API Reference#

All public functions are available from the main module.

import pydash

pydash.<function>

This is the recommended way to use pydash.

# OK (importing main module)
import pydash
pydash.where({})

# OK (import from main module)
from pydash import where
where({})

# NOT RECOMMENDED (importing from submodule)
from pydash.collections import where

Only the main pydash module API is guaranteed to adhere to semver. It’s possible that backwards incompatibility outside the main module API could be broken between minor releases.

py_ Instance#

There is a special py_ instance available from pydash that supports method calling and method chaining from a single object:

from pydash import py_

# Method calling
py_.initial([1, 2, 3, 4, 5]) == [1, 2, 3, 4]

# Method chaining
py_([1, 2, 3, 4, 5]).initial().value() == [1, 2, 3, 4]

# Method aliasing to underscore suffixed methods that shadow builtin names
py_.map is py_.map_
py_([1, 2, 3]).map(_.to_string).value() == py_([1, 2, 3]).map_(_.to_string).value()

The py_ instance is basically a combination of using pydash.<function> and pydash.chain.

A full listing of aliased py_ methods:

_.object is pydash.arrays.object_()
_.slice is pydash.arrays.slice_()
_.zip is pydash.arrays.zip_()
_.all is pydash.collections.all_()
_.any is pydash.collections.any_()
_.filter is pydash.collections.filter_()
_.map is pydash.collections.map_()
_.max is pydash.collections.max_()
_.min is pydash.collections.min_()
_.reduce is pydash.collections.reduce_()
_.pow is pydash.numerical.pow_()
_.round is pydash.numerical.round_()
_.sum is pydash.numerical.sum_()
_.property is pydash.utilities.property_()
_.range is pydash.utilities.range_()

Arrays#

Functions that operate on lists.

New in version 1.0.0.

pydash.arrays.chunk(array: Sequence[T], size: int = 1) → List[Sequence[T]][source]#

Creates a list of elements split into groups the length of size. If array can’t be split evenly, the final chunk will be the remaining elements.

Parameters:

array – List to chunk.
size – Chunk size. Defaults to 1.

Returns:

New list containing chunks of array.

Example

>>> chunk([1, 2, 3, 4, 5], 2)
[[1, 2], [3, 4], [5]]

New in version 1.1.0.

pydash.arrays.compact(array: Iterable[T | None]) → List[T][source]#

Creates a list with all falsey values of array removed.

Parameters:: array – List to compact.
Returns:: Compacted list.

Example

>>> compact(['', 1, 0, True, False, None])
[1, True]

New in version 1.0.0.

pydash.arrays.concat(*arrays: Iterable[T]) → List[T][source]#

Concatenates zero or more lists into one.

Parameters:: arrays – Lists to concatenate.
Returns:: Concatenated list.

Example

>>> concat([1, 2], [3, 4], [[5], [6]])
[1, 2, 3, 4, [5], [6]]

New in version 2.0.0.

Changed in version 4.0.0: Renamed from cat to concat.

pydash.arrays.difference(array: Iterable[T], *others: Iterable[T]) → List[T][source]#

Creates a list of list elements not present in others.

Parameters:

array – List to process.
others – Lists to check.

Returns:

Difference between others.

Example

>>> difference([1, 2, 3], [1], [2])
[3]

New in version 1.0.0.

This method is like difference() except that it accepts an iteratee which is invoked for each element of each array to generate the criterion by which they’re compared. The order and references of result values are determined by array. The iteratee is invoked with one argument: (value).

Parameters:

array – The array to find the difference of.
others – Lists to check for difference with array.

Keyword Arguments:

iteratee – Function to transform the elements of the arrays. Defaults to identity().

Returns:

Difference between others.

Example

>>> difference_by([1.2, 1.5, 1.7, 2.8], [0.9, 3.2], round)
[1.5, 1.7]

New in version 4.0.0.

pydash.arrays.difference_with(array: Iterable[T], *others: Iterable[T2], comparator: Callable[[T, T2], Any] | None) → List[T][source]#

pydash.arrays.difference_with(array: Iterable[T], *others: Iterable[T2] | Callable[[T, T2], Any]) → List[T]

This method is like difference() except that it accepts a comparator which is invoked to compare the elements of all arrays. The order and references of result values are determined by the first array. The comparator is invoked with two arguments: (arr_val, oth_val).

Parameters:

array – The array to find the difference of.
others – Lists to check for difference with array.

Keyword Arguments:

comparator – Function to compare the elements of the arrays. Defaults to is_equal().

Returns:

Difference between others.

Example

>>> array = ['apple', 'banana', 'pear']
>>> others = (['avocado', 'pumpkin'], ['peach'])
>>> comparator = lambda a, b: a[0] == b[0]
>>> difference_with(array, *others, comparator=comparator)
['banana']

New in version 4.0.0.

pydash.arrays.drop(array: Sequence[T], n: int = 1) → List[T][source]#

Creates a slice of array with n elements dropped from the beginning.

Parameters:

array – List to process.
n – Number of elements to drop. Defaults to 1.

Returns:

Dropped list.

Example

>>> drop([1, 2, 3, 4], 2)
[3, 4]

New in version 1.0.0.

Changed in version 1.1.0: Added n argument and removed as alias of rest().

Changed in version 3.0.0: Made n default to 1.

pydash.arrays.drop_right(array: Sequence[T], n: int = 1) → List[T][source]#

Creates a slice of array with n elements dropped from the end.

Parameters:

array – List to process.
n – Number of elements to drop. Defaults to 1.

Returns:

Dropped list.

Example

>>> drop_right([1, 2, 3, 4], 2)
[1, 2]

New in version 1.1.0.

Changed in version 3.0.0: Made n default to 1.

pydash.arrays.drop_right_while(array: Sequence[T], predicate: Callable[[T, int, List[T]], Any]) → List[T][source]#

pydash.arrays.drop_right_while(array: Sequence[T], predicate: Callable[[T, int], Any]) → List[T]

pydash.arrays.drop_right_while(array: Sequence[T], predicate: Callable[[T], Any]) → List[T]

pydash.arrays.drop_right_while(array: Sequence[T], predicate: None = None) → List[T]

Creates a slice of array excluding elements dropped from the end. Elements are dropped until the predicate returns falsey. The predicate is invoked with three arguments: (value, index, array).

Parameters:

array – List to process.
predicate – Predicate called per iteration

Returns:

Dropped list.

Example

>>> drop_right_while([1, 2, 3, 4], lambda x: x >= 3)
[1, 2]

New in version 1.1.0.

pydash.arrays.drop_while(array: Sequence[T], predicate: Callable[[T, int, List[T]], Any]) → List[T][source]#

pydash.arrays.drop_while(array: Sequence[T], predicate: Callable[[T, int], Any]) → List[T]

pydash.arrays.drop_while(array: Sequence[T], predicate: Callable[[T], Any]) → List[T]

pydash.arrays.drop_while(array: Sequence[T], predicate: None = None) → List[T]

Creates a slice of array excluding elements dropped from the beginning. Elements are dropped until the predicate returns falsey. The predicate is invoked with three arguments: (value, index, array).

Parameters:

array – List to process.
predicate – Predicate called per iteration

Returns:

Dropped list.

Example

>>> drop_while([1, 2, 3, 4], lambda x: x < 3)
[3, 4]

New in version 1.1.0.

Creates a unique list of duplicate values from array. If iteratee is passed, each element of array is passed through an iteratee before duplicates are computed. The iteratee is invoked with three arguments: (value, index, array). If an object path is passed for iteratee, the created iteratee will return the path value of the given element. If an object is passed for iteratee, the created filter style iteratee will return True for elements that have the properties of the given object, else False.

Parameters:

array – List to process.
iteratee – Iteratee applied per iteration.

Returns:

List of duplicates.

Example

>>> duplicates([0, 1, 3, 2, 3, 1])
[3, 1]

New in version 3.0.0.

pydash.arrays.fill(array: Sequence[T], value: T2, start: int = 0, end: int | None = None) → List[T | T2][source]#

Fills elements of array with value from start up to, but not including, end.

Parameters:

array – List to fill.
value – Value to fill with.
start – Index to start filling. Defaults to 0.
end – Index to end filling. Defaults to len(array).

Returns:

Filled array.

Example

>>> fill([1, 2, 3, 4, 5], 0)
[0, 0, 0, 0, 0]
>>> fill([1, 2, 3, 4, 5], 0, 1, 3)
[1, 0, 0, 4, 5]
>>> fill([1, 2, 3, 4, 5], 0, 0, 100)
[0, 0, 0, 0, 0]

Warning

array is modified in place.

New in version 3.1.0.

pydash.arrays.find_index(array: Iterable[T], predicate: Callable[[T, int, List[T]], Any]) → int[source]#

pydash.arrays.find_index(array: Iterable[T], predicate: Callable[[T, int], Any]) → int

pydash.arrays.find_index(array: Iterable[T], predicate: Callable[[T], Any]) → int

pydash.arrays.find_index(array: Iterable[Any], predicate: int | str | List | Tuple | Dict) → int

pydash.arrays.find_index(array: Iterable[Any], predicate: None = None) → int

This method is similar to pydash.collections.find(), except that it returns the index of the element that passes the predicate check, instead of the element itself.

Parameters:

array – List to process.
predicate – Predicate applied per iteration.

Returns:

Index of found item or -1 if not found.

Example

>>> find_index([1, 2, 3, 4], lambda x: x >= 3)
2
>>> find_index([1, 2, 3, 4], lambda x: x > 4)
-1

New in version 1.0.0.

pydash.arrays.find_last_index(array: Iterable[T], predicate: Callable[[T, int, List[T]], Any]) → int[source]#

pydash.arrays.find_last_index(array: Iterable[T], predicate: Callable[[T, int], Any]) → int

pydash.arrays.find_last_index(array: Iterable[T], predicate: Callable[[T], Any]) → int

pydash.arrays.find_last_index(array: Iterable[Any], predicate: int | str | List | Tuple | Dict) → int

pydash.arrays.find_last_index(array: Iterable[Any], predicate: None = None) → int

This method is similar to find_index(), except that it iterates over elements from right to left.

Parameters:

array – List to process.
predicate – Predicate applied per iteration.

Returns:

Index of found item or -1 if not found.

Example

>>> find_last_index([1, 2, 3, 4], lambda x: x >= 3)
3
>>> find_last_index([1, 2, 3, 4], lambda x: x > 4)
-1

New in version 1.0.0.

pydash.arrays.flatten(array: Iterable[Iterable[T]]) → List[T][source]#

pydash.arrays.flatten(array: Iterable[T]) → List[T]

Flattens array a single level deep.

Parameters:: array – List to flatten.
Returns:: Flattened list.

Example

>>> flatten([[1], [2, [3]], [[4]]])
[1, 2, [3], [4]]

New in version 1.0.0.

Changed in version 2.0.0: Removed callback option. Added is_deep option. Made it shallow by default.

Changed in version 4.0.0: Removed is_deep option. Use flatten_deep() instead.

pydash.arrays.flatten_deep(array: Iterable) → List[source]#

Flattens an array recursively.

Parameters:: array – List to flatten.
Returns:: Flattened list.

Example

>>> flatten_deep([[1], [2, [3]], [[4]]])
[1, 2, 3, 4]

New in version 2.0.0.

pydash.arrays.flatten_depth(array: Iterable, depth: int = 1) → List[source]#

Recursively flatten array up to depth times.

Parameters:

array – List to flatten.
depth – Depth to flatten to. Defaults to 1.

Returns:

Flattened list.

Example

>>> flatten_depth([[[1], [2, [3]], [[4]]]], 1)
[[1], [2, [3]], [[4]]]
>>> flatten_depth([[[1], [2, [3]], [[4]]]], 2)
[1, 2, [3], [4]]
>>> flatten_depth([[[1], [2, [3]], [[4]]]], 3)
[1, 2, 3, 4]
>>> flatten_depth([[[1], [2, [3]], [[4]]]], 4)
[1, 2, 3, 4]

New in version 4.0.0.

pydash.arrays.from_pairs(pairs: Iterable[Tuple[T, T2]]) → Dict[T, T2][source]#

pydash.arrays.from_pairs(pairs: Iterable[List[T | T2]]) → Dict[T | T2, T | T2]

Returns a dict from the given list of pairs.

Parameters:: pairs – List of key-value pairs.
Returns:: dict

Example

>>> from_pairs([['a', 1], ['b', 2]]) == {'a': 1, 'b': 2}
True

New in version 4.0.0.

pydash.arrays.head(array: Sequence[T]) → T | None[source]#

Return the first element of array.

Parameters:: array – List to process.
Returns:: First element of list.

Example

>>> head([1, 2, 3, 4])
1

New in version 1.0.0.

Changed in version Renamed: from first to head.

pydash.arrays.index_of(array: Sequence[T], value: T, from_index: int = 0) → int[source]#

Gets the index at which the first occurrence of value is found.

Parameters:

array – List to search.
value – Value to search for.
from_index – Index to search from.

Returns:

Index of found item or -1 if not found.

Example

>>> index_of([1, 2, 3, 4], 2)
1
>>> index_of([2, 1, 2, 3], 2, from_index=1)
2

New in version 1.0.0.

pydash.arrays.initial(array: Sequence[T]) → Sequence[T][source]#

Return all but the last element of array.

Parameters:: array – List to process.
Returns:: Initial part of array.

Example

>>> initial([1, 2, 3, 4])
[1, 2, 3]

New in version 1.0.0.

pydash.arrays.intercalate(array: Iterable[Iterable[T]], separator: T2) → List[T | T2][source]#

pydash.arrays.intercalate(array: Iterable[T], separator: T2) → List[T | T2]

Like intersperse() for lists of lists but shallowly flattening the result.

Parameters:

array – List to intercalate.
separator – Element to insert.

Returns:

Intercalated list.

Example

>>> intercalate([1, [2], [3], 4], 'x')
[1, 'x', 2, 'x', 3, 'x', 4]

New in version 2.0.0.

pydash.arrays.interleave(*arrays: Iterable[T]) → List[T][source]#

Merge multiple lists into a single list by inserting the next element of each list by sequential round-robin into the new list.

Parameters:: arrays – Lists to interleave.
Returns:: Interleaved list.

Example

>>> interleave([1, 2, 3], [4, 5, 6], [7, 8, 9])
[1, 4, 7, 2, 5, 8, 3, 6, 9]

New in version 2.0.0.

pydash.arrays.intersection(array: Sequence[T], *others: Iterable[Any]) → List[T][source]#

Computes the intersection of all the passed-in arrays.

Parameters:

array – The array to find the intersection of.
others – Lists to check for intersection with array.

Returns:

Intersection of provided lists.

Example

>>> intersection([1, 2, 3], [1, 2, 3, 4, 5], [2, 3])
[2, 3]

>>> intersection([1, 2, 3])
[1, 2, 3]

New in version 1.0.0.

Changed in version 4.0.0: Support finding intersection of unhashable types.

This method is like intersection() except that it accepts an iteratee which is invoked for each element of each array to generate the criterion by which they’re compared. The order and references of result values are determined by array. The iteratee is invoked with one argument: (value).

Parameters:

array – The array to find the intersection of.
others – Lists to check for intersection with array.

Keyword Arguments:

iteratee – Function to transform the elements of the arrays. Defaults to identity().

Returns:

Intersection of provided lists.

Example

>>> intersection_by([1.2, 1.5, 1.7, 2.8], [0.9, 3.2], round)
[1.2, 2.8]

New in version 4.0.0.

pydash.arrays.intersection_with(array: Sequence[T], *others: Iterable[T2], comparator: Callable[[T, T2], Any]) → List[T][source]#

pydash.arrays.intersection_with(array: Sequence[T], *others: Iterable[T2] | Callable[[T, T2], Any]) → List[T]

This method is like intersection() except that it accepts a comparator which is invoked to compare the elements of all arrays. The order and references of result values are determined by the first array. The comparator is invoked with two arguments: (arr_val, oth_val).

Parameters:

array – The array to find the intersection of.
others – Lists to check for intersection with array.

Keyword Arguments:

comparator – Function to compare the elements of the arrays. Defaults to is_equal().

Returns:

Intersection of provided lists.

Example

>>> array = ['apple', 'banana', 'pear']
>>> others = (['avocado', 'pumpkin'], ['peach'])
>>> comparator = lambda a, b: a[0] == b[0]
>>> intersection_with(array, *others, comparator=comparator)
['pear']

New in version 4.0.0.

pydash.arrays.intersperse(array: Iterable[T], separator: T2) → List[T | T2][source]#

Insert a separating element between the elements of array.

Parameters:

array – List to intersperse.
separator – Element to insert.

Returns:

Interspersed list.

Example

>>> intersperse([1, [2], [3], 4], 'x')
[1, 'x', [2], 'x', [3], 'x', 4]

New in version 2.0.0.

pydash.arrays.last(array: Sequence[T]) → T | None[source]#

Return the last element of array.

Parameters:: array – List to process.
Returns:: Last part of array.

Example

>>> last([1, 2, 3, 4])
4

New in version 1.0.0.

pydash.arrays.last_index_of(array: Sequence[Any], value: Any, from_index: int | None = None) → int[source]#

Gets the index at which the last occurrence of value is found.

Parameters:

array – List to search.
value – Value to search for.
from_index – Index to search from.

Returns:

Index of found item or -1 if not found.

