_index=0): """ Checks if a given value is present in a collection. If `from_index` is negative, it is used as the offset from the end of the collection. Args: collection (list|dict): Collection to iterate over. target (mixed): Target value to compare to. from_index (int, optional): Offset to start search from. Returns: bool: Whether `target` is in `collection`. Example: >>> includes([1, 2, 3, 4], 2) True >>> includes([1, 2, 3, 4], 2, from_index=2) False >>> includes({'a': 1, 'b': 2, 'c': 3, 'd': 4}, 2) True .. versionadded:: 1.0.0 .. versionchanged:: 4.0.0 Renamed from ``contains`` to ``includes`` and removed alias ``include``. """ if isinstance(collection, dict): collection = collection.values() else: # only makes sense to do this if `collection` is not a dict collection = collection[from_index:] return target in collection
[docs]def invoke_map(collection, path, *args, **kwargs): """ Invokes the method at `path` of each element in `collection`, returning a list of the results of each invoked method. Any additional arguments are provided to each invoked method. If `path` is a function, it's invoked for each element in `collection`. Args: collection (list|dict): Collection to iterate over. path (str|func): String path to method to invoke or callable to invoke for each element in `collection`. args (optional): Arguments to pass to method call. kwargs (optional): Keyword arguments to pass to method call. Returns: list: List of results of invoking method of each item. Example: >>> items = [{'a': [{'b': 1}]}, {'a': [{'c': 2}]}] >>> expected = [{'b': 1}.items(), {'c': 2}.items()] >>> invoke_map(items, 'a[0].items') == expected True .. versionadded:: 4.0.0 """ return map_(collection, lambda item: pyd.invoke(item, path, *args, **kwargs))
[docs]def key_by(collection, iteratee=None): """ Creates an object composed of keys generated from the results of running each element of the collection through the given iteratee. Args: collection (list|dict): Collection to iterate over. iteratee (mixed, optional): Iteratee applied per iteration. Returns: dict: Results of indexing by `iteratee`. Example: >>> results = key_by([{'a': 1, 'b': 2}, {'a': 3, 'b': 4}], 'a') >>> assert results == {1: {'a': 1, 'b': 2}, 3: {'a': 3, 'b': 4}} .. versionadded:: 1.0.0 .. versionchanged:: 4.0.0 Renamed from ``index_by`` to ``key_by``. """ ret = {} cbk = pyd.iteratee(iteratee) for value in collection: ret[cbk(value)] = value return ret
[docs]def map_(collection, iteratee=None): """ Creates an array of values by running each element in the collection through the iteratee. The iteratee is invoked with three arguments: ``(value, index|key, collection)``. If a property name is passed for iteratee, the created :func:`pluck` style iteratee will return the property value of the given element. If an object is passed for iteratee, the created :func:`.matches` style iteratee will return ``True`` for elements that have the properties of the given object, else ``False``. Args: collection (list|dict): Collection to iterate over. iteratee (mixed, optional): Iteratee applied per iteration. Returns: list: Mapped list. Example: >>> map_([1, 2, 3, 4], str) ['1', '2', '3', '4'] >>> map_([{'a': 1, 'b': 2}, {'a': 3, 'b': 4}, {'a': 5, 'b': 6}], 'a') [1, 3, 5] >>> map_([[[0, 1]], [[2, 3]], [[4, 5]]], '0.1') [1, 3, 5] >>> map_([{'a': {'b': 1}}, {'a': {'b': 2}}], 'a.b') [1, 2] >>> map_([{'a': {'b': [0, 1]}}, {'a': {'b': [2, 3]}}], 'a.b[1]') [1, 3] .. versionadded:: 1.0.0 .. versionchanged:: 4.0.0 Removed alias ``collect``. """ return list(itermap(collection, iteratee))
[docs]def nest(collection, *properties): """ This method is like :func:`group_by` except that it supports nested grouping by multiple string `properties`. If only a single key is given, it is like calling ``group_by(collection, prop)``. Args: collection (list|dict): Collection to iterate over. *properties (str): Properties to nest by. Returns: dict: Results of nested grouping by `properties`. Example: >>> results = nest([{'shape': 'square', 'color': 'red', 'qty': 5},\ {'shape': 'square', 'color': 'blue', 'qty': 10},\ {'shape': 'square', 'color': 'orange', 'qty': 5},\ {'shape': 'circle', 'color': 'yellow', 'qty': 5},\ {'shape': 'circle', 'color': 'pink', 'qty': 10},\ {'shape': 'oval', 'color': 'purple', 'qty': 5}],\ 'shape', 'qty') >>> expected = {\ 'square': {5: [{'shape': 'square', 'color': 'red', 'qty': 5},\ {'shape': 'square', 'color': 'orange', 'qty': 5}],\ 10: [{'shape': 'square', 'color': 'blue', 'qty': 10}]},\ 'circle': {5: [{'shape': 'circle', 'color': 'yellow', 'qty': 5}],\ 10: [{'shape': 'circle', 'color': 'pink', 'qty': 10}]},\ 'oval': {5: [{'shape': 'oval', 'color': 'purple', 'qty': 5}]}} >>> results == expected True .. versionadded:: 4.3.0 """ if not properties: return collection properties = pyd.flatten(properties) first, rest = properties[0], properties[1:] return pyd.map_values(group_by(collection, first), lambda value: nest(value, *rest))