Example

>>> last_index_of([1, 2, 2, 4], 2)
2
>>> last_index_of([1, 2, 2, 4], 2, from_index=1)
1

New in version 1.0.0.

pydash.arrays.mapcat(array: Iterable[T], iteratee: Callable[[T, int, List[T]], List[T2] | List[List[T2]]]) → List[T2][source]#

pydash.arrays.mapcat(array: Iterable[T], iteratee: Callable[[T, int, List[T]], T2]) → List[T2]

pydash.arrays.mapcat(array: Iterable[T], iteratee: Callable[[T, int], List[T2] | List[List[T2]]]) → List[T2]

pydash.arrays.mapcat(array: Iterable[T], iteratee: Callable[[T, int], T2]) → List[T2]

pydash.arrays.mapcat(array: Iterable[T], iteratee: Callable[[T], List[T2] | List[List[T2]]]) → List[T2]

pydash.arrays.mapcat(array: Iterable[T], iteratee: Callable[[T], T2]) → List[T2]

pydash.arrays.mapcat(array: Iterable[List[T] | List[List[T]]], iteratee: None = None) → List[T | List[T]]

Map an iteratee to each element of a list and concatenate the results into a single list using concat().

Parameters:

array – List to map and concatenate.
iteratee – Iteratee to apply to each element.

Returns:

Mapped and concatenated list.

Example

>>> mapcat(range(4), lambda x: list(range(x)))
[0, 0, 1, 0, 1, 2]

New in version 2.0.0.

pydash.arrays.nth(array: Iterable[T], pos: int = 0) → T | None[source]#

Gets the element at index n of array.

Parameters:

array – List passed in by the user.
pos – Index of element to return.

Returns:

Returns the element at pos.

Example

>>> nth([1, 2, 3], 0)
1
>>> nth([3, 4, 5, 6], 2)
5
>>> nth([11, 22, 33], -1)
33
>>> nth([11, 22, 33])
11

New in version 4.0.0.

pydash.arrays.pull(array: List[T], *values: T) → List[T][source]#

Removes all provided values from the given array.

Parameters:

array – List to pull from.
values – Values to remove.

Returns:

Modified array.

Warning

array is modified in place.

Example

>>> pull([1, 2, 2, 3, 3, 4], 2, 3)
[1, 4]

New in version 1.0.0.

Changed in version 4.0.0: pull() method now calls pull_all() method for the desired functionality.

pydash.arrays.pull_all(array: List[T], values: Iterable[T]) → List[T][source]#

Removes all provided values from the given array.

Parameters:

array – Array to modify.
values – Values to remove.

Returns:

Modified array.

Example

>>> pull_all([1, 2, 2, 3, 3, 4], [2, 3])
[1, 4]

New in version 4.0.0.

This method is like pull_all() except that it accepts iteratee which is invoked for each element of array and values to generate the criterion by which they’re compared. The iteratee is invoked with one argument: (value).

Parameters:

array – Array to modify.
values – Values to remove.
iteratee – Function to transform the elements of the arrays. Defaults to identity().

Returns:

Modified array.

Example

>>> array = [{'x': 1}, {'x': 2}, {'x': 3}, {'x': 1}]
>>> pull_all_by(array, [{'x': 1}, {'x': 3}], 'x')
[{'x': 2}]

New in version 4.0.0.

pydash.arrays.pull_all_with(array: List[T], values: Iterable[T], comparator: Callable[[T, T], Any] | None = None) → List[T][source]#

This method is like pull_all() except that it accepts comparator which is invoked to compare elements of array to values. The comparator is invoked with two arguments: (arr_val, oth_val).

Parameters:

array – Array to modify.
values – Values to remove.
comparator – Function to compare the elements of the arrays. Defaults to is_equal().

Returns:

Modified array.

Example

>>> array = [{'x': 1, 'y': 2}, {'x': 3, 'y': 4}, {'x': 5, 'y': 6}]
>>> res = pull_all_with(array, [{'x': 3, 'y': 4}], lambda a, b: a == b)
>>> res == [{'x': 1, 'y': 2}, {'x': 5, 'y': 6}]
True
>>> array = [{'x': 1, 'y': 2}, {'x': 3, 'y': 4}, {'x': 5, 'y': 6}]
>>> res = pull_all_with(array, [{'x': 3, 'y': 4}], lambda a, b: a != b)
>>> res == [{'x': 3, 'y': 4}]
True

New in version 4.0.0.

pydash.arrays.pull_at(array: List[T], *indexes: int) → List[T][source]#

Removes elements from array corresponding to the specified indexes and returns a list of the removed elements. Indexes may be specified as a list of indexes or as individual arguments.

Parameters:

array – List to pull from.
indexes – Indexes to pull.

Returns:

Modified array.

Warning

array is modified in place.

Example

>>> pull_at([1, 2, 3, 4], 0, 2)
[2, 4]

New in version 1.1.0.

pydash.arrays.push(array: List[T], *items: T2) → List[T | T2][source]#

Push items onto the end of array and return modified array.

Parameters:

array – List to push to.
items – Items to append.

Returns:

Modified array.

Warning

array is modified in place.

Example

>>> array = [1, 2, 3]
>>> push(array, 4, 5, [6])
[1, 2, 3, 4, 5, [6]]

New in version 2.2.0.

Changed in version 4.0.0: Removed alias append.

pydash.arrays.remove(array: List[T], predicate: Callable[[T, int, List[T]], Any] | Callable[[T, int], Any] | Callable[[T], Any] | None = None) → List[T][source]#

Removes all elements from a list that the predicate returns truthy for and returns an array of removed elements.

Parameters:

array – List to remove elements from.
predicate – Predicate applied per iteration.

Returns:

Removed elements of array.

Warning

array is modified in place.

Example

>>> array = [1, 2, 3, 4]
>>> items = remove(array, lambda x: x >= 3)
>>> items
[3, 4]
>>> array
[1, 2]

New in version 1.0.0.

pydash.arrays.reverse(array: SequenceT) → SequenceT[source]#

Return array in reverse order.

Parameters:: array – Object to process.
Returns:: Reverse of object.

Example

>>> reverse([1, 2, 3, 4])
[4, 3, 2, 1]

New in version 2.2.0.

pydash.arrays.shift(array: List[T]) → T[source]#

Remove the first element of array and return it.

Parameters:: array – List to shift.
Returns:: First element of array.

Warning

array is modified in place.

Example

>>> array = [1, 2, 3, 4]
>>> item = shift(array)
>>> item
1
>>> array
[2, 3, 4]

New in version 2.2.0.

pydash.arrays.slice_(array: SequenceT, start: int = 0, end: int | None = None) → SequenceT[source]#

Slices array from the start index up to, but not including, the end index.

Parameters:

array – Array to slice.
start – Start index. Defaults to 0.
end – End index. Defaults to selecting the value at start index.

Returns:

Sliced list.

Example

>>> slice_([1, 2, 3, 4])
[1]
>>> slice_([1, 2, 3, 4], 1)
[2]
>>> slice_([1, 2, 3, 4], 1, 3)
[2, 3]

New in version 1.1.0.

pydash.arrays.sort(array: t.List['SupportsRichComparisonT'], comparator: None = None, key: None = None, reverse: bool = False) → t.List['SupportsRichComparisonT'][source]#

pydash.arrays.sort(array: List[T], comparator: Callable[[T, T], int], *, reverse: bool = False) → List[T]

pydash.arrays.sort(array: List[T], *, key: t.Callable[[T], 'SupportsRichComparisonT'], reverse: bool = False) → List[T]

Sort array using optional comparator, key, and reverse options and return sorted array.

Note

Python 3 removed the option to pass a custom comparator function and instead only allows a key function. Therefore, if a comparator function is passed in, it will be converted to a key function automatically using functools.cmp_to_key.

Parameters:

array – List to sort.
comparator – A custom comparator function used to sort the list. Function should accept two arguments and return a negative, zero, or position number depending on whether the first argument is considered smaller than, equal to, or larger than the second argument. Defaults to None. This argument is mutually exclusive with key.
key – A function of one argument used to extract a comparator key from each list element. Defaults to None. This argument is mutually exclusive with comparator.
reverse – Whether to reverse the sort. Defaults to False.

Returns:

Sorted list.

Warning

array is modified in place.

Example

>>> sort([2, 1, 4, 3])
[1, 2, 3, 4]
>>> sort([2, 1, 4, 3], reverse=True)
[4, 3, 2, 1]
>>> results = sort([{'a': 2, 'b': 1},                            {'a': 3, 'b': 2},                            {'a': 0, 'b': 3}],                           key=lambda item: item['a'])
>>> assert results == [{'a': 0, 'b': 3},                               {'a': 2, 'b': 1},                               {'a': 3, 'b': 2}]

New in version 2.2.0.

pydash.arrays.sorted_index(array: Sequence[SupportsRichComparisonT], value: SupportsRichComparisonT) → int[source]#

Uses a binary search to determine the lowest index at which value should be inserted into array in order to maintain its sort order.

Parameters:

array – List to inspect.
value – Value to evaluate.

Returns:

Returns the index at which value should be inserted into array.

Example

>>> sorted_index([1, 2, 2, 3, 4], 2)
1

New in version 1.0.0.

Changed in version 4.0.0: Move iteratee support to sorted_index_by().

pydash.arrays.sorted_index_by(array: Sequence[T], value: T, iteratee: t.Union[IterateeObjT, t.Callable[[T], 'SupportsRichComparisonT']]) → int[source]#

pydash.arrays.sorted_index_by(array: t.Sequence['SupportsRichComparisonT'], value: SupportsRichComparisonT, iteratee: None = None) → int

This method is like sorted_index() except that it accepts iteratee which is invoked for value and each element of array to compute their sort ranking. The iteratee is invoked with one argument: (value).

Parameters:

array – List to inspect.
value – Value to evaluate.
iteratee – The iteratee invoked per element. Defaults to identity().

Returns:

Returns the index at which value should be inserted into array.

Example

>>> array = [{'x': 4}, {'x': 5}]
>>> sorted_index_by(array, {'x': 4}, lambda o: o['x'])
0
>>> sorted_index_by(array, {'x': 4}, 'x')
0

New in version 4.0.0.

pydash.arrays.sorted_index_of(array: Sequence[SupportsRichComparisonT], value: SupportsRichComparisonT) → int[source]#

Returns the index of the matched value from the sorted array, else -1.

Parameters:

array – Array to inspect.
value – Value to search for.

Returns:

Returns the index of the first matched value, else -1.

Example

>>> sorted_index_of([3, 5, 7, 10], 3)
0
>>> sorted_index_of([10, 10, 5, 7, 3], 10)
-1

New in version 4.0.0.

pydash.arrays.sorted_last_index(array: Sequence[SupportsRichComparisonT], value: SupportsRichComparisonT) → int[source]#

This method is like sorted_index() except that it returns the highest index at which value should be inserted into array in order to maintain its sort order.

Parameters:

array – List to inspect.
value – Value to evaluate.

Returns:

Returns the index at which value should be inserted into array.

Example

>>> sorted_last_index([1, 2, 2, 3, 4], 2)
3

New in version 1.1.0.

Changed in version 4.0.0: Move iteratee support to sorted_last_index_by().

pydash.arrays.sorted_last_index_by(array: Sequence[T], value: T, iteratee: t.Union[IterateeObjT, t.Callable[[T], 'SupportsRichComparisonT']]) → int[source]#

pydash.arrays.sorted_last_index_by(array: t.Sequence['SupportsRichComparisonT'], value: SupportsRichComparisonT, iteratee: None = None) → int

This method is like sorted_last_index() except that it accepts iteratee which is invoked for value and each element of array to compute their sort ranking. The iteratee is invoked with one argument: (value).

Parameters:

array – List to inspect.
value – Value to evaluate.
iteratee – The iteratee invoked per element. Defaults to identity().

Returns:

Returns the index at which value should be inserted into array.

Example

>>> array = [{'x': 4}, {'x': 5}]
>>> sorted_last_index_by(array, {'x': 4}, lambda o: o['x'])
1
>>> sorted_last_index_by(array, {'x': 4}, 'x')
1

pydash.arrays.sorted_last_index_of(array: Sequence[SupportsRichComparisonT], value: SupportsRichComparisonT) → int[source]#

This method is like last_index_of() except that it performs a binary search on a sorted array.

Parameters:

array – Array to inspect.
value – Value to search for.

Returns:

Returns the index of the matched value, else -1.

Example

>>> sorted_last_index_of([4, 5, 5, 5, 6], 5)
3
>>> sorted_last_index_of([6, 5, 5, 5, 4], 6)
-1

New in version 4.0.0.

pydash.arrays.sorted_uniq(array: Iterable[SupportsRichComparisonT]) → List[SupportsRichComparisonT][source]#

Return sorted array with unique elements.

Parameters:: array – List of values to be sorted.
Returns:: List of unique elements in a sorted fashion.

Example

>>> sorted_uniq([4, 2, 2, 5])
[2, 4, 5]
>>> sorted_uniq([-2, -2, 4, 1])
[-2, 1, 4]

New in version 4.0.0.

pydash.arrays.sorted_uniq_by(array: Iterable[SupportsRichComparisonT], iteratee: Callable[[SupportsRichComparisonT], SupportsRichComparisonT] | None = None) → List[SupportsRichComparisonT][source]#

This method is like sorted_uniq() except that it accepts iteratee which is invoked for each element in array to generate the criterion by which uniqueness is computed. The order of result values is determined by the order they occur in the array. The iteratee is invoked with one argument: (value).

Parameters:

array – List of values to be sorted.
iteratee – Function to transform the elements of the arrays. Defaults to identity().

Returns:

Unique list.

Example

>>> sorted_uniq_by([3, 2, 1, 3, 2, 1], lambda val: val % 2)
[2, 3]

New in version 4.0.0.

pydash.arrays.splice(array: MutableSequenceT, start: int, count: int | None = None, *items: Any) → MutableSequenceT[source]#

Modify the contents of array by inserting elements starting at index start and removing count number of elements after.

Parameters:

array – List to splice.
start – Start to splice at.
count – Number of items to remove starting at start. If None then all items after start are removed. Defaults to None.
items – Elements to insert starting at start. Each item is inserted in the order given.

Returns:

The removed elements of array or the spliced string.

Warning

array is modified in place if list.

Example

>>> array = [1, 2, 3, 4]
>>> splice(array, 1)
[2, 3, 4]
>>> array
[1]
>>> array = [1, 2, 3, 4]
>>> splice(array, 1, 2)
[2, 3]
>>> array
[1, 4]
>>> array = [1, 2, 3, 4]
>>> splice(array, 1, 2, 0, 0)
[2, 3]
>>> array
[1, 0, 0, 4]

New in version 2.2.0.

Changed in version 3.0.0: Support string splicing.

pydash.arrays.split_at(array: Sequence[T], index: int) → List[Sequence[T]][source]#

Returns a list of two lists composed of the split of array at index.

Parameters:

array – List to split.
index – Index to split at.

Returns:

Split list.

Example

>>> split_at([1, 2, 3, 4], 2)
[[1, 2], [3, 4]]

New in version 2.0.0.

pydash.arrays.tail(array: Sequence[T]) → Sequence[T][source]#

Return all but the first element of array.

Parameters:: array – List to process.
Returns:: Rest of the list.

Example

>>> tail([1, 2, 3, 4])
[2, 3, 4]

New in version 1.0.0.

Changed in version 4.0.0: Renamed from rest to tail.

pydash.arrays.take(array: Sequence[T], n: int = 1) → Sequence[T][source]#

Creates a slice of array with n elements taken from the beginning.

Parameters:

array – List to process.
n – Number of elements to take. Defaults to 1.

Returns:

Taken list.

Example

>>> take([1, 2, 3, 4], 2)
[1, 2]

New in version 1.0.0.

Changed in version 1.1.0: Added n argument and removed as alias of first().

Changed in version 3.0.0: Made n default to 1.

pydash.arrays.take_right(array: Sequence[T], n: int = 1) → Sequence[T][source]#

Creates a slice of array with n elements taken from the end.

Parameters:

array – List to process.
n – Number of elements to take. Defaults to 1.

Returns:

Taken list.

Example

>>> take_right([1, 2, 3, 4], 2)
[3, 4]

New in version 1.1.0.

Changed in version 3.0.0: Made n default to 1.

pydash.arrays.take_right_while(array: Sequence[T], predicate: Callable[[T, int, List[T]], Any]) → Sequence[T][source]#

pydash.arrays.take_right_while(array: Sequence[T], predicate: Callable[[T, int], Any]) → Sequence[T]

pydash.arrays.take_right_while(array: Sequence[T], predicate: Callable[[T], Any]) → Sequence[T]

pydash.arrays.take_right_while(array: Sequence[T], predicate: None = None) → Sequence[T]

Creates a slice of array with elements taken from the end. Elements are taken until the predicate returns falsey. The predicate is invoked with three arguments: (value, index, array).

Parameters:

array – List to process.
predicate – Predicate called per iteration

Returns:

Dropped list.

Example

>>> take_right_while([1, 2, 3, 4], lambda x: x >= 3)
[3, 4]

New in version 1.1.0.

pydash.arrays.take_while(array: Sequence[T], predicate: Callable[[T, int, List[T]], Any]) → List[T][source]#

pydash.arrays.take_while(array: Sequence[T], predicate: Callable[[T, int], Any]) → List[T]

pydash.arrays.take_while(array: Sequence[T], predicate: Callable[[T], Any]) → List[T]

pydash.arrays.take_while(array: Sequence[T], predicate: None = None) → List[T]

Creates a slice of array with elements taken from the beginning. Elements are taken until the predicate returns falsey. The predicate is invoked with three arguments: (value, index, array).

Parameters:

array – List to process.
predicate – Predicate called per iteration

Returns:

Taken list.

Example

>>> take_while([1, 2, 3, 4], lambda x: x < 3)
[1, 2]

New in version 1.1.0.

pydash.arrays.union(array: Sequence[T]) → List[T][source]#

pydash.arrays.union(array: Sequence[T], *others: Sequence[T2]) → List[T | T2]

Computes the union of the passed-in arrays.

Parameters:

array – List to union with.
others – Lists to unionize with array.

Returns:

Unionized list.

Example

>>> union([1, 2, 3], [2, 3, 4], [3, 4, 5])
[1, 2, 3, 4, 5]

New in version 1.0.0.

pydash.arrays.union_by(array: Sequence[T], *others: Iterable[T], iteratee: Callable[[T], Any]) → List[T][source]#

pydash.arrays.union_by(array: Sequence[T], *others: Iterable[T] | Callable[[T], Any]) → List[T]

This method is similar to union() except that it accepts iteratee which is invoked for each element of each array to generate the criterion by which uniqueness is computed.

Parameters:

array – List to unionize with.
others – Lists to unionize with array.

Keyword Arguments:

iteratee – Function to invoke on each element.

Returns:

Unionized list.

Example

>>> union_by([1, 2, 3], [2, 3, 4], iteratee=lambda x: x % 2)
[1, 2]
>>> union_by([1, 2, 3], [2, 3, 4], iteratee=lambda x: x % 9)
[1, 2, 3, 4]

New in version 4.0.0.

pydash.arrays.union_with(array: Sequence[T], *others: Iterable[T2], comparator: Callable[[T, T2], Any]) → List[T][source]#

pydash.arrays.union_with(array: Sequence[T], *others: Iterable[T2] | Callable[[T, T2], Any]) → List[T]

This method is like union() except that it accepts comparator which is invoked to compare elements of arrays. Result values are chosen from the first array in which the value occurs.

Parameters:

array – List to unionize with.
others – Lists to unionize with array.

Keyword Arguments:

comparator – Function to compare the elements of the arrays. Defaults to is_equal().

Returns:

Unionized list.

Example

>>> comparator = lambda a, b: (a % 2) == (b % 2)
>>> union_with([1, 2, 3], [2, 3, 4], comparator=comparator)
[1, 2]
>>> union_with([1, 2, 3], [2, 3, 4])
[1, 2, 3, 4]

New in version 4.0.0.

pydash.arrays.uniq(array: Iterable[T]) → List[T][source]#

Creates a duplicate-value-free version of the array. If iteratee is passed, each element of array is passed through an iteratee before uniqueness is computed. The iteratee is invoked with three arguments: (value, index, array). If an object path is passed for iteratee, the created iteratee will return the path value of the given element. If an object is passed for iteratee, the created filter style iteratee will return True for elements that have the properties of the given object, else False.

Parameters:: array – List to process.
Returns:: Unique list.

Example

>>> uniq([1, 2, 3, 1, 2, 3])
[1, 2, 3]

New in version 1.0.0.

Changed in version 4.0.0:

Moved iteratee argument to uniq_by().
Removed alias unique.

pydash.arrays.uniq_by(array: Iterable[T], iteratee: Callable[[T], Any] | None = None) → List[T][source]#

This method is like uniq() except that it accepts iteratee which is invoked for each element in array to generate the criterion by which uniqueness is computed. The order of result values is determined by the order they occur in the array. The iteratee is invoked with one argument: (value).

Parameters:

array – List to process.
iteratee – Function to transform the elements of the arrays. Defaults to identity().

Returns:

Unique list.

Example

>>> uniq_by([1, 2, 3, 1, 2, 3], lambda val: val % 2)
[1, 2]

New in version 4.0.0.

pydash.arrays.uniq_with(array: Sequence[T], comparator: Callable[[T, T], Any] | None = None) → List[T][source]#

This method is like uniq() except that it accepts comparator which is invoked to compare elements of array. The order of result values is determined by the order they occur in the array.The comparator is invoked with two arguments: (value, other).

Parameters:

array – List to process.
comparator – Function to compare the elements of the arrays. Defaults to is_equal().

Returns:

Unique list.

Example

>>> uniq_with([1, 2, 3, 4, 5], lambda a, b: (a % 2) == (b % 2))
[1, 2]

New in version 4.0.0.

pydash.arrays.unshift(array: List[T], *items: T2) → List[T | T2][source]#

Insert the given elements at the beginning of array and return the modified list.

Parameters:

array – List to modify.
items – Items to insert.

Returns:

Modified list.

Warning

array is modified in place.

Example

>>> array = [1, 2, 3, 4]
>>> unshift(array, -1, -2)
[-1, -2, 1, 2, 3, 4]
>>> array
[-1, -2, 1, 2, 3, 4]

New in version 2.2.0.

pydash.arrays.unzip(array: Iterable[Iterable[T]]) → List[List[T]][source]#

The inverse of zip_(), this method splits groups of elements into lists composed of elements from each group at their corresponding indexes.

Parameters:: array – List to process.
Returns:: Unzipped list.

Example

>>> unzip([[1, 4, 7], [2, 5, 8], [3, 6, 9]])
[[1, 2, 3], [4, 5, 6], [7, 8, 9]]

New in version 1.0.0.

pydash.arrays.unzip_with(array: Iterable[Iterable[T]], iteratee: Callable[[T, T, int, List[T]], T2] | Callable[[T, T, int], T2] | Callable[[T, T], T2] | Callable[[T], T2]) → List[T2][source]#

pydash.arrays.unzip_with(array: Iterable[Iterable[T]], iteratee: None = None) → List[List[T]]

This method is like unzip() except that it accepts an iteratee to specify how regrouped values should be combined. The iteratee is invoked with four arguments: (accumulator, value, index, group).

Parameters:

array – List to process.
iteratee – Function to combine regrouped values.

Returns:

Unzipped list.

Example

>>> from pydash import add
>>> unzip_with([[1, 10, 100], [2, 20, 200]], add)
[3, 30, 300]

New in version 3.3.0.

pydash.arrays.without(array: Iterable[T], *values: T) → List[T][source]#

Creates an array with all occurrences of the passed values removed.

Parameters:

array – List to filter.
values – Values to remove.

Returns:

Filtered list.

Example

>>> without([1, 2, 3, 2, 4, 4], 2, 4)
[1, 3]

New in version 1.0.0.

pydash.arrays.xor(array: Iterable[T], *lists: Iterable[T]) → List[T][source]#

Creates a list that is the symmetric difference of the provided lists.

Parameters:

array – List to process.
*lists – Lists to xor with.

Returns:

XOR’d list.

Example

>>> xor([1, 3, 4], [1, 2, 4], [2])
[3]

New in version 1.0.0.

pydash.arrays.xor_by(array: Iterable[T], *lists: Iterable[T] | Callable[[T], Any]) → List[T]

This method is like xor() except that it accepts iteratee which is invoked for each element of each arras to generate the criterion by which they’re compared. The order of result values is determined by the order they occur in the arrays. The iteratee is invoked with one argument: (value).

Parameters:

array – List to process.
*lists – Lists to xor with.

Keyword Arguments:

iteratee – Function to transform the elements of the arrays. Defaults to identity().

Returns:

XOR’d list.

Example

>>> xor_by([2.1, 1.2], [2.3, 3.4], round)
[1.2, 3.4]
>>> xor_by([{'x': 1}], [{'x': 2}, {'x': 1}], 'x')
[{'x': 2}]

New in version 4.0.0.

pydash.arrays.xor_with(array: Sequence[T], *lists: Iterable[T2], comparator: Callable[[T, T2], Any]) → List[T][source]#

pydash.arrays.xor_with(array: Sequence[T], *lists: Iterable[T2] | Callable[[T, T2], Any]) → List[T]

This method is like xor() except that it accepts comparator which is invoked to compare elements of arrays. The order of result values is determined by the order they occur in the arrays. The comparator is invoked with two arguments: (arr_val, oth_val).

Parameters:

array – List to process.
*lists – Lists to xor with.

Keyword Arguments:

comparator – Function to compare the elements of the arrays. Defaults to is_equal().

Returns:

XOR’d list.

Example

>>> objects = [{'x': 1, 'y': 2}, {'x': 2, 'y': 1}]
>>> others = [{'x': 1, 'y': 1}, {'x': 1, 'y': 2}]
>>> expected = [{'y': 1, 'x': 2}, {'y': 1, 'x': 1}]
>>> xor_with(objects, others, lambda a, b: a == b) == expected
True

New in version 4.0.0.

pydash.arrays.zip_(*arrays: Iterable[T]) → List[List[T]][source]#

Groups the elements of each array at their corresponding indexes. Useful for separate data sources that are coordinated through matching array indexes.

Parameters:: arrays – Lists to process.
Returns:: Zipped list.

Example

>>> zip_([1, 2, 3], [4, 5, 6], [7, 8, 9])
[[1, 4, 7], [2, 5, 8], [3, 6, 9]]

New in version 1.0.0.

pydash.arrays.zip_object(keys: Iterable[Tuple[T, T2]], values: None = None) → Dict[T, T2][source]#

pydash.arrays.zip_object(keys: Iterable[List[T | T2]], values: None = None) → Dict[T | T2, T | T2]

pydash.arrays.zip_object(keys: Iterable[T], values: List[T2]) → Dict[T, T2]

Creates a dict composed of lists of keys and values. Pass either a single two-dimensional list, i.e. [[key1, value1], [key2, value2]], or two lists, one of keys and one of corresponding values.

Parameters:

keys – Either a list of keys or a list of [key, value] pairs.
values – List of values to zip.

Returns:

Zipped dict.

Example

>>> zip_object([1, 2, 3], [4, 5, 6])
{1: 4, 2: 5, 3: 6}

New in version 1.0.0.

Changed in version 4.0.0: Removed alias object_.

pydash.arrays.zip_object_deep(keys: Iterable[Any], values: List[Any] | None = None) → Dict[source]#

This method is like zip_object() except that it supports property paths.

Parameters:

keys – Either a list of keys or a list of [key, value] pairs.
values – List of values to zip.

Returns:

Zipped dict.

Example

>>> expected = {'a': {'b': {'c': 1, 'd': 2}}}
>>> zip_object_deep(['a.b.c', 'a.b.d'], [1, 2]) == expected
True

New in version 4.0.0.

pydash.arrays.zip_with(*arrays: Iterable[T], iteratee: Callable[[T, T, int, List[T]], T2] | Callable[[T, T, int], T2] | Callable[[T, T], T2] | Callable[[T], T2]) → List[T2][source]#

pydash.arrays.zip_with(*arrays: Iterable[T]) → List[List[T]]

This method is like zip() except that it accepts an iteratee to specify how grouped values should be combined. The iteratee is invoked with four arguments: (accumulator, value, index, group).

Parameters:: *arrays – Lists to process.
Keyword Arguments:: iteratee (callable) – Function to combine grouped values.
Returns:: Zipped list of grouped elements.

Example

>>> from pydash import add
>>> zip_with([1, 2], [10, 20], [100, 200], add)
[111, 222]
>>> zip_with([1, 2], [10, 20], [100, 200], iteratee=add)
[111, 222]

New in version 3.3.0.

Chaining#

pydash.chaining.chain(value: ~pydash.chaining.chaining.T | ~pydash.helpers.Unset = <pydash.helpers.Unset object>) → Chain[T][source]#

Creates a Chain object which wraps the given value to enable intuitive method chaining. Chaining is lazy and won’t compute a final value until Chain.value() is called.

Parameters:: value – Value to initialize chain operations with.
Returns:: Instance of Chain initialized with value.

Example

>>> chain([1, 2, 3, 4]).map(lambda x: x * 2).sum().value()
20
>>> chain().map(lambda x: x * 2).sum()([1, 2, 3, 4])
20

>>> summer = chain([1, 2, 3, 4]).sum()
>>> new_summer = summer.plant([1, 2])
>>> new_summer.value()
3
>>> summer.value()
10

>>> def echo(item): print(item)
>>> summer = chain([1, 2, 3, 4]).for_each(echo).sum()
>>> committed = summer.commit()
1
2
3
4
>>> committed.value()
10
>>> summer.value()
1
2
3
4
10

New in version 1.0.0.

Changed in version 2.0.0: Made chaining lazy.

Changed in version 3.0.0:

Added support for late passing of value.
Added Chain.plant() for replacing initial chain value.
Added Chain.commit() for returning a new Chain instance initialized with the results from calling Chain.value().

pydash.chaining.tap(value: T, interceptor: Callable[[T], Any]) → T[source]#

Invokes interceptor with the value as the first argument and then returns value. The purpose of this method is to “tap into” a method chain in order to perform operations on intermediate results within the chain.

Parameters:

value – Current value of chain operation.
interceptor – Function called on value.

Returns:

value after interceptor call.

Example

>>> data = []
>>> def log(value): data.append(value)
>>> chain([1, 2, 3, 4]).map(lambda x: x * 2).tap(log).value()
[2, 4, 6, 8]
>>> data
[[2, 4, 6, 8]]

New in version 1.0.0.

pydash.chaining.thru(value: T, interceptor: Callable[[T], T2]) → T2[source]#

Returns the result of calling interceptor on value. The purpose of this method is to pass value through a function during a method chain.

Parameters:

value – Current value of chain operation.
interceptor – Function called with value.

Returns:

Results of interceptor(value).

Example

>>> chain([1, 2, 3, 4]).thru(lambda x: x * 2).value()
[1, 2, 3, 4, 1, 2, 3, 4]

New in version 2.0.0.

Collections#

Functions that operate on lists and dicts.

New in version 1.0.0.

pydash.collections.at(collection: Mapping[T, T2], *paths: T) → List[T2 | None][source]#

pydash.collections.at(collection: Mapping[T, Any], *paths: T | Iterable[T]) → List[Any]

pydash.collections.at(collection: Iterable[T], *paths: int) → List[T | None]

pydash.collections.at(collection: Iterable[Any], *paths: int | Iterable[int]) → List[Any]

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.

Parameters:

collection – Collection to iterate over.
*paths – The indexes of collection to retrieve, specified as individual indexes or arrays of indexes.

Returns:

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]

New in version 1.0.0.

Changed in version 4.1.0: Support deep path access.

pydash.collections.count_by(collection: Mapping[Any, T2], iteratee: None = None) → Dict[T2, int][source]#

pydash.collections.count_by(collection: Mapping[T, T2], iteratee: Callable[[T2, T, Dict[T, T2]], T3]) → Dict[T3, int]

pydash.collections.count_by(collection: Mapping[T, T2], iteratee: Callable[[T2, T], T3]) → Dict[T3, int]

pydash.collections.count_by(collection: Mapping[Any, T2], iteratee: Callable[[T2], T3]) → Dict[T3, int]

pydash.collections.count_by(collection: Iterable[T], iteratee: None = None) → Dict[T, int]

pydash.collections.count_by(collection: Iterable[T], iteratee: Callable[[T, int, List[T]], T2]) → Dict[T2, int]

pydash.collections.count_by(collection: Iterable[T], iteratee: Callable[[T, int], T2]) → Dict[T2, int]

pydash.collections.count_by(collection: Iterable[T], iteratee: Callable[[T], T2]) → Dict[T2, int]

Creates an object composed of keys generated from the results of running each element of collection through the iteratee.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.

Returns:

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}

New in version 1.0.0.

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 pluck() style predicate will return the property value of the given element. If an object is passed for predicate, the created matches() style predicate will return True for elements that have the properties of the given object, else False.

Parameters:

collection – Collection to iterate over.
predicate – Predicate applied per iteration.

Returns:

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

New in version 1.0.0.

Iterates over elements of a collection, returning a list of all elements the predicate returns truthy for.

Parameters:

collection – Collection to iterate over.
predicate – Predicate applied per iteration.

Returns:

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]

New in version 1.0.0.

Changed in version 4.0.0: Removed alias select.

Iterates over elements of a collection, returning the first element that the predicate returns truthy for.

Parameters:

collection – Collection to iterate over.
predicate – Predicate applied per iteration.

Returns:

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}

New in version 1.0.0.

Changed in version 4.0.0: Removed aliases detect and find_where.

This method is like find() except that it iterates over elements of a collection from right to left.

Parameters:

collection – Collection to iterate over.
predicate – Predicate applied per iteration.

Returns:

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}

New in version 1.0.0.

pydash.collections.flat_map(collection: Mapping[T, T2], iteratee: Callable[[T2, T, Dict[T, T2]], Iterable[T3]]) → List[T3][source]#

pydash.collections.flat_map(collection: Mapping[T, T2], iteratee: Callable[[T2, T], Iterable[T3]]) → List[T3]

pydash.collections.flat_map(collection: Mapping[Any, T2], iteratee: Callable[[T2], Iterable[T3]]) → List[T3]

pydash.collections.flat_map(collection: Mapping[T, T2], iteratee: Callable[[T2, T, Dict[T, T2]], T3]) → List[T3]

pydash.collections.flat_map(collection: Mapping[T, T2], iteratee: Callable[[T2, T], T3]) → List[T3]

pydash.collections.flat_map(collection: Mapping[Any, T2], iteratee: Callable[[T2], T3]) → List[T3]

pydash.collections.flat_map(collection: Mapping[Any, Iterable[T2]], iteratee: None = None) → List[T2]

pydash.collections.flat_map(collection: Mapping[Any, T2], iteratee: None = None) → List[T2]

pydash.collections.flat_map(collection: Iterable[T], iteratee: Callable[[T, int, List[T]], Iterable[T2]]) → List[T2]

pydash.collections.flat_map(collection: Iterable[T], iteratee: Callable[[T, int], Iterable[T2]]) → List[T2]

pydash.collections.flat_map(collection: Iterable[T], iteratee: Callable[[T], Iterable[T2]]) → List[T2]

pydash.collections.flat_map(collection: Iterable[T], iteratee: Callable[[T, int, List[T]], T2]) → List[T2]

pydash.collections.flat_map(collection: Iterable[T], iteratee: Callable[[T, int], T2]) → List[T2]

pydash.collections.flat_map(collection: Iterable[T], iteratee: Callable[[T], T2]) → List[T2]

pydash.collections.flat_map(collection: Iterable[Iterable[T]], iteratee: None = None) → List[T]

pydash.collections.flat_map(collection: Iterable[T], iteratee: None = None) → List[T]

Creates a flattened list of values by running each element in collection through iteratee and flattening the mapped results. The iteratee is invoked with three arguments: (value, index|key, collection).