[docs]def order_by(collection, keys, orders=None, reverse=False): """ This method is like :func:`sort_by` except that it sorts by key names instead of an iteratee function. Keys can be sorted in descending order by prepending a ``"-"`` to the key name (e.g. ``"name"`` would become ``"-name"``) or by passing a list of boolean sort options via `orders` where ``True`` is ascending and ``False`` is descending. Args: collection (list|dict): Collection to iterate over. keys (list): List of keys to sort by. By default, keys will be sorted in ascending order. To sort a key in descending order, prepend a ``"-"`` to the key name. For example, to sort the key value for ``"name"`` in descending order, use ``"-name"``. orders (list, optional): List of boolean sort orders to apply for each key. ``True`` corresponds to ascending order while ``False`` is descending. Defaults to ``None``. reverse (bool, optional): Whether to reverse the sort. Defaults to ``False``. Returns: list: Sorted list. Example: >>> items = [{'a': 2, 'b': 1}, {'a': 3, 'b': 2}, {'a': 1, 'b': 3}] >>> results = order_by(items, ['b', 'a']) >>> assert results == [{'a': 2, 'b': 1},\ {'a': 3, 'b': 2},\ {'a': 1, 'b': 3}] >>> results = order_by(items, ['a', 'b']) >>> assert results == [{'a': 1, 'b': 3},\ {'a': 2, 'b': 1},\ {'a': 3, 'b': 2}] >>> results = order_by(items, ['-a', 'b']) >>> assert results == [{'a': 3, 'b': 2},\ {'a': 2, 'b': 1},\ {'a': 1, 'b': 3}] >>> results = order_by(items, ['a', 'b'], [False, True]) >>> assert results == [{'a': 3, 'b': 2},\ {'a': 2, 'b': 1},\ {'a': 1, 'b': 3}] .. versionadded:: 3.0.0 .. versionchanged:: 3.2.0 Added `orders` argument. .. versionchanged:: 3.2.0 Added :func:`sort_by_order` as alias. .. versionchanged:: 4.0.0 Renamed from ``order_by`` to ``order_by`` and removed alias ``sort_by_order``. """ if isinstance(collection, dict): collection = collection.values() # Maintain backwards compatibility. if pyd.is_boolean(orders): reverse = orders orders = None comparers = [] if orders: for i, key in enumerate(keys): if pyd.has(orders, i): order = 1 if orders[i] else -1 else: order = 1 comparers.append((pyd.property_(key), order)) else: for key in keys: if key.startswith("-"): order = -1 key = key[1:] else: order = 1 comparers.append((pyd.property_(key), order)) def comparison(left, right): # pylint: disable=useless-else-on-loop,missing-docstring for func, mult in comparers: result = cmp(func(left), func(right)) if result: return mult * result else: return 0 return sorted(collection, key=cmp_to_key(comparison), reverse=reverse)
[docs]def partition(collection, predicate=None): """ Creates an array of elements split into two groups, the first of which contains elements the `predicate` returns truthy for, while the second of which contains elements the `predicate` returns falsey for. The `predicate` is invoked with three arguments: ``(value, index|key, collection)``. If a property name is provided for `predicate` the created :func:`pluck` style predicate returns the property value of the given element. If an object is provided for `predicate` the created :func:`.matches` style predicate returns ``True`` for elements that have the properties of the given object, else ``False``. Args: collection (list|dict): Collection to iterate over. predicate (mixed, optional): Predicate applied per iteration. Returns: list: List of grouped elements. Example: >>> partition([1, 2, 3, 4], lambda x: x >= 3) [[3, 4], [1, 2]] .. versionadded:: 1.1.0 """ trues = [] falses = [] for is_true, value, _, _ in iteriteratee(collection, predicate): if is_true: trues.append(value) else: falses.append(value) return [trues, falses]