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.

Returns:

Flattened mapped list.

Example

>>> duplicate = lambda n: [[n, n]]
>>> flat_map([1, 2], duplicate)
[[1, 1], [2, 2]]

New in version 4.0.0.

pydash.collections.flat_map_deep(collection: Mapping[T, T2], iteratee: Callable[[T2, T, Dict[T, T2]], Any] | None = None) → List[source]#

pydash.collections.flat_map_deep(collection: Mapping[T, T2], iteratee: Callable[[T2, T], Any] | None = None) → List

pydash.collections.flat_map_deep(collection: Mapping[Any, T2], iteratee: Callable[[T2], Any] | None = None) → List

pydash.collections.flat_map_deep(collection: Iterable[T], iteratee: Callable[[T, int, List[T]], Any] | None = None) → List

pydash.collections.flat_map_deep(collection: Iterable[T], iteratee: Callable[[T, int], Any] | None = None) → List

pydash.collections.flat_map_deep(collection: Iterable[T], iteratee: Callable[[T], Any] | None = None) → List

This method is like flat_map() except that it recursively flattens the mapped results.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.

Returns:

Flattened mapped list.

Example

>>> duplicate = lambda n: [[n, n]]
>>> flat_map_deep([1, 2], duplicate)
[1, 1, 2, 2]

New in version 4.0.0.

pydash.collections.flat_map_depth(collection: Mapping[T, T2], iteratee: Callable[[T2, T, Dict[T, T2]], Any] | None = None, depth: int = 1) → List[source]#

pydash.collections.flat_map_depth(collection: Mapping[T, T2], iteratee: Callable[[T2, T], Any] | None = None, depth: int = 1) → List

pydash.collections.flat_map_depth(collection: Mapping[Any, T2], iteratee: Callable[[T2], Any] | None = None, depth: int = 1) → List

pydash.collections.flat_map_depth(collection: Iterable[T], iteratee: Callable[[T, int, List[T]], Any] | None = None, depth: int = 1) → List

pydash.collections.flat_map_depth(collection: Iterable[T], iteratee: Callable[[T, int], Any] | None = None, depth: int = 1) → List

pydash.collections.flat_map_depth(collection: Iterable[T], iteratee: Callable[[T], Any] | None = None, depth: int = 1) → List

This method is like flat_map() except that it recursively flattens the mapped results up to depth times.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.

Returns:

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]

New in version 4.0.0.

Iterates over elements of a collection, executing the iteratee for each element.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.

Returns:

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}

New in version 1.0.0.

Changed in version 4.0.0: Removed alias each.

This method is like for_each() except that it iterates over elements of a collection from right to left.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.

Returns:

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}

New in version 1.0.0.

Changed in version 4.0.0: Removed alias each_right.

pydash.collections.group_by(collection: Iterable[T], iteratee: Callable[[T], T2]) → Dict[T2, List[T]][source]#

Creates an object composed of keys generated from the results of running each element of a collection through the iteratee.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.

Returns:

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}]}

New in version 1.0.0.

pydash.collections.includes(collection: Sequence | Dict, target: Any, from_index: int = 0) → bool[source]#

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.

Parameters:

collection – Collection to iterate over.
target – Target value to compare to.
from_index – Offset to start search from.

Returns:

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

New in version 1.0.0.

Changed in version 4.0.0: Renamed from contains to includes and removed alias include.

pydash.collections.invoke_map(collection: Iterable, path: Hashable | List[Hashable], *args: Any, **kwargs: Any) → List[Any][source]#

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.

Parameters:

collection – Collection to iterate over.
path – String path to method to invoke or callable to invoke for each element in collection.
args – Arguments to pass to method call.
kwargs – Keyword arguments to pass to method call.

Returns:

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

New in version 4.0.0.

pydash.collections.key_by(collection: Iterable[T], iteratee: Callable[[T], T2]) → Dict[T2, T][source]#

Creates an object composed of keys generated from the results of running each element of the collection through the given iteratee.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.

Returns:

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}}

New in version 1.0.0.

Changed in version 4.0.0: Renamed from index_by to key_by.

pydash.collections.map_(collection: Mapping[Any, T2], iteratee: Callable[[T2], T3]) → List[T3][source]#

pydash.collections.map_(collection: Mapping[T, T2], iteratee: Callable[[T2, T], T3]) → List[T3]

pydash.collections.map_(collection: Mapping[T, T2], iteratee: Callable[[T2, T, Dict[T, T2]], T3]) → List[T3]

pydash.collections.map_(collection: Iterable[T], iteratee: Callable[[T], T2]) → List[T2]

pydash.collections.map_(collection: Iterable[T], iteratee: Callable[[T, int], T2]) → List[T2]

pydash.collections.map_(collection: Iterable[T], iteratee: Callable[[T, int, List[T]], T2]) → List[T2]

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 pluck() style iteratee will return the property value of the given element. If an object is passed for iteratee, the created matches() style iteratee will return True for elements that have the properties of the given object, else False.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.

Returns:

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]

New in version 1.0.0.

Changed in version 4.0.0: Removed alias collect.

pydash.collections.nest(collection: Iterable, *properties: Any) → Any[source]#

This method is like 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).

Parameters:

collection – Collection to iterate over.
*properties – Properties to nest by.

Returns:

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

New in version 4.3.0.

pydash.collections.order_by(collection: Mapping[Any, T2], keys: Iterable[str | int], orders: Iterable[bool] | bool, reverse: bool = False) → List[T2][source]#

pydash.collections.order_by(collection: Mapping[Any, T2], keys: Iterable[str], orders: None = None, reverse: bool = False) → List[T2]

pydash.collections.order_by(collection: Iterable[T], keys: Iterable[str | int], orders: Iterable[bool] | bool, reverse: bool = False) → List[T]

pydash.collections.order_by(collection: Iterable[T], keys: Iterable[str], orders: None = None, reverse: bool = False) → List[T]

This method is like 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.

Parameters:

collection – Collection to iterate over.
keys – 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 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:

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}]

New in version 3.0.0.

Changed in version 3.2.0: Added orders argument.

Changed in version 3.2.0: Added sort_by_order() as alias.

Changed in version 4.0.0: Renamed from order_by to order_by and removed alias sort_by_order.

pydash.collections.partition(collection: Mapping[T, T2], predicate: Callable[[T2, T, Dict[T, T2]], Any]) → List[List[T2]][source]#

pydash.collections.partition(collection: Mapping[T, T2], predicate: Callable[[T2, T], Any]) → List[List[T2]]

pydash.collections.partition(collection: Mapping[Any, T2], predicate: Callable[[T2], Any]) → List[List[T2]]

pydash.collections.partition(collection: Iterable[T], predicate: Callable[[T, int, List[T]], Any]) → List[List[T]]

pydash.collections.partition(collection: Iterable[T], predicate: Callable[[T, int], Any]) → List[List[T]]

pydash.collections.partition(collection: Iterable[T], predicate: Callable[[T], Any]) → List[List[T]]

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 pluck() style predicate returns the property value of the given element.

If an object is provided for predicate the created matches() style predicate returns True for elements that have the properties of the given object, else False.

Parameters:

collection – Collection to iterate over.
predicate – Predicate applied per iteration.

Returns:

List of grouped elements.

Example

>>> partition([1, 2, 3, 4], lambda x: x >= 3)
[[3, 4], [1, 2]]

New in version 1.1.0.

pydash.collections.pluck(collection: Iterable, path: Hashable | List[Hashable]) → List[source]#

Retrieves the value of a specified property from all elements in the collection.

Parameters:

collection – List of dicts.
path – Collection’s path to pluck

Returns:

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]

New in version 1.0.0.

Changed in version 4.0.0: Function removed.

Changed in version 4.0.1: Made property access deep.

pydash.collections.reduce_(collection: Mapping[T, T2], iteratee: Callable[[T3, T2, T], T3], accumulator: T3) → T3[source]#

pydash.collections.reduce_(collection: Mapping[Any, T2], iteratee: Callable[[T3, T2], T3], accumulator: T3) → T3

pydash.collections.reduce_(collection: Mapping, iteratee: Callable[[T3], T3], accumulator: T3) → T3

pydash.collections.reduce_(collection: Mapping[T, T2], iteratee: Callable[[T2, T2, T], T2], accumulator: None = None) → T2

pydash.collections.reduce_(collection: Mapping[Any, T2], iteratee: Callable[[T2, T2], T2], accumulator: None = None) → T2

pydash.collections.reduce_(collection: Mapping, iteratee: Callable[[T], T], accumulator: None = None) → T

pydash.collections.reduce_(collection: Iterable[T], iteratee: Callable[[T2, T, int], T2], accumulator: T2) → T2

pydash.collections.reduce_(collection: Iterable[T], iteratee: Callable[[T2, T], T2], accumulator: T2) → T2

pydash.collections.reduce_(collection: Iterable, iteratee: Callable[[T2], T2], accumulator: T2) → T2

pydash.collections.reduce_(collection: Iterable[T], iteratee: Callable[[T, T, int], T], accumulator: None = None) → T

pydash.collections.reduce_(collection: Iterable[T], iteratee: Callable[[T, T], T], accumulator: None = None) → T

pydash.collections.reduce_(collection: Iterable, iteratee: Callable[[T], T], accumulator: None = None) → T

pydash.collections.reduce_(collection: Iterable[T], iteratee: None = None, accumulator: T | None = None) → T

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.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.
accumulator – Initial value of aggregator. Default is to use the result of the first iteration.

Returns:

Accumulator object containing results of reduction.

Example

>>> reduce_([1, 2, 3, 4], lambda total, x: total * x)
24

New in version 1.0.0.

Changed in version 4.0.0: Removed aliases foldl and inject.

pydash.collections.reduce_right(collection: Mapping[T, T2], iteratee: Callable[[T3, T2, T], T3], accumulator: T3) → T3[source]#

pydash.collections.reduce_right(collection: Mapping[Any, T2], iteratee: Callable[[T3, T2], T3], accumulator: T3) → T3

pydash.collections.reduce_right(collection: Mapping, iteratee: Callable[[T3], T3], accumulator: T3) → T3

pydash.collections.reduce_right(collection: Mapping[T, T2], iteratee: Callable[[T2, T2, T], T2], accumulator: None = None) → T2

pydash.collections.reduce_right(collection: Mapping[Any, T2], iteratee: Callable[[T2, T2], T2], accumulator: None = None) → T2

pydash.collections.reduce_right(collection: Mapping, iteratee: Callable[[T], T], accumulator: None = None) → T

pydash.collections.reduce_right(collection: Iterable[T], iteratee: Callable[[T2, T, int], T2], accumulator: T2) → T2

pydash.collections.reduce_right(collection: Iterable[T], iteratee: Callable[[T2, T], T2], accumulator: T2) → T2

pydash.collections.reduce_right(collection: Iterable, iteratee: Callable[[T2], T2], accumulator: T2) → T2

pydash.collections.reduce_right(collection: Iterable[T], iteratee: Callable[[T, T, int], T], accumulator: None = None) → T

pydash.collections.reduce_right(collection: Iterable[T], iteratee: Callable[[T, T], T], accumulator: None = None) → T

pydash.collections.reduce_right(collection: Iterable, iteratee: Callable[[T], T], accumulator: None = None) → T

pydash.collections.reduce_right(collection: Iterable[T], iteratee: None = None, accumulator: T | None = None) → T

This method is like reduce_() except that it iterates over elements of a collection from right to left.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.
accumulator – Initial value of aggregator. Default is to use the result of the first iteration.

Returns:

Accumulator object containing results of reduction.

Example

>>> reduce_right([1, 2, 3, 4], lambda total, x: total ** x)
4096

New in version 1.0.0.

Changed in version 3.2.1: Fix bug where collection was not reversed correctly.

Changed in version 4.0.0: Removed alias foldr.

pydash.collections.reductions(collection: Mapping[T, T2], iteratee: Callable[[T3, T2, T], T3], accumulator: T3, from_right: bool = False) → List[T3][source]#

pydash.collections.reductions(collection: Mapping[Any, T2], iteratee: Callable[[T3, T2], T3], accumulator: T3, from_right: bool = False) → List[T3]

pydash.collections.reductions(collection: Mapping, iteratee: Callable[[T3], T3], accumulator: T3, from_right: bool = False) → List[T3]

pydash.collections.reductions(collection: Mapping[T, T2], iteratee: Callable[[T2, T2, T], T2], accumulator: None = None, from_right: bool = False) → List[T2]

pydash.collections.reductions(collection: Mapping[Any, T2], iteratee: Callable[[T2, T2], T2], accumulator: None = None, from_right: bool = False) → List[T2]

pydash.collections.reductions(collection: Mapping, iteratee: Callable[[T], T], accumulator: None = None, from_right: bool = False) → List[T]

pydash.collections.reductions(collection: Iterable[T], iteratee: Callable[[T2, T, int], T2], accumulator: T2, from_right: bool = False) → List[T2]

pydash.collections.reductions(collection: Iterable[T], iteratee: Callable[[T2, T], T2], accumulator: T2, from_right: bool = False) → List[T2]

pydash.collections.reductions(collection: Iterable, iteratee: Callable[[T2], T2], accumulator: T2, from_right: bool = False) → List[T2]

pydash.collections.reductions(collection: Iterable[T], iteratee: Callable[[T, T, int], T], accumulator: None = None, from_right: bool = False) → List[T]

pydash.collections.reductions(collection: Iterable[T], iteratee: Callable[[T, T], T], accumulator: None = None, from_right: bool = False) → List[T]

pydash.collections.reductions(collection: Iterable, iteratee: Callable[[T], T], accumulator: None = None, from_right: bool = False) → List[T]

pydash.collections.reductions(collection: Iterable[T], iteratee: None = None, accumulator: T | None = None, from_right: bool = False) → List[T]

This function is like reduce_() except that it returns a list of every intermediate value in the reduction operation.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.
accumulator – Initial value of aggregator. Default is to use the result of the first iteration.

Returns:

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 reduce_().

New in version 2.0.0.

pydash.collections.reductions_right(collection: Mapping[T, T2], iteratee: Callable[[T3, T2, T], T3], accumulator: T3) → List[T3][source]#

pydash.collections.reductions_right(collection: Mapping[Any, T2], iteratee: Callable[[T3, T2], T3], accumulator: T3) → List[T3]

pydash.collections.reductions_right(collection: Mapping, iteratee: Callable[[T3], T3], accumulator: T3) → List[T3]

pydash.collections.reductions_right(collection: Mapping[T, T2], iteratee: Callable[[T2, T2, T], T2], accumulator: None = None) → List[T2]

pydash.collections.reductions_right(collection: Mapping[Any, T2], iteratee: Callable[[T2, T2], T2], accumulator: None = None) → List[T2]

pydash.collections.reductions_right(collection: Mapping, iteratee: Callable[[T], T], accumulator: None = None) → List[T]

pydash.collections.reductions_right(collection: Iterable[T], iteratee: Callable[[T2, T, int], T2], accumulator: T2) → List[T2]

pydash.collections.reductions_right(collection: Iterable[T], iteratee: Callable[[T2, T], T2], accumulator: T2) → List[T2]

pydash.collections.reductions_right(collection: Iterable, iteratee: Callable[[T2], T2], accumulator: T2) → List[T2]

pydash.collections.reductions_right(collection: Iterable[T], iteratee: Callable[[T, T, int], T], accumulator: None = None) → List[T]

pydash.collections.reductions_right(collection: Iterable[T], iteratee: Callable[[T, T], T], accumulator: None = None) → List[T]

pydash.collections.reductions_right(collection: Iterable, iteratee: Callable[[T], T], accumulator: None = None) → List[T]

pydash.collections.reductions_right(collection: Iterable[T], iteratee: None = None, accumulator: T | None = None) → List[T]

This method is like reductions() except that it iterates over elements of a collection from right to left.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.
accumulator – Initial value of aggregator. Default is to use the result of the first iteration.

Returns:

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 reduce_().

New in version 2.0.0.

The opposite of filter_() this method returns the elements of a collection that the predicate does not return truthy for.

Parameters:

collection – Collection to iterate over.
predicate – Predicate applied per iteration.

Returns:

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}]

New in version 1.0.0.

pydash.collections.sample(collection: Sequence[T]) → T[source]#

Retrieves a random element from a given collection.

Parameters:: collection – Collection to iterate over.
Returns:: Random element from the given collection.

Example

>>> items = [1, 2, 3, 4, 5]
>>> results = sample(items)
>>> assert results in items

New in version 1.0.0.

Changed in version 4.0.0: Moved multiple samples functionality to sample_size(). This function now only returns a single random sample.

pydash.collections.sample_size(collection: Sequence[T], n: int | None = None) → List[T][source]#

Retrieves list of n random elements from a collection.

Parameters:

collection – Collection to iterate over.
n – Number of random samples to return.

Returns:

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)

New in version 4.0.0.

pydash.collections.shuffle(collection: Mapping[Any, T]) → List[T][source]#

pydash.collections.shuffle(collection: Iterable[T]) → List[T]

Creates a list of shuffled values, using a version of the Fisher-Yates shuffle.

Parameters:: collection – Collection to iterate over.
Returns:: Shuffled list of values.

Example

>>> items = [1, 2, 3, 4]
>>> results = shuffle(items)
>>> assert len(results) == len(items)
>>> assert set(results) == set(items)

New in version 1.0.0.

pydash.collections.size(collection: Sized) → int[source]#

Gets the size of the collection by returning len(collection) for iterable objects.

Parameters:: collection – Collection to iterate over.
Returns:: Collection length.

Example

>>> size([1, 2, 3, 4])
4

New in version 1.0.0.

pydash.collections.some(collection: Iterable[T], predicate: Callable[[T], Any] | None = None) → bool[source]#

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 map_() style predicate will return the property value of the given element. If an object is passed for predicate, the created matches() style predicate will return True for elements that have the properties of the given object, else False.

Parameters:

collection – Collection to iterate over.
predicate – Predicate applied per iteration.

Returns:

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

New in version 1.0.0.

Changed in version 4.0.0: Removed alias any_.

Creates a list of elements, sorted in ascending order by the results of running each element in a collection through the iteratee.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.
reverse – Whether to reverse the sort. Defaults to False.

Returns:

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}]

New in version 1.0.0.

Functions#

Functions that wrap other functions.

New in version 1.0.0.

pydash.functions.after(func: Callable[[P], T], n: SupportsInt) → After[P, T][source]#

Creates a function that executes func, with the arguments of the created function, only after being called n times.

Parameters:

func – Function to execute.
n – Number of times func must be called before it is executed.

Returns:

Function wrapped in an After context.

Example

>>> func = lambda a, b, c: (a, b, c)
>>> after_func = after(func, 3)
>>> after_func(1, 2, 3)
>>> after_func(1, 2, 3)
>>> after_func(1, 2, 3)
(1, 2, 3)
>>> after_func(4, 5, 6)
(4, 5, 6)

New in version 1.0.0.

Changed in version 3.0.0: Reordered arguments to make func first.

pydash.functions.ary(func: Callable[[...], T], n: SupportsInt | None) → Ary[T][source]#

Creates a function that accepts up to n arguments ignoring any additional arguments. Only positional arguments are capped. All keyword arguments are allowed through.

Parameters:

func – Function to cap arguments for.
n – Number of arguments to accept.

Returns:

Function wrapped in an Ary context.

Example

>>> func = lambda a, b, c=0, d=5: (a, b, c, d)
>>> ary_func = ary(func, 2)
>>> ary_func(1, 2, 3, 4, 5, 6)
(1, 2, 0, 5)
>>> ary_func(1, 2, 3, 4, 5, 6, c=10, d=20)
(1, 2, 10, 20)

New in version 3.0.0.

pydash.functions.before(func: Callable[[P], T], n: SupportsInt) → Before[P, T][source]#

Creates a function that executes func, with the arguments of the created function, until it has been called n times.

Parameters:

func – Function to execute.
n – Number of times func may be executed.

Returns:

Function wrapped in an Before context.

Example

>>> func = lambda a, b, c: (a, b, c)
>>> before_func = before(func, 3)
>>> before_func(1, 2, 3)
(1, 2, 3)
>>> before_func(1, 2, 3)
(1, 2, 3)
>>> before_func(1, 2, 3)
>>> before_func(1, 2, 3)

New in version 1.1.0.

Changed in version 3.0.0: Reordered arguments to make func first.

pydash.functions.conjoin(*funcs: Callable[[T], Any]) → Callable[[Iterable[T]], bool][source]#

Creates a function that composes multiple predicate functions into a single predicate that tests whether all elements of an object pass each predicate.

Parameters:: *funcs – Function(s) to conjoin.
Returns:: Function(s) wrapped in a Conjoin context.

Example

>>> conjoiner = conjoin(lambda x: isinstance(x, int), lambda x: x > 3)
>>> conjoiner([1, 2, 3])
False
>>> conjoiner([1.0, 2, 1])
False
>>> conjoiner([4.0, 5, 6])
False
>>> conjoiner([4, 5, 6])
True

New in version 2.0.0.

pydash.functions.curry(func: Callable[[T1], T], arity: int | None = None) → CurryOne[T1, T][source]#

pydash.functions.curry(func: Callable[[T1, T2], T], arity: int | None = None) → CurryTwo[T1, T2, T]

pydash.functions.curry(func: Callable[[T1, T2, T3], T], arity: int | None = None) → CurryThree[T1, T2, T3, T]

pydash.functions.curry(func: Callable[[T1, T2, T3, T4], T], arity: int | None = None) → CurryFour[T1, T2, T3, T4, T]

pydash.functions.curry(func: Callable[[T1, T2, T3, T4, T5], T], arity: int | None = None) → CurryFive[T1, T2, T3, T4, T5, T]

Creates a function that accepts one or more arguments of func that when invoked either executes func returning its result (if all func arguments have been provided) or returns a function that accepts one or more of the remaining func arguments, and so on.

Parameters:

func – Function to curry.
arity – Number of function arguments that can be accepted by curried function. Default is to use the number of arguments that are accepted by func.

Returns:

Function wrapped in a Curry context.

Example

>>> func = lambda a, b, c: (a, b, c)
>>> currier = curry(func)
>>> currier = currier(1)
>>> assert isinstance(currier, Curry)
>>> currier = currier(2)
>>> assert isinstance(currier, Curry)
>>> currier = currier(3)
>>> currier
(1, 2, 3)

New in version 1.0.0.

pydash.functions.curry_right(func: Callable[[T1], T], arity: int | None = None) → CurryRightOne[T1, T][source]#

pydash.functions.curry_right(func: Callable[[T1, T2], T], arity: int | None = None) → CurryRightTwo[T2, T1, T]

pydash.functions.curry_right(func: Callable[[T1, T2, T3], T], arity: int | None = None) → CurryRightThree[T3, T2, T1, T]

pydash.functions.curry_right(func: Callable[[T1, T2, T3, T4], T], arity: int | None = None) → CurryRightFour[T4, T3, T2, T1, T]

pydash.functions.curry_right(func: Callable[[T1, T2, T3, T4, T5], T]) → CurryRightFive[T5, T4, T3, T2, T1, T]

This method is like curry() except that arguments are applied to func in the manner of partial_right() instead of partial().

Parameters:

func – Function to curry.
arity – Number of function arguments that can be accepted by curried function. Default is to use the number of arguments that are accepted by func.

Returns:

Function wrapped in a CurryRight context.

Example

>>> func = lambda a, b, c: (a, b, c)
>>> currier = curry_right(func)
>>> currier = currier(1)
>>> assert isinstance(currier, CurryRight)
>>> currier = currier(2)
>>> assert isinstance(currier, CurryRight)
>>> currier = currier(3)
>>> currier
(3, 2, 1)

New in version 1.1.0.

pydash.functions.debounce(func: Callable[[P], T], wait: int, max_wait: int | Literal[False] = False) → Debounce[P, T][source]#

Creates a function that will delay the execution of func until after wait milliseconds have elapsed since the last time it was invoked. Subsequent calls to the debounced function will return the result of the last func call.

Parameters:

func – Function to execute.
wait – Milliseconds to wait before executing func.
max_wait (optional) – Maximum time to wait before executing func.

Returns:

Function wrapped in a Debounce context.

New in version 1.0.0.

pydash.functions.delay(func: ~typing.Callable[[~P], ~pydash.functions.T], wait: int, *args: ~typing.~P, **kwargs: ~typing.~P) → T[source]#

Executes the func function after wait milliseconds. Additional arguments will be provided to func when it is invoked.

Parameters:

func – Function to execute.
wait – Milliseconds to wait before executing func.
*args – Arguments to pass to func.
**kwargs – Keyword arguments to pass to func.

Returns:

Return from func.

New in version 1.0.0.

pydash.functions.disjoin(*funcs: Callable[[T], Any]) → Disjoin[T][source]#

Creates a function that composes multiple predicate functions into a single predicate that tests whether any elements of an object pass each predicate.

Parameters:: *funcs – Function(s) to disjoin.
Returns:: Function(s) wrapped in a Disjoin context.

Example

>>> disjoiner = disjoin(lambda x: isinstance(x, float),                                lambda x: isinstance(x, int))
>>> disjoiner([1, '2', '3'])
True
>>> disjoiner([1.0, '2', '3'])
True
>>> disjoiner(['1', '2', '3'])
False

New in version 2.0.0.

pydash.functions.flip(func: Callable[[T1, T2, T3, T4, T5], T]) → Callable[[T5, T4, T3, T2, T1], T][source]#

pydash.functions.flip(func: Callable[[T1, T2, T3, T4], T]) → Callable[[T4, T3, T2, T1], T]

pydash.functions.flip(func: Callable[[T1, T2, T3], T]) → Callable[[T3, T2, T1], T]

pydash.functions.flip(func: Callable[[T1, T2], T]) → Callable[[T2, T1], T]

pydash.functions.flip(func: Callable[[T1], T]) → Callable[[T1], T]

Creates a function that invokes the method with arguments reversed.

Parameters:: func – Function to flip arguments for.
Returns:: Function wrapped in a Flip context.

Example

>>> flipped = flip(lambda *args: args)
>>> flipped(1, 2, 3, 4)
(4, 3, 2, 1)
>>> flipped = flip(lambda *args: [i * 2 for i in args])
>>> flipped(1, 2, 3, 4)
[8, 6, 4, 2]

New in version 4.0.0.

pydash.functions.flow(func1: Callable[[P], T2], func2: Callable[[T2], T3], func3: Callable[[T3], T4], func4: Callable[[T4], T5], func5: Callable[[T5], T]) → Flow[P, T][source]#

pydash.functions.flow(func1: Callable[[P], T2], func2: Callable[[T2], T3], func3: Callable[[T3], T4], func4: Callable[[T4], T]) → Flow[P, T]

pydash.functions.flow(func1: Callable[[P], T2], func2: Callable[[T2], T3], func3: Callable[[T3], T]) → Flow[P, T]

pydash.functions.flow(func1: Callable[[P], T2], func2: Callable[[T2], T]) → Flow[P, T]

pydash.functions.flow(func1: Callable[[P], T]) → Flow[P, T]

Creates a function that is the composition of the provided functions, where each successive invocation is supplied the return value of the previous. For example, composing the functions f(), g(), and h() produces h(g(f())).

Parameters:: *funcs – Function(s) to compose.
Returns:: Function(s) wrapped in a Flow context.

Example

>>> mult_5 = lambda x: x * 5
>>> div_10 = lambda x: x / 10.0
>>> pow_2 = lambda x: x ** 2
>>> ops = flow(sum, mult_5, div_10, pow_2)
>>> ops([1, 2, 3, 4])
25.0

New in version 2.0.0.

Changed in version 2.3.1: Added pipe() as alias.

Changed in version 4.0.0: Removed alias pipe.

pydash.functions.flow_right(func5: Callable[[T4], T], func4: Callable[[T3], T4], func3: Callable[[T2], T3], func2: Callable[[T1], T2], func1: Callable[[P], T1]) → Flow[P, T][source]#

pydash.functions.flow_right(func4: Callable[[T3], T], func3: Callable[[T2], T3], func2: Callable[[T1], T2], func1: Callable[[P], T1]) → Flow[P, T]

pydash.functions.flow_right(func3: Callable[[T2], T], func2: Callable[[T1], T2], func1: Callable[[P], T1]) → Flow[P, T]

pydash.functions.flow_right(func2: Callable[[T1], T], func1: Callable[[P], T1]) → Flow[P, T]

pydash.functions.flow_right(func1: Callable[[P], T]) → Flow[P, T]

This function is like flow() except that it creates a function that invokes the provided functions from right to left. For example, composing the functions f(), g(), and h() produces f(g(h())).

Parameters:: *funcs – Function(s) to compose.
Returns:: Function(s) wrapped in a Flow context.

Example

>>> mult_5 = lambda x: x * 5
>>> div_10 = lambda x: x / 10.0
>>> pow_2 = lambda x: x ** 2
>>> ops = flow_right(mult_5, div_10, pow_2, sum)
>>> ops([1, 2, 3, 4])
50.0

New in version 1.0.0.

Changed in version 2.0.0: Added flow_right() and made compose() an alias.

Changed in version 2.3.1: Added pipe_right() as alias.

Changed in version 4.0.0: Removed aliases pipe_right and compose.

pydash.functions.iterated(func: Callable[[T], T]) → Iterated[T][source]#

Creates a function that is composed with itself. Each call to the iterated function uses the previous function call’s result as input. Returned Iterated instance can be called with (initial, n) where initial is the initial value to seed func with and n is the number of times to call func.

Parameters:: func – Function to iterate.
Returns:: Function wrapped in a Iterated context.

Example

>>> doubler = iterated(lambda x: x * 2)
>>> doubler(4, 5)
128
>>> doubler(3, 9)
1536

New in version 2.0.0.

pydash.functions.juxtapose(*funcs: Callable[[P], T]) → Juxtapose[P, T][source]#

Creates a function whose return value is a list of the results of calling each funcs with the supplied arguments.

Parameters:: *funcs – Function(s) to juxtapose.
Returns:: Function wrapped in a Juxtapose context.

Example

>>> double = lambda x: x * 2
>>> triple = lambda x: x * 3
>>> quadruple = lambda x: x * 4
>>> juxtapose(double, triple, quadruple)(5)
[10, 15, 20]

New in version 2.0.0.

pydash.functions.negate(func: Callable[[P], Any]) → Negate[P][source]#

Creates a function that negates the result of the predicate func. The func function is executed with the arguments of the created function.

Parameters:: func – Function to negate execute.
Returns:: Function wrapped in a Negate context.

Example

>>> not_is_number = negate(lambda x: isinstance(x, (int, float)))
>>> not_is_number(1)
False
>>> not_is_number('1')
True

New in version 1.1.0.

pydash.functions.once(func: Callable[[P], T]) → Once[P, T][source]#

Creates a function that is restricted to execute func once. Repeat calls to the function will return the value of the first call.

Parameters:: func – Function to execute.
Returns:: Function wrapped in a Once context.

Example

>>> oncer = once(lambda *args: args[0])
>>> oncer(5)
5
>>> oncer(6)
5

New in version 1.0.0.

pydash.functions.over_args(func: Callable[[T1, T2, T3, T4, T5], T], transform_one: Callable[[T1], T1], transform_two: Callable[[T2], T2], transform_three: Callable[[T3], T3], transform_four: Callable[[T4], T4], transform_five: Callable[[T5], T5]) → Callable[[T1, T2, T3, T4, T5], T][source]#

pydash.functions.over_args(func: Callable[[T1, T2, T3, T4], T], transform_one: Callable[[T1], T1], transform_two: Callable[[T2], T2], transform_three: Callable[[T3], T3], transform_four: Callable[[T4], T4]) → Callable[[T1, T2, T3, T4], T]

pydash.functions.over_args(func: Callable[[T1, T2, T3], T], transform_one: Callable[[T1], T1], transform_two: Callable[[T2], T2], transform_three: Callable[[T3], T3]) → Callable[[T1, T2, T3], T]

pydash.functions.over_args(func: Callable[[T1, T2], T], transform_one: Callable[[T1], T1], transform_two: Callable[[T2], T2]) → Callable[[T1, T2], T]

pydash.functions.over_args(func: Callable[[T1], T], transform_one: Callable[[T1], T1]) → Callable[[T1], T]

Creates a function that runs each argument through a corresponding transform function.

Parameters:

func – Function to wrap.
*transforms – Functions to transform arguments, specified as individual functions or lists of functions.

Returns:

Function wrapped in a OverArgs context.

Example

>>> squared = lambda x: x ** 2
>>> double = lambda x: x * 2
>>> modder = over_args(lambda x, y: [x, y], squared, double)
>>> modder(5, 10)
[25, 20]

New in version 3.3.0.

Changed in version 4.0.0: Renamed from mod_args to over_args.

pydash.functions.partial(func: Callable[[...], T], *args: Any, **kwargs: Any) → Partial[T][source]#

Creates a function that, when called, invokes func with any additional partial arguments prepended to those provided to the new function.

Parameters:

func – Function to execute.
*args – Partial arguments to prepend to function call.
**kwargs – Partial keyword arguments to bind to function call.

Returns:

Function wrapped in a Partial context.

Example

>>> dropper = partial(lambda array, n: array[n:], [1, 2, 3, 4])
>>> dropper(2)
[3, 4]
>>> dropper(1)
[2, 3, 4]
>>> myrest = partial(lambda array, n: array[n:], n=1)
>>> myrest([1, 2, 3, 4])
[2, 3, 4]

New in version 1.0.0.

pydash.functions.partial_right(func: Callable[[...], T], *args: Any, **kwargs: Any) → Partial[T][source]#

This method is like partial() except that partial arguments are appended to those provided to the new function.

Parameters:

func – Function to execute.
*args – Partial arguments to append to function call.
**kwargs – Partial keyword arguments to bind to function call.

Returns:

Function wrapped in a Partial context.

Example

>>> myrest = partial_right(lambda array, n: array[n:], 1)
>>> myrest([1, 2, 3, 4])
[2, 3, 4]

New in version 1.0.0.

pydash.functions.rearg(func: Callable[[P], T], *indexes: int) → Rearg[P, T][source]#

Creates a function that invokes func with arguments arranged according to the specified indexes where the argument value at the first index is provided as the first argument, the argument value at the second index is provided as the second argument, and so on.

Parameters:

func – Function to rearrange arguments for.
*indexes – The arranged argument indexes.

Returns:

Function wrapped in a Rearg context.

Example

>>> jumble = rearg(lambda *args: args, 1, 2, 3)
>>> jumble(1, 2, 3)
(2, 3, 1)
>>> jumble('a', 'b', 'c', 'd', 'e')
('b', 'c', 'd', 'a', 'e')

New in version 3.0.0.

pydash.functions.spread(func: Callable[[...], T]) → Spread[T][source]#

Creates a function that invokes func with the array of arguments provided to the created function.

Parameters:: func – Function to spread.
Returns:: Function wrapped in a Spread context.

Example

>>> greet = spread(lambda *people: 'Hello ' + ', '.join(people) + '!')
>>> greet(['Mike', 'Don', 'Leo'])
'Hello Mike, Don, Leo!'