[docs]def pluck(collection, path): """ Retrieves the value of a specified property from all elements in the collection. Args: collection (list): List of dicts. path (str|list): Collection's path to pluck Returns: list: Plucked list. Example: >>> pluck([{'a': 1, 'b': 2}, {'a': 3, 'b': 4}, {'a': 5, 'b': 6}], 'a') [1, 3, 5] >>> pluck([[[0, 1]], [[2, 3]], [[4, 5]]], '0.1') [1, 3, 5] >>> pluck([{'a': {'b': 1}}, {'a': {'b': 2}}], 'a.b') [1, 2] >>> pluck([{'a': {'b': [0, 1]}}, {'a': {'b': [2, 3]}}], 'a.b.1') [1, 3] >>> pluck([{'a': {'b': [0, 1]}}, {'a': {'b': [2, 3]}}], ['a', 'b', 1]) [1, 3] .. versionadded:: 1.0.0 .. versionchanged:: 4.0.0 Function removed. .. versionchanged:: 4.0.1 Made property access deep. """ return map_(collection, pyd.property_(path))
[docs]def reduce_(collection, iteratee=None, accumulator=None): """ Reduces a collection to a value which is the accumulated result of running each element in the collection through the iteratee, where each successive iteratee execution consumes the return value of the previous execution. Args: collection (list|dict): Collection to iterate over. iteratee (mixed): Iteratee applied per iteration. accumulator (mixed, optional): Initial value of aggregator. Default is to use the result of the first iteration. Returns: mixed: Accumulator object containing results of reduction. Example: >>> reduce_([1, 2, 3, 4], lambda total, x: total * x) 24 .. versionadded:: 1.0.0 .. versionchanged:: 4.0.0 Removed aliases ``foldl`` and ``inject``. """ iterable = iterator(collection) if accumulator is None: try: _, accumulator = next(iterable) except StopIteration: raise TypeError("reduce_() of empty sequence with no initial value") result = accumulator if iteratee is None: iteratee = pyd.identity argcount = 1 else: argcount = getargcount(iteratee, maxargs=3) for index, item in iterable: result = callit(iteratee, result, item, index, argcount=argcount) return result
[docs]def reduce_right(collection, iteratee=None, accumulator=None): """ This method is like :func:`reduce_` except that it iterates over elements of a `collection` from right to left. Args: collection (list|dict): Collection to iterate over. iteratee (mixed): Iteratee applied per iteration. accumulator (mixed, optional): Initial value of aggregator. Default is to use the result of the first iteration. Returns: mixed: Accumulator object containing results of reduction. Example: >>> reduce_right([1, 2, 3, 4], lambda total, x: total ** x) 4096 .. versionadded:: 1.0.0 .. versionchanged:: 3.2.1 Fix bug where collection was not reversed correctly. .. versionchanged:: 4.0.0 Removed alias ``foldr``. """ if not isinstance(collection, dict): collection = list(collection)[::-1] return reduce_(collection, iteratee, accumulator)
[docs]def reductions(collection, iteratee=None, accumulator=None, from_right=False): """ This function is like :func:`reduce_` except that it returns a list of every intermediate value in the reduction operation. Args: collection (list|dict): Collection to iterate over. iteratee (mixed): Iteratee applied per iteration. accumulator (mixed, optional): Initial value of aggregator. Default is to use the result of the first iteration. Returns: list: Results of each reduction operation. Example: >>> reductions([1, 2, 3, 4], lambda total, x: total * x) [2, 6, 24] Note: The last element of the returned list would be the result of using :func:`reduce_`. .. versionadded:: 2.0.0 """ if iteratee is None: iteratee = pyd.identity argcount = 1 else: argcount = getargcount(iteratee, maxargs=3) results = [] def interceptor(result, item, index): result = callit(iteratee, result, item, index, argcount=argcount) results.append(result) return result reducer = reduce_right if from_right else reduce_ reducer(collection, interceptor, accumulator) return results
[docs]def reductions_right(collection, iteratee=None, accumulator=None): """ This method is like :func:`reductions` except that it iterates over elements of a `collection` from right to left. Args: collection (list|dict): Collection to iterate over. iteratee (mixed): Iteratee applied per iteration. accumulator (mixed, optional): Initial value of aggregator. Default is to use the result of the first iteration. Returns: list: Results of each reduction operation. Example: >>> reductions_right([1, 2, 3, 4], lambda total, x: total ** x) [64, 4096, 4096] Note: The last element of the returned list would be the result of using :func:`reduce_`. .. versionadded:: 2.0.0 """ return reductions(collection, iteratee, accumulator, from_right=True)