New in version 3.1.0.

pydash.functions.throttle(func: Callable[[P], T], wait: int) → Throttle[P, T][source]#

Creates a function that, when executed, will only call the func function at most once per every wait milliseconds. Subsequent calls to the throttled function will return the result of the last func call.

Parameters:

func – Function to throttle.
wait – Milliseconds to wait before calling func again.

Returns:

Results of last func call.

New in version 1.0.0.

pydash.functions.unary(func: Callable[[...], T]) → Ary[T][source]#

Creates a function that accepts up to one argument, ignoring any additional arguments.

Parameters:: func – Function to cap arguments for.
Returns:: Function wrapped in an Ary context.

Example

>>> func = lambda a, b=1, c=0, d=5: (a, b, c, d)
>>> unary_func = unary(func)
>>> unary_func(1, 2, 3, 4, 5, 6)
(1, 1, 0, 5)
>>> unary_func(1, 2, 3, 4, 5, 6, b=0, c=10, d=20)
(1, 0, 10, 20)

New in version 4.0.0.

pydash.functions.wrap(value: T1, func: Callable[[Concatenate[T1, P]], T]) → Partial[T][source]#

Creates a function that provides value to the wrapper function as its first argument. Additional arguments provided to the function are appended to those provided to the wrapper function.

Parameters:

value – Value provided as first argument to function call.
func – Function to execute.

Returns:

Function wrapped in a Partial context.

Example

>>> wrapper = wrap('hello', lambda *args: args)
>>> wrapper(1, 2)
('hello', 1, 2)

New in version 1.0.0.

Numerical#

Numerical/mathematical related functions.

New in version 2.1.0.

pydash.numerical.add(a: SupportsAdd[T, T2], b: T) → T2[source]#

pydash.numerical.add(a: T, b: SupportsAdd[T, T2]) → T2

Adds two numbers.

Parameters:

a – First number to add.
b – Second number to add.

Returns:

number

Example

>>> add(10, 5)
15

New in version 2.1.0.

Changed in version 3.3.0: Support adding two numbers when passed as positional arguments.

Changed in version 4.0.0: Only support two argument addition.

pydash.numerical.ceil(x: float | int | Decimal, precision: int = 0) → float[source]#

Round number up to precision.

Parameters:

x – Number to round up.
precision – Rounding precision. Defaults to 0.

Returns:

Number rounded up.

Example

>>> ceil(3.275) == 4.0
True
>>> ceil(3.215, 1) == 3.3
True
>>> ceil(6.004, 2) == 6.01
True

New in version 3.3.0.

pydash.numerical.clamp(x: NumT, lower: NumT2, upper: NumT3 | None = None) → NumT | NumT2 | NumT3[source]#

Clamps number within the inclusive lower and upper bounds.

Parameters:

x – Number to clamp.
lower – Lower bound.
upper – Upper bound

Returns:

number

Example

>>> clamp(-10, -5, 5)
-5
>>> clamp(10, -5, 5)
5
>>> clamp(10, 5)
5
>>> clamp(-10, 5)
-10

New in version 4.0.0.

Divide two numbers.

Parameters:

dividend – The first number in a division.
divisor – The second number in a division.

Returns:

Returns the quotient.

Example

>>> divide(20, 5)
4.0
>>> divide(1.5, 3)
0.5
>>> divide(None, None)
1.0
>>> divide(5, None)
5.0

New in version 4.0.0.

pydash.numerical.floor(x: float | int | Decimal, precision: int = 0) → float[source]#

Round number down to precision.

Parameters:

x – Number to round down.
precision – Rounding precision. Defaults to 0.

Returns:

Number rounded down.

Example

>>> floor(3.75) == 3.0
True
>>> floor(3.215, 1) == 3.2
True
>>> floor(0.046, 2) == 0.04
True

New in version 3.3.0.

pydash.numerical.max_(collection: t.Mapping[t.Any, 'SupportsRichComparisonT'], default: Unset = UNSET) → SupportsRichComparisonT[source]#

pydash.numerical.max_(collection: t.Mapping[t.Any, 'SupportsRichComparisonT'], default: T) → t.Union['SupportsRichComparisonT', T]

pydash.numerical.max_(collection: t.Iterable['SupportsRichComparisonT'], default: Unset = UNSET) → SupportsRichComparisonT

pydash.numerical.max_(collection: t.Iterable['SupportsRichComparisonT'], default: T) → t.Union['SupportsRichComparisonT', T]

Retrieves the maximum value of a collection.

Parameters:

collection – Collection to iterate over.
default – Value to return if collection is empty.

Returns:

Maximum value.

Example

>>> max_([1, 2, 3, 4])
4
>>> max_([], default=-1)
-1

New in version 1.0.0.

Changed in version 4.0.0: Moved iteratee iteratee support to max_by().

pydash.numerical.max_by(collection: t.Mapping[t.Any, 'SupportsRichComparisonT'], iteratee: None = None, default: Unset = UNSET) → SupportsRichComparisonT[source]#

pydash.numerical.max_by(collection: Mapping[Any, T2], iteratee: t.Callable[[T2], 'SupportsRichComparisonT'], default: Unset = UNSET) → T2

pydash.numerical.max_by(collection: Mapping[Any, T2], iteratee: t.Callable[[T2], 'SupportsRichComparisonT'], *, default: T) → T2 | T

pydash.numerical.max_by(collection: t.Mapping[t.Any, 'SupportsRichComparisonT'], iteratee: None = None, *, default: T) → t.Union['SupportsRichComparisonT', T]

pydash.numerical.max_by(collection: t.Iterable['SupportsRichComparisonT'], iteratee: None = None, default: Unset = UNSET) → SupportsRichComparisonT

pydash.numerical.max_by(collection: Iterable[T2], iteratee: t.Callable[[T2], 'SupportsRichComparisonT'], default: Unset = UNSET) → T2

pydash.numerical.max_by(collection: Iterable[T2], iteratee: t.Callable[[T2], 'SupportsRichComparisonT'], *, default: T) → T2 | T

pydash.numerical.max_by(collection: t.Iterable['SupportsRichComparisonT'], iteratee: None = None, *, default: T) → t.Union['SupportsRichComparisonT', T]

pydash.numerical.max_by(collection: Iterable[T], iteratee: int | str | List | Tuple | Dict, default: Unset = UNSET) → T

Retrieves the maximum value of a collection.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.
default – Value to return if collection is empty.

Returns:

Maximum value.

Example

>>> max_by([1.0, 1.5, 1.8], math.floor)
1.0
>>> max_by([{'a': 1}, {'a': 2}, {'a': 3}], 'a')
{'a': 3}
>>> max_by([], default=-1)
-1

New in version 4.0.0.

pydash.numerical.mean(collection: t.Mapping[t.Any, 'SupportsAdd[int, t.Any]']) → float[source]#

pydash.numerical.mean(collection: t.Iterable['SupportsAdd[int, t.Any]']) → float

Calculate arithmetic mean of each element in collection.

Parameters:: collection – Collection to process.
Returns:: Result of mean.

Example

>>> mean([1, 2, 3, 4])
2.5

New in version 2.1.0.

Changed in version 4.0.0:

Removed average and avg aliases.
Moved iteratee functionality to mean_by().

pydash.numerical.mean_by(collection: Mapping[T, T2], iteratee: t.Callable[[T2, T, t.Dict[T, T2]], 'SupportsAdd[int, t.Any]']) → float[source]#

pydash.numerical.mean_by(collection: Mapping[T, T2], iteratee: t.Callable[[T2, T], 'SupportsAdd[int, t.Any]']) → float

pydash.numerical.mean_by(collection: Mapping[Any, T2], iteratee: t.Callable[[T2], 'SupportsAdd[int, t.Any]']) → float

pydash.numerical.mean_by(collection: Iterable[T], iteratee: t.Callable[[T, int, t.List[T]], 'SupportsAdd[int, t.Any]']) → float

pydash.numerical.mean_by(collection: Iterable[T], iteratee: t.Callable[[T, int], 'SupportsAdd[int, t.Any]']) → float

pydash.numerical.mean_by(collection: Iterable[T], iteratee: t.Callable[[T], 'SupportsAdd[int, t.Any]']) → float

pydash.numerical.mean_by(collection: t.Mapping[t.Any, 'SupportsAdd[int, t.Any]'], iteratee: None = None) → float

pydash.numerical.mean_by(collection: t.Iterable['SupportsAdd[int, t.Any]'], iteratee: None = None) → float

Calculate arithmetic mean of each element in collection. If iteratee is passed, each element of collection is passed through an iteratee before the mean is computed.

Parameters:

collection – Collection to process.
iteratee – Iteratee applied per iteration.

Returns:

Result of mean.

Example

>>> mean_by([1, 2, 3, 4], lambda x: x ** 2)
7.5

New in version 4.0.0.

pydash.numerical.median(collection: Mapping[T, T2], iteratee: t.Callable[[T2, T, t.Dict[T, T2]], NumberT]) → float | int[source]#

pydash.numerical.median(collection: Mapping[T, T2], iteratee: t.Callable[[T2, T], NumberT]) → float | int

pydash.numerical.median(collection: Mapping[Any, T2], iteratee: t.Callable[[T2], NumberT]) → float | int

pydash.numerical.median(collection: Iterable[T], iteratee: t.Callable[[T, int, t.List[T]], NumberT]) → float | int

pydash.numerical.median(collection: Iterable[T], iteratee: t.Callable[[T, int], NumberT]) → float | int

pydash.numerical.median(collection: Iterable[T], iteratee: t.Callable[[T], NumberT]) → float | int

pydash.numerical.median(collection: t.Iterable[NumberT], iteratee: None = None) → float | int

Calculate median of each element in collection. If iteratee is passed, each element of collection is passed through an iteratee before the median is computed.

Parameters:

collection – Collection to process.
iteratee – Iteratee applied per iteration.

Returns:

Result of median.

Example

>>> median([1, 2, 3, 4, 5])
3
>>> median([1, 2, 3, 4])
2.5

New in version 2.1.0.

pydash.numerical.min_(collection: t.Mapping[t.Any, 'SupportsRichComparisonT'], default: Unset = UNSET) → SupportsRichComparisonT[source]#

pydash.numerical.min_(collection: t.Mapping[t.Any, 'SupportsRichComparisonT'], default: T) → t.Union['SupportsRichComparisonT', T]

pydash.numerical.min_(collection: t.Iterable['SupportsRichComparisonT'], default: Unset = UNSET) → SupportsRichComparisonT

pydash.numerical.min_(collection: t.Iterable['SupportsRichComparisonT'], default: T) → t.Union['SupportsRichComparisonT', T]

Retrieves the minimum value of a collection.

Parameters:

collection – Collection to iterate over.
default – Value to return if collection is empty.

Returns:

Minimum value.

Example

>>> min_([1, 2, 3, 4])
1
>>> min_([], default=100)
100

New in version 1.0.0.

Changed in version 4.0.0: Moved iteratee iteratee support to min_by().

pydash.numerical.min_by(collection: t.Mapping[t.Any, 'SupportsRichComparisonT'], iteratee: None = None, default: Unset = UNSET) → SupportsRichComparisonT[source]#

pydash.numerical.min_by(collection: Mapping[Any, T2], iteratee: t.Callable[[T2], 'SupportsRichComparisonT'], default: Unset = UNSET) → T2

pydash.numerical.min_by(collection: Mapping[Any, T2], iteratee: t.Callable[[T2], 'SupportsRichComparisonT'], *, default: T) → T2 | T

pydash.numerical.min_by(collection: t.Mapping[t.Any, 'SupportsRichComparisonT'], iteratee: None = None, *, default: T) → t.Union['SupportsRichComparisonT', T]

pydash.numerical.min_by(collection: t.Iterable['SupportsRichComparisonT'], iteratee: None = None, default: Unset = UNSET) → SupportsRichComparisonT

pydash.numerical.min_by(collection: Iterable[T2], iteratee: t.Callable[[T2], 'SupportsRichComparisonT'], default: Unset = UNSET) → T2

pydash.numerical.min_by(collection: Iterable[T2], iteratee: t.Callable[[T2], 'SupportsRichComparisonT'], *, default: T) → T2 | T

pydash.numerical.min_by(collection: t.Iterable['SupportsRichComparisonT'], iteratee: None = None, *, default: T) → t.Union['SupportsRichComparisonT', T]

pydash.numerical.min_by(collection: Iterable[T], iteratee: int | str | List | Tuple | Dict, default: Unset = UNSET) → T

Retrieves the minimum value of a collection.

Parameters:

collection – Collection to iterate over.
iteratee – Iteratee applied per iteration.
default – Value to return if collection is empty.

Returns:

Minimum value.

Example

>>> min_by([1.8, 1.5, 1.0], math.floor)
1.8
>>> min_by([{'a': 1}, {'a': 2}, {'a': 3}], 'a')
{'a': 1}
>>> min_by([], default=100)
100

New in version 4.0.0.

pydash.numerical.moving_mean(array: Sequence[SupportsAdd[int, t.Any]], size: SupportsInt) → List[float][source]#

Calculate moving mean of each element of array.

Parameters:

array – List to process.
size – Window size.

Returns:

Result of moving average.

Example

>>> moving_mean(range(10), 1)
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
>>> moving_mean(range(10), 5)
[2.0, 3.0, 4.0, 5.0, 6.0, 7.0]
>>> moving_mean(range(10), 10)
[4.5]

New in version 2.1.0.

Changed in version 4.0.0: Rename to moving_mean and remove moving_average and moving_avg aliases.

pydash.numerical.multiply(multiplier: SupportsMul[int, T2], multiplicand: None) → T2[source]#

pydash.numerical.multiply(multiplier: None, multiplicand: SupportsMul[int, T2]) → T2

pydash.numerical.multiply(multiplier: None, multiplicand: None) → int

pydash.numerical.multiply(multiplier: SupportsMul[T, T2], multiplicand: T) → T2

pydash.numerical.multiply(multiplier: T, multiplicand: SupportsMul[T, T2]) → T2

Multiply two numbers.

Parameters:

multiplier – The first number in a multiplication.
multiplicand – The second number in a multiplication.

Returns:

Returns the product.

Example

>>> multiply(4, 5)
20
>>> multiply(10, 4)
40
>>> multiply(None, 10)
10
>>> multiply(None, None)
1

New in version 4.0.0.

pydash.numerical.power(x: int, n: int) → int | float[source]#

pydash.numerical.power(x: float, n: int | float) → float

pydash.numerical.power(x: List[int], n: int) → List[int | float]

pydash.numerical.power(x: List[float], n: List[int | float]) → List[float]

Calculate exponentiation of x raised to the n power.

Parameters:

x – Base number.
n – Exponent.

Returns:

Result of calculation.

Example

>>> power(5, 2)
25
>>> power(12.5, 3)
1953.125

New in version 2.1.0.

Changed in version 4.0.0: Removed alias pow_.

pydash.numerical.round_(x: t.List[SupportsRound[NumberT]], precision: int = 0) → List[float][source]#

pydash.numerical.round_(x: SupportsRound[NumberT], precision: int = 0) → float

Round number to precision.

Parameters:

x – Number to round.
precision – Rounding precision. Defaults to 0.

Returns:

Rounded number.

Example

>>> round_(3.275) == 3.0
True
>>> round_(3.275, 1) == 3.3
True

New in version 2.1.0.

Changed in version 4.0.0: Remove alias curve.

pydash.numerical.scale(array: t.Iterable['Decimal'], maximum: Decimal) → t.List['Decimal'][source]#

pydash.numerical.scale(array: Iterable[float | int], maximum: float | int) → List[float]

pydash.numerical.scale(array: t.Iterable[NumberT], maximum: int = 1) → List[float]

Scale list of value to a maximum number.

Parameters:

array – Numbers to scale.
maximum – Maximum scale value.

Returns:

Scaled numbers.

Example

>>> scale([1, 2, 3, 4])
[0.25, 0.5, 0.75, 1.0]
>>> scale([1, 2, 3, 4], 1)
[0.25, 0.5, 0.75, 1.0]
>>> scale([1, 2, 3, 4], 4)
[1.0, 2.0, 3.0, 4.0]
>>> scale([1, 2, 3, 4], 2)
[0.5, 1.0, 1.5, 2.0]

New in version 2.1.0.

pydash.numerical.slope(point1: t.Union[t.Tuple['Decimal', 'Decimal'], t.List['Decimal']], point2: t.Union[t.Tuple['Decimal', 'Decimal'], t.List['Decimal']]) → Decimal[source]#

Calculate the slope between two points.

Parameters:

point1 – X and Y coordinates of first point.
point2 – X and Y cooredinates of second point.

Returns:

Calculated slope.

Example

>>> slope((1, 2), (4, 8))
2.0

New in version 2.1.0.

pydash.numerical.std_deviation(array: List[float | int | Decimal]) → float[source]#

Calculate standard deviation of list of numbers.

Parameters:: array – List to process.
Returns:: Calculated standard deviation.

Example

>>> round(std_deviation([1, 18, 20, 4]), 2) == 8.35
True

New in version 2.1.0.

Changed in version 4.0.0: Remove alias sigma.

pydash.numerical.subtract(minuend: SupportsSub[T, T2], subtrahend: T) → T2[source]#

pydash.numerical.subtract(minuend: T, subtrahend: SupportsSub[T, T2]) → T2

Subtracts two numbers.

Parameters:

minuend – Value passed in by the user.
subtrahend – Value passed in by the user.

Returns:

Result of the difference from the given values.

Example

>>> subtract(10, 5)
5
>>> subtract(-10, 4)
-14
>>> subtract(2, 0.5)
1.5

New in version 4.0.0.

pydash.numerical.sum_(collection: t.Mapping[t.Any, 'SupportsAdd[int, T]']) → T[source]#

pydash.numerical.sum_(collection: t.Iterable['SupportsAdd[int, T]']) → T

Sum each element in collection.

Parameters:: collection – Collection to process or first number to add.
Returns:: Result of summation.

Example

>>> sum_([1, 2, 3, 4])
10

New in version 2.1.0.

Changed in version 3.3.0: Support adding two numbers when passed as positional arguments.

Changed in version 4.0.0: Move iteratee support to sum_by(). Move two argument addition to add().

pydash.numerical.sum_by(collection: Mapping[T, T2], iteratee: t.Callable[[T2, T, t.Dict[T, T2]], 'SupportsAdd[int, T3]']) → T3[source]#

pydash.numerical.sum_by(collection: Mapping[T, T2], iteratee: t.Callable[[T2, T], 'SupportsAdd[int, T3]']) → T3

pydash.numerical.sum_by(collection: Mapping[Any, T2], iteratee: t.Callable[[T2], 'SupportsAdd[int, T3]']) → T3

pydash.numerical.sum_by(collection: Iterable[T], iteratee: t.Callable[[T, int, t.List[T]], 'SupportsAdd[int, T2]']) → T2

pydash.numerical.sum_by(collection: Iterable[T], iteratee: t.Callable[[T, int], 'SupportsAdd[int, T2]']) → T2

pydash.numerical.sum_by(collection: Iterable[T], iteratee: t.Callable[[T], 'SupportsAdd[int, T2]']) → T2

pydash.numerical.sum_by(collection: t.Mapping[t.Any, 'SupportsAdd[int, T]'], iteratee: None = None) → T

pydash.numerical.sum_by(collection: t.Iterable['SupportsAdd[int, T]'], iteratee: None = None) → T

Sum each element in collection. If iteratee is passed, each element of collection is passed through an iteratee before the summation is computed.

Parameters:

collection – Collection to process or first number to add.
iteratee – Iteratee applied per iteration or second number to add.

Returns:

Result of summation.

Example

>>> sum_by([1, 2, 3, 4], lambda x: x ** 2)
30

New in version 4.0.0.

pydash.numerical.transpose(array: Iterable[Iterable[T]]) → List[List[T]][source]#

Transpose the elements of array.

Parameters:: array – List to process.
Returns:: Transposed list.

Example

>>> transpose([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
[[1, 4, 7], [2, 5, 8], [3, 6, 9]]

New in version 2.1.0.

pydash.numerical.variance(array: t.Mapping[t.Any, 'SupportsAdd[int, t.Any]']) → float[source]#

pydash.numerical.variance(array: t.Iterable['SupportsAdd[int, t.Any]']) → float

Calculate the variance of the elements in array.

Parameters:: array – List to process.
Returns:: Calculated variance.

Example

>>> variance([1, 18, 20, 4])
69.6875

New in version 2.1.0.

pydash.numerical.zscore(collection: Mapping[T, T2], iteratee: t.Callable[[T2, T, t.Dict[T, T2]], NumberT]) → List[float][source]#

pydash.numerical.zscore(collection: Mapping[T, T2], iteratee: t.Callable[[T2, T], NumberT]) → List[float]

pydash.numerical.zscore(collection: Mapping[Any, T2], iteratee: t.Callable[[T2], NumberT]) → List[float]

pydash.numerical.zscore(collection: Iterable[T], iteratee: t.Callable[[T, int, t.List[T]], NumberT]) → List[float]

pydash.numerical.zscore(collection: Iterable[T], iteratee: t.Callable[[T, int], NumberT]) → List[float]

pydash.numerical.zscore(collection: Iterable[T], iteratee: t.Callable[[T], NumberT]) → List[float]

pydash.numerical.zscore(collection: t.Iterable[NumberT], iteratee: None = None) → List[float]

Calculate the standard score assuming normal distribution. If iteratee is passed, each element of collection is passed through an iteratee before the standard score is computed.

Parameters:

collection – Collection to process.
iteratee – Iteratee applied per iteration.

Returns:

Calculated standard score.

Example

>>> results = zscore([1, 2, 3])

# [-1.224744871391589, 0.0, 1.224744871391589]

New in version 2.1.0.

Objects#

Functions that operate on lists, dicts, and other objects.

New in version 1.0.0.

pydash.objects.assign(obj: Mapping[T, T2], *sources: Mapping[T3, T4]) → Dict[T | T3, T2 | T4][source]#

pydash.objects.assign(obj: Tuple[T, ...] | List[T], *sources: Mapping[int, T2]) → List[T | T2]

Assigns properties of source object(s) to the destination object.

Parameters:

obj – Destination object whose properties will be modified.
sources – Source objects to assign to obj.

Returns:

Modified obj.

Warning

obj is modified in place.

Example

>>> obj = {}
>>> obj2 = assign(obj, {'a': 1}, {'b': 2}, {'c': 3})
>>> obj == {'a': 1, 'b': 2, 'c': 3}
True
>>> obj is obj2
True

New in version 1.0.0.

Changed in version 2.3.2: Apply clone_deep() to each source before assigning to obj.

Changed in version 3.0.0: Allow iteratees to accept partial arguments.

Changed in version 3.4.4: Shallow copy each source instead of deep copying.

Changed in version 4.0.0:

Moved iteratee argument to assign_with().
Removed alias extend.

pydash.objects.assign_with(obj: Mapping[T, T2], *sources: Mapping[T3, Any], customizer: Callable[[T2 | None], T5]) → Dict[T | T3, T2 | T5][source]#

pydash.objects.assign_with(obj: Mapping[T, T2], *sources: Mapping[T3, T4], customizer: Callable[[T2 | None, T4], T5]) → Dict[T | T3, T2 | T5]

pydash.objects.assign_with(obj: Mapping[T, T2], *sources: Mapping[T3, T4], customizer: Callable[[T2 | None, T4, T3], T5]) → Dict[T | T3, T2 | T5]

pydash.objects.assign_with(obj: Mapping[T, T2], *sources: Mapping[T3, T4], customizer: Callable[[T2 | None, T4, T3, Dict[T, T2]], T5]) → Dict[T | T3, T2 | T5]

pydash.objects.assign_with(obj: Mapping[T, T2], *sources: Mapping[T3, T4], customizer: Callable[[T2 | None, T4, T3, Dict[T, T2], Dict[T3, T4]], T5]) → Dict[T | T3, T2 | T5]

pydash.objects.assign_with(obj: Mapping[T, T2], *sources: Mapping[T3, T4], customizer: None = None) → Dict[T | T3, T2 | T4]

This method is like assign() except that it accepts customizer which is invoked to produce the assigned values. If customizer returns None, assignment is handled by the method instead. The customizer is invoked with five arguments: (obj_value, src_value, key, obj, source).

Parameters:

obj – Destination object whose properties will be modified.
sources – Source objects to assign to obj.

Keyword Arguments:

customizer – Customizer applied per iteration.

Returns:

Modified obj.

Warning

obj is modified in place.

Example

>>> customizer = lambda o, s: s if o is None else o
>>> results = assign_with({'a': 1}, {'b': 2}, {'a': 3}, customizer)
>>> results == {'a': 1, 'b': 2}
True

New in version 4.0.0.

pydash.objects.callables(obj: t.Mapping['SupportsRichComparisonT', t.Any]) → t.List['SupportsRichComparisonT'][source]#

pydash.objects.callables(obj: Iterable[T]) → List[T]

Creates a sorted list of keys of an object that are callable.

Parameters:: obj – Object to inspect.
Returns:: All keys whose values are callable.

Example

>>> callables({'a': 1, 'b': lambda: 2, 'c': lambda: 3})
['b', 'c']

New in version 1.0.0.

Changed in version 2.0.0: Renamed functions to callables.

Changed in version 4.0.0: Removed alias methods.

pydash.objects.clone(value: T) → T[source]#

Creates a clone of value.

Parameters:: value – Object to clone.

Example

>>> x = {'a': 1, 'b': 2, 'c': {'d': 3}}
>>> y = clone(x)
>>> y == y
True
>>> x is y
False
>>> x['c'] is y['c']
True

Returns:: Cloned object.

New in version 1.0.0.

Changed in version 4.0.0: Moved ‘iteratee’ parameter to clone_with().

pydash.objects.clone_deep(value: T) → T[source]#

Creates a deep clone of value. If an iteratee is provided it will be executed to produce the cloned values.

Parameters:: value – Object to clone.
Returns:: Cloned object.

Example

>>> x = {'a': 1, 'b': 2, 'c': {'d': 3}}
>>> y = clone_deep(x)
>>> y == y
True
>>> x is y
False
>>> x['c'] is y['c']
False

New in version 1.0.0.

Changed in version 4.0.0: Moved ‘iteratee’ parameter to clone_deep_with().

pydash.objects.clone_deep_with(value: Mapping[T, T2], customizer: Callable[[T2, T, Mapping[T, T2]], T3]) → Dict[T, T2 | T3][source]#

pydash.objects.clone_deep_with(value: Mapping[T, T2], customizer: Callable[[T2, T], T3]) → Dict[T, T2 | T3]

pydash.objects.clone_deep_with(value: Mapping[T, T2], customizer: Callable[[T2], T3]) → Dict[T, T2 | T3]

pydash.objects.clone_deep_with(value: List[T], customizer: Callable[[T, int, List[T]], T2]) → List[T | T2]

pydash.objects.clone_deep_with(value: List[T], customizer: Callable[[T, int], T2]) → List[T | T2]

pydash.objects.clone_deep_with(value: List[T], customizer: Callable[[T], T2]) → List[T | T2]

pydash.objects.clone_deep_with(value: T, customizer: None = None) → T

pydash.objects.clone_deep_with(value: Any, customizer: Callable) → Any

This method is like clone_with() except that it recursively clones value.

Parameters:

value – Object to clone.
customizer – Function to customize cloning.

Returns:

Cloned object.

pydash.objects.clone_with(value: Mapping[T, T2], customizer: Callable[[T2, T, Mapping[T, T2]], T3]) → Dict[T, T2 | T3][source]#

pydash.objects.clone_with(value: Mapping[T, T2], customizer: Callable[[T2, T], T3]) → Dict[T, T2 | T3]

pydash.objects.clone_with(value: Mapping[T, T2], customizer: Callable[[T2], T3]) → Dict[T, T2 | T3]

pydash.objects.clone_with(value: List[T], customizer: Callable[[T, int, List[T]], T2]) → List[T | T2]

pydash.objects.clone_with(value: List[T], customizer: Callable[[T, int], T2]) → List[T | T2]

pydash.objects.clone_with(value: List[T], customizer: Callable[[T], T2]) → List[T | T2]

pydash.objects.clone_with(value: T, customizer: None = None) → T

pydash.objects.clone_with(value: Any, customizer: Callable) → Any

This method is like clone() except that it accepts customizer which is invoked to produce the cloned value. If customizer returns None, cloning is handled by the method instead. The customizer is invoked with up to three arguments: (value, index|key, object).

Parameters:

value – Object to clone.
customizer – Function to customize cloning.

Returns:

Cloned object.

Example

>>> x = {'a': 1, 'b': 2, 'c': {'d': 3}}
>>> cbk = lambda v, k: v + 2 if isinstance(v, int) and k else None
>>> y = clone_with(x, cbk)
>>> y == {'a': 3, 'b': 4, 'c': {'d': 3}}
True

pydash.objects.defaults(obj: Dict[T, T2], *sources: Dict[T3, T4]) → Dict[T | T3, T2 | T4][source]#

Assigns properties of source object(s) to the destination object for all destination properties that resolve to undefined.

Parameters:

obj – Destination object whose properties will be modified.
sources – Source objects to assign to obj.

Returns:

Modified obj.

Warning

obj is modified in place.

Example

>>> obj = {'a': 1}
>>> obj2 = defaults(obj, {'b': 2}, {'c': 3}, {'a': 4})
>>> obj is obj2
True
>>> obj == {'a': 1, 'b': 2, 'c': 3}
True

New in version 1.0.0.

pydash.objects.defaults_deep(obj: Dict[T, T2], *sources: Dict[T3, T4]) → Dict[T | T3, T2 | T4][source]#

This method is like defaults() except that it recursively assigns default properties.

Parameters:

obj – Destination object whose properties will be modified.
sources – Source objects to assign to obj.

Returns:

Modified obj.

Warning

obj is modified in place.

Example

>>> obj = {'a': {'b': 1}}
>>> obj2 = defaults_deep(obj, {'a': {'b': 2, 'c': 3}})
>>> obj is obj2
True
>>> obj == {'a': {'b': 1, 'c': 3}}
True

New in version 3.3.0.

pydash.objects.find_key(obj: Mapping[T, T2], predicate: Callable[[T2, T, Dict[T, T2]], Any]) → T | None[source]#

pydash.objects.find_key(obj: Mapping[T, T2], predicate: Callable[[T2, T], Any]) → T | None

pydash.objects.find_key(obj: Mapping[T, T2], predicate: Callable[[T2], Any]) → T | None

pydash.objects.find_key(obj: Mapping[T, Any], predicate: None = None) → T | None

pydash.objects.find_key(collection: Iterable[T], iteratee: Callable[[T, int, List[T]], Any]) → int | None

pydash.objects.find_key(collection: Iterable[T], iteratee: Callable[[T, int], Any]) → int | None

pydash.objects.find_key(collection: Iterable[T], iteratee: Callable[[T], Any]) → int | None

pydash.objects.find_key(collection: Iterable[Any], iteratee: None = None) → int | None

This method is like pydash.arrays.find_index() except that it returns the key of the first element that passes the predicate check, instead of the element itself.

Parameters:

obj – Object to search.
predicate – Predicate applied per iteration.

Returns:

Found key or None.

Example

>>> find_key({'a': 1, 'b': 2, 'c': 3}, lambda x: x == 1)
'a'
>>> find_key([1, 2, 3, 4], lambda x: x == 1)
0

New in version 1.0.0.

pydash.objects.find_last_key(obj: Mapping[T, T2], predicate: Callable[[T2, T, Dict[T, T2]], Any]) → T | None[source]#

pydash.objects.find_last_key(obj: Mapping[T, T2], predicate: Callable[[T2, T], Any]) → T | None

pydash.objects.find_last_key(obj: Mapping[T, T2], predicate: Callable[[T2], Any]) → T | None

pydash.objects.find_last_key(obj: Mapping[T, Any], predicate: None = None) → T | None

pydash.objects.find_last_key(collection: Iterable[T], iteratee: Callable[[T, int, List[T]], Any]) → int | None

pydash.objects.find_last_key(collection: Iterable[T], iteratee: Callable[[T, int], Any]) → int | None

pydash.objects.find_last_key(collection: Iterable[T], iteratee: Callable[[T], Any]) → int | None

pydash.objects.find_last_key(collection: Iterable[Any], iteratee: None = None) → int | None

This method is like find_key() except that it iterates over elements of a collection in the opposite order.

Parameters:

obj – Object to search.
predicate – Predicate applied per iteration.

Returns:

Found key or None.

Example

>>> find_last_key({'a': 1, 'b': 2, 'c': 3}, lambda x: x == 1)
'a'
>>> find_last_key([1, 2, 3, 1], lambda x: x == 1)
3

Changed in version 4.0.0: Made into its own function (instead of an alias of find_key) with proper reverse find implementation.

pydash.objects.for_in(obj: Mapping[T, T2], iteratee: Callable[[T2, T, Dict[T, T2]], Any]) → Dict[T, T2][source]#

pydash.objects.for_in(obj: Mapping[T, T2], iteratee: Callable[[T2, T], Any]) → Dict[T, T2]

pydash.objects.for_in(obj: Mapping[T, T2], iteratee: Callable[[T2], Any]) → Dict[T, T2]

pydash.objects.for_in(obj: Mapping[T, T2], iteratee: None = None) → Dict[T, T2]

pydash.objects.for_in(obj: Sequence[T], iteratee: Callable[[T, int, List[T]], Any]) → List[T]

pydash.objects.for_in(obj: Sequence[T], iteratee: Callable[[T, int], Any]) → List[T]

pydash.objects.for_in(obj: Sequence[T], iteratee: Callable[[T], Any]) → List[T]

pydash.objects.for_in(obj: Sequence[T], iteratee: None = None) → List[T]

Iterates over own and inherited enumerable properties of obj, executing iteratee for each property.

Parameters:

obj – Object to process.
iteratee – Iteratee applied per iteration.

Returns:

obj.

Example

>>> obj = {}
>>> def cb(v, k): obj[k] = v
>>> results = for_in({'a': 1, 'b': 2, 'c': 3}, cb)
>>> results == {'a': 1, 'b': 2, 'c': 3}
True
>>> obj == {'a': 1, 'b': 2, 'c': 3}
True

New in version 1.0.0.

Changed in version 4.0.0: Removed alias for_own.

pydash.objects.for_in_right(obj: Mapping[T, T2], iteratee: Callable[[T2, T, Dict[T, T2]], Any]) → Dict[T, T2][source]#

pydash.objects.for_in_right(obj: Mapping[T, T2], iteratee: Callable[[T2, T], Any]) → Dict[T, T2]

pydash.objects.for_in_right(obj: Mapping[T, T2], iteratee: Callable[[T2], Any]) → Dict[T, T2]

pydash.objects.for_in_right(obj: Mapping[T, T2], iteratee: None = None) → Dict[T, T2]

pydash.objects.for_in_right(obj: Sequence[T], iteratee: Callable[[T, int, List[T]], Any]) → List[T]

pydash.objects.for_in_right(obj: Sequence[T], iteratee: Callable[[T, int], Any]) → List[T]

pydash.objects.for_in_right(obj: Sequence[T], iteratee: Callable[[T], Any]) → List[T]

pydash.objects.for_in_right(obj: Sequence[T], iteratee: None = None) → List[T]

This function is like for_in() except it iterates over the properties in reverse order.

Parameters:

obj – Object to process.
iteratee – Iteratee applied per iteration.

Returns:

obj.