[docs]def reject(collection, predicate=None): """ The opposite of :func:`filter_` this method returns the elements of a collection that the predicate does **not** return truthy for. Args: collection (list|dict): Collection to iterate over. predicate (mixed, optional): Predicate applied per iteration. Returns: list: Rejected elements of `collection`. Example: >>> reject([1, 2, 3, 4], lambda x: x >= 3) [1, 2] >>> reject([{'a': 0}, {'a': 1}, {'a': 2}], 'a') [{'a': 0}] >>> reject([{'a': 0}, {'a': 1}, {'a': 2}], {'a': 1}) [{'a': 0}, {'a': 2}] .. versionadded:: 1.0.0 """ return [value for is_true, value, _, _ in iteriteratee(collection, predicate) if not is_true]
[docs]def sample(collection): """ Retrieves a random element from a given `collection`. Args: collection (list|dict): Collection to iterate over. Returns: mixed: Random element from the given collection. Example: >>> items = [1, 2, 3, 4, 5] >>> results = sample(items) >>> assert results in items .. versionadded:: 1.0.0 .. versionchanged:: 4.0.0 Moved multiple samples functionality to :func:`sample_size`. This function now only returns a single random sample. """ return random.choice(collection)
[docs]def sample_size(collection, n=None): """ Retrieves list of `n` random elements from a collection. Args: collection (list|dict): Collection to iterate over. n (int, optional): Number of random samples to return. Returns: list: List of `n` sampled collection values. Examples: >>> items = [1, 2, 3, 4, 5] >>> results = sample_size(items, 2) >>> assert len(results) == 2 >>> assert set(items).intersection(results) == set(results) .. versionadded:: 4.0.0 """ num = min(n or 1, len(collection)) return random.sample(collection, num)
[docs]def shuffle(collection): """ Creates a list of shuffled values, using a version of the Fisher-Yates shuffle. Args: collection (list|dict): Collection to iterate over. Returns: list: Shuffled list of values. Example: >>> items = [1, 2, 3, 4] >>> results = shuffle(items) >>> assert len(results) == len(items) >>> assert set(results) == set(items) .. versionadded:: 1.0.0 """ if isinstance(collection, dict): collection = collection.values() # Make copy of collection since random.shuffle works on list in-place. collection = list(collection) # NOTE: random.shuffle uses Fisher-Yates. random.shuffle(collection) return collection
[docs]def size(collection): """ Gets the size of the `collection` by returning `len(collection)` for iterable objects. Args: collection (list|dict): Collection to iterate over. Returns: int: Collection length. Example: >>> size([1, 2, 3, 4]) 4 .. versionadded:: 1.0.0 """ return len(collection)
[docs]def some(collection, predicate=None): """ Checks if the predicate returns a truthy value for any element of a collection. The predicate is invoked with three arguments: ``(value, index|key, collection)``. If a property name is passed for predicate, the created :func:`map_` style predicate will return the property value of the given element. If an object is passed for predicate, the created :func:`.matches` style predicate will return ``True`` for elements that have the properties of the given object, else ``False``. Args: collection (list|dict): Collection to iterate over. predicate (mixed, optional): Predicate applied per iteration. Returns: bool: Whether any of the elements are truthy. Example: >>> some([False, True, 0]) True >>> some([False, 0, None]) False >>> some([1, 2, 3, 4], lambda x: x >= 3) True >>> some([1, 2, 3, 4], lambda x: x == 0) False .. versionadded:: 1.0.0 .. versionchanged:: 4.0.0 Removed alias ``any_``. """ if predicate: cbk = pyd.iteratee(predicate) collection = (cbk(item) for item in collection) return any(collection)
[docs]def sort_by(collection, iteratee=None, reverse=False): """ Creates a list of elements, sorted in ascending order by the results of running each element in a `collection` through the iteratee. Args: collection (list|dict): Collection to iterate over. iteratee (mixed, optional): Iteratee applied per iteration. reverse (bool, optional): Whether to reverse the sort. Defaults to ``False``. Returns: list: Sorted list. Example: >>> sort_by({'a': 2, 'b': 3, 'c': 1}) [1, 2, 3] >>> sort_by({'a': 2, 'b': 3, 'c': 1}, reverse=True) [3, 2, 1] >>> sort_by([{'a': 2}, {'a': 3}, {'a': 1}], 'a') [{'a': 1}, {'a': 2}, {'a': 3}] .. versionadded:: 1.0.0 """ if isinstance(collection, dict): collection = collection.values() return sorted(collection, key=pyd.iteratee(iteratee), reverse=reverse)
# # Utility methods not a part of the main API # def itermap(collection, iteratee=None): """Generative mapper.""" for result in iteriteratee(collection, iteratee): yield result[0]