Example

>>> data = {'product': 1}
>>> def cb(v): data['product'] *= v
>>> for_in_right([1, 2, 3, 4], cb)
[1, 2, 3, 4]
>>> data['product'] == 24
True

New in version 1.0.0.

Changed in version 4.0.0: Removed alias for_own_right.

pydash.objects.get(obj: List[T], path: int, default: T2) → T | T2[source]#

pydash.objects.get(obj: List[T], path: int, default: None = None) → T | None

pydash.objects.get(obj: Any, path: Hashable | List[Hashable], default: Any = None) → Any

Get the value at any depth of a nested object based on the path described by path. If path doesn’t exist, default is returned.

Parameters:

obj – Object to process.
path – List or . delimited string of path describing path.
default – Default value to return if path doesn’t exist. Defaults to None.

Returns:

Value of obj at path.

Example

>>> get({}, 'a.b.c') is None
True
>>> get({'a': {'b': {'c': [1, 2, 3, 4]}}}, 'a.b.c[1]')
2
>>> get({'a': {'b': {'c': [1, 2, 3, 4]}}}, 'a.b.c.1')
2
>>> get({'a': {'b': [0, {'c': [1, 2]}]}}, 'a.b.1.c.1')
2
>>> get({'a': {'b': [0, {'c': [1, 2]}]}}, ['a', 'b', 1, 'c', 1])
2
>>> get({'a': {'b': [0, {'c': [1, 2]}]}}, 'a.b.1.c.2') is None
True

New in version 2.0.0.

Changed in version 2.2.0: Support escaping “.” delimiter in single string path key.

Changed in version 3.3.0:

Added get() as main definition and get_path() as alias.
Made deep_get() an alias.

Changed in version 3.4.7: Fixed bug where an iterable default was iterated over instead of being returned when an object path wasn’t found.

Changed in version 4.0.0:

Support attribute access on obj if item access fails.
Removed aliases get_path and deep_get.

Changed in version 4.7.6: Fixed bug where getattr is used on Mappings and Sequence in Python 3.5+

pydash.objects.has(obj: Any, path: Hashable | List[Hashable]) → bool[source]#

Checks if path exists as a key of obj.

Parameters:

obj – Object to test.
path – Path to test for. Can be a list of nested keys or a . delimited string of path describing the path.

Returns:

Whether obj has path.

Example

>>> has([1, 2, 3], 1)
True
>>> has({'a': 1, 'b': 2}, 'b')
True
>>> has({'a': 1, 'b': 2}, 'c')
False
>>> has({'a': {'b': [0, {'c': [1, 2]}]}}, 'a.b.1.c.1')
True
>>> has({'a': {'b': [0, {'c': [1, 2]}]}}, 'a.b.1.c.2')
False

New in version 1.0.0.

Changed in version 3.0.0: Return False on ValueError when checking path.

Changed in version 3.3.0:

Added deep_has() as alias.
Added has_path() as alias.

Changed in version 4.0.0: Removed aliases deep_has and has_path.

pydash.objects.invert(obj: Mapping[T, T2]) → Dict[T2, T][source]#

pydash.objects.invert(obj: Iterable[T]) → Dict[T, int]

Creates an object composed of the inverted keys and values of the given object.

Parameters:: obj – Dict to invert.
Returns:: Inverted dict.

Example

>>> results = invert({'a': 1, 'b': 2, 'c': 3})
>>> results == {1: 'a', 2: 'b', 3: 'c'}
True

Note

Assumes obj values are hashable as dict keys.

New in version 1.0.0.

Changed in version 2.0.0: Added multivalue argument.

Changed in version 4.0.0: Moved multivalue=True functionality to invert_by().

pydash.objects.invert_by(obj: Mapping[T, T2], iteratee: Callable[[T2], T3]) → Dict[T3, List[T]][source]#

pydash.objects.invert_by(obj: Mapping[T, T2], iteratee: None = None) → Dict[T2, List[T]]

pydash.objects.invert_by(obj: Iterable[T], iteratee: Callable[[T], T2]) → Dict[T2, List[int]]

pydash.objects.invert_by(obj: Iterable[T], iteratee: None = None) → Dict[T, List[int]]

This method is like invert() except that the inverted object is generated from the results of running each element of object through iteratee. The corresponding inverted value of each inverted key is a list of keys responsible for generating the inverted value. The iteratee is invoked with one argument: (value).

Parameters:

obj – Object to invert.
iteratee – Iteratee applied per iteration.

Returns:

Inverted dict.

Example

>>> obj = {'a': 1, 'b': 2, 'c': 1}
>>> results = invert_by(obj)  # {1: ['a', 'c'], 2: ['b']}
>>> set(results[1]) == set(['a', 'c'])
True
>>> set(results[2]) == set(['b'])
True
>>> results2 = invert_by(obj, lambda value: 'group' + str(value))
>>> results2['group1'] == results[1]
True
>>> results2['group2'] == results[2]
True

Note

Assumes obj values are hashable as dict keys.

New in version 4.0.0.

pydash.objects.invoke(obj: Any, path: Hashable | List[Hashable], *args: Any, **kwargs: Any) → Any[source]#

Invokes the method at path of object.

Parameters:

obj – The object to query.
path – The path of the method to invoke.
args – Arguments to pass to method call.
kwargs – Keyword arguments to pass to method call.

Returns:

Result of the invoked method.

Example

>>> obj = {'a': [{'b': {'c': [1, 2, 3, 4]}}]}
>>> invoke(obj, 'a[0].b.c.pop', 1)
2
>>> obj
{'a': [{'b': {'c': [1, 3, 4]}}]}

New in version 1.0.0.

pydash.objects.keys(obj: Iterable[T]) → List[T][source]#

pydash.objects.keys(obj: Any) → List

Creates a list composed of the keys of obj.

Parameters:: obj – Object to extract keys from.
Returns:: List of keys.

Example

>>> keys([1, 2, 3])
[0, 1, 2]
>>> set(keys({'a': 1, 'b': 2, 'c': 3})) == set(['a', 'b', 'c'])
True

New in version 1.0.0.

Changed in version 1.1.0: Added keys_in as alias.

Changed in version 4.0.0: Removed alias keys_in.

pydash.objects.map_keys(obj: Mapping[T, T2], iteratee: Callable[[T2, T, Dict[T, T2]], T3]) → Dict[T3, T2][source]#

pydash.objects.map_keys(obj: Mapping[T, T2], iteratee: Callable[[T2, T], T3]) → Dict[T3, T2]

pydash.objects.map_keys(obj: Mapping[Any, T2], iteratee: Callable[[T2], T3]) → Dict[T3, T2]

pydash.objects.map_keys(obj: Iterable[T], iteratee: Callable[[T, int, List[T]], T2]) → Dict[T2, T]

pydash.objects.map_keys(obj: Iterable[T], iteratee: Callable[[T, int], T2]) → Dict[T2, T]

pydash.objects.map_keys(obj: Iterable[T], iteratee: Callable[[T], T2]) → Dict[T2, T]

The opposite of map_values(), this method creates an object with the same values as object and keys generated by running each own enumerable string keyed property of object through iteratee. The iteratee is invoked with three arguments: (value, key, object).

Parameters:

obj – Object to map.
iteratee – Iteratee applied per iteration.

Returns:

Results of running obj through iteratee.

Example

>>> callback = lambda value, key: key * 2
>>> results = map_keys({'a': 1, 'b': 2, 'c': 3}, callback)
>>> results == {'aa': 1, 'bb': 2, 'cc': 3}
True

New in version 3.3.0.

pydash.objects.map_values(obj: Mapping[T, T2], iteratee: Callable[[T2, T, Dict[T, T2]], T3]) → Dict[T, T3][source]#

pydash.objects.map_values(obj: Mapping[T, T2], iteratee: Callable[[T2, T], T3]) → Dict[T, T3]

pydash.objects.map_values(obj: Mapping[T, T2], iteratee: Callable[[T2], T3]) → Dict[T, T3]

pydash.objects.map_values(obj: Iterable[T], iteratee: Callable[[T, int, List[T]], T2]) → Dict[T, T2]

pydash.objects.map_values(obj: Iterable[T], iteratee: Callable[[T, int], T2]) → Dict[T, T2]

pydash.objects.map_values(obj: Iterable[T], iteratee: Callable[[T], T2]) → Dict[T, T2]

Creates an object with the same keys as object and values generated by running each string keyed property of object through iteratee. The iteratee is invoked with three arguments: (value, key, object).

Parameters:

obj – Object to map.
iteratee – Iteratee applied per iteration.

Returns:

Results of running obj through iteratee.

Example

>>> results = map_values({'a': 1, 'b': 2, 'c': 3}, lambda x: x * 2)
>>> results == {'a': 2, 'b': 4, 'c': 6}
True
>>> results = map_values({'a': 1, 'b': {'d': 4}, 'c': 3}, {'d': 4})
>>> results == {'a': False, 'b': True, 'c': False}
True

New in version 1.0.0.

pydash.objects.map_values_deep(obj: ~typing.Iterable, iteratee: ~typing.Callable | None = None, property_path: ~typing.Any = <pydash.helpers.Unset object>) → Any[source]#

Map all non-object values in obj with return values from iteratee. The iteratee is invoked with two arguments: (obj_value, property_path) where property_path contains the list of path keys corresponding to the path of obj_value.

Parameters:

obj – Object to map.
iteratee – Iteratee applied to each value.
property_path – Path key(s) to access.

Returns:

The modified object.

Warning

obj is modified in place.

Example

>>> x = {'a': 1, 'b': {'c': 2}}
>>> y = map_values_deep(x, lambda val: val * 2)
>>> y == {'a': 2, 'b': {'c': 4}}
True
>>> z = map_values_deep(x, lambda val, props: props)
>>> z == {'a': ['a'], 'b': {'c': ['b', 'c']}}
True

Changed in version 3.0.0: Allow iteratees to accept partial arguments.

Changed in version 4.0.0: Renamed from deep_map_values to map_values_deep.

pydash.objects.merge(obj: Mapping[T, T2], *sources: Mapping[T3, T4]) → Dict[T | T3, T2 | T4][source]#

pydash.objects.merge(obj: Sequence[T], *sources: Sequence[T2]) → List[T | T2]

Recursively merges properties of the source object(s) into the destination object. Subsequent sources will overwrite property assignments of previous sources.

Parameters:

obj – Destination object to merge source(s) into.
sources – Source objects to merge from. subsequent sources overwrite previous ones.

Returns:

Merged object.

Warning

obj is modified in place.

Example

>>> obj = {'a': 2}
>>> obj2 = merge(obj, {'a': 1}, {'b': 2, 'c': 3}, {'d': 4})
>>> obj2 == {'a': 1, 'b': 2, 'c': 3, 'd': 4}
True
>>> obj is obj2
True

New in version 1.0.0.

Changed in version 2.3.2: Apply clone_deep() to each source before assigning to obj.

Changed in version 2.3.2: Allow iteratee to be passed by reference if it is the last positional argument.

Changed in version 4.0.0: Moved iteratee argument to merge_with().

Changed in version 4.9.3: Fixed regression in v4.8.0 that caused exception when obj was None.

pydash.objects.merge_with(obj: Any, *sources: Any, **kwargs: Any) → Any[source]#

This method is like merge() except that it accepts customizer which is invoked to produce the merged values of the destination and source properties. If customizer returns None, merging is handled by this method instead. The customizer is invoked with five arguments: (obj_value, src_value, key, obj, source).

Parameters:

obj – Destination object to merge source(s) into.
sources – Source objects to merge from. subsequent sources overwrite previous ones.

Keyword Arguments:

iteratee – Iteratee function to handle merging (must be passed in as keyword argument).

Returns:

Merged object.

Warning

obj is modified in place.

Example

>>> cbk = lambda obj_val, src_val: obj_val + src_val
>>> obj1 = {'a': [1], 'b': [2]}
>>> obj2 = {'a': [3], 'b': [4]}
>>> res = merge_with(obj1, obj2, cbk)
>>> obj1 == {'a': [1, 3], 'b': [2, 4]}
True

New in version 4.0.0.

Changed in version 4.9.3: Fixed regression in v4.8.0 that caused exception when obj was None.

pydash.objects.omit(obj: Mapping[T, T2], *properties: Hashable | List[Hashable]) → Dict[T, T2][source]#

pydash.objects.omit(obj: Iterable[T], *properties: Hashable | List[Hashable]) → Dict[int, T]

pydash.objects.omit(obj: Any, *properties: Hashable | List[Hashable]) → Dict

The opposite of pick(). This method creates an object composed of the property paths of obj that are not omitted.

Parameters:

obj – Object to process.
*properties – Property values to omit.

Returns:

Results of omitting properties.

Example

>>> omit({'a': 1, 'b': 2, 'c': 3}, 'b', 'c') == {'a': 1}
True
>>> omit({'a': 1, 'b': 2, 'c': 3 }, ['a', 'c']) == {'b': 2}
True
>>> omit([1, 2, 3, 4], 0, 3) == {1: 2, 2: 3}
True
>>> omit({'a': {'b': {'c': 'd'}}}, 'a.b.c') == {'a': {'b': {}}}
True

New in version 1.0.0.

Changed in version 4.0.0: Moved iteratee argument to omit_by().

Changed in version 4.2.0: Support deep paths.

pydash.objects.omit_by(obj: Mapping[T, T2], iteratee: Callable[[T2, T], Any]) → Dict[T, T2][source]#

pydash.objects.omit_by(obj: Mapping[T, T2], iteratee: Callable[[T2], Any]) → Dict[T, T2]

pydash.objects.omit_by(obj: Dict[T, T2], iteratee: None = None) → Dict[T, T2]

pydash.objects.omit_by(obj: Iterable[T], iteratee: Callable[[T, int], Any]) → Dict[int, T]

pydash.objects.omit_by(obj: Iterable[T], iteratee: Callable[[T], Any]) → Dict[int, T]

pydash.objects.omit_by(obj: List[T], iteratee: None = None) → Dict[int, T]

pydash.objects.omit_by(obj: Any, iteratee: Callable | None = None) → Dict

The opposite of pick_by(). This method creates an object composed of the string keyed properties of object that predicate doesn’t return truthy for. The predicate is invoked with two arguments: (value, key).

Parameters:

obj – Object to process.
iteratee – Iteratee used to determine which properties to omit.

Returns:

Results of omitting properties.

Example

>>> omit_by({'a': 1, 'b': '2', 'c': 3}, lambda v: isinstance(v, int))
{'b': '2'}

New in version 4.0.0.

Changed in version 4.2.0: Support deep paths for iteratee.

pydash.objects.parse_int(value: Any, radix: int | None = None) → int | None[source]#

Converts the given value into an integer of the specified radix. If radix is falsey, a radix of 10 is used unless the value is a hexadecimal, in which case a radix of 16 is used.

Parameters:

value – Value to parse.
radix – Base to convert to.

Returns:

Integer if parsable else None.

Example

>>> parse_int('5')
5
>>> parse_int('12', 8)
10
>>> parse_int('x') is None
True

New in version 1.0.0.

pydash.objects.pick(obj: Mapping[T, T2], *properties: Hashable | List[Hashable]) → Dict[T, T2][source]#

pydash.objects.pick(obj: Tuple[T, ...] | List[T], *properties: Hashable | List[Hashable]) → Dict[int, T]

pydash.objects.pick(obj: Any, *properties: Hashable | List[Hashable]) → Dict

Creates an object composed of the picked object properties.

Parameters:

obj – Object to pick from.
properties – Property values to pick.

Returns:

Dict containing picked properties.

Example

>>> pick({'a': 1, 'b': 2, 'c': 3}, 'a', 'b') == {'a': 1, 'b': 2}
True

New in version 1.0.0.

Changed in version 4.0.0: Moved iteratee argument to pick_by().

pydash.objects.pick_by(obj: Mapping[T, T2], iteratee: Callable[[T2], Any]) → Dict[T, T2][source]#

pydash.objects.pick_by(obj: Mapping[T, T2], iteratee: Callable[[T2, T], Any]) → Dict[T, T2]

pydash.objects.pick_by(obj: Dict[T, T2], iteratee: None = None) → Dict[T, T2]

pydash.objects.pick_by(obj: Tuple[T, ...] | List[T], iteratee: Callable[[T, int], Any]) → Dict[int, T]

pydash.objects.pick_by(obj: Tuple[T, ...] | List[T], iteratee: Callable[[T], Any]) → Dict[int, T]

pydash.objects.pick_by(obj: Tuple[T, ...] | List[T], iteratee: None = None) → Dict[int, T]

pydash.objects.pick_by(obj: Any, iteratee: Callable | None = None) → Dict

Creates an object composed of the object properties predicate returns truthy for. The predicate is invoked with two arguments: (value, key).

Parameters:

obj – Object to pick from.
iteratee – Iteratee used to determine which properties to pick.

Returns:

Dict containing picked properties.

Example

>>> obj = {'a': 1, 'b': '2', 'c': 3 }
>>> pick_by(obj, lambda v: isinstance(v, int)) == {'a': 1, 'c': 3}
True

New in version 4.0.0.

pydash.objects.rename_keys(obj: Dict[T, T2], key_map: Dict[Any, T3]) → Dict[T | T3, T2][source]#

Rename the keys of obj using key_map and return new object.

Parameters:

obj – Object to rename.
key_map – Renaming map whose keys correspond to existing keys in obj and whose values are the new key name.

Returns:

Renamed obj.

Example

>>> obj = rename_keys({'a': 1, 'b': 2, 'c': 3}, {'a': 'A', 'b': 'B'})
>>> obj == {'A': 1, 'B': 2, 'c': 3}
True

New in version 2.0.0.

pydash.objects.set_(obj: T, path: Hashable | List[Hashable], value: Any) → T[source]#

Sets the value of an object described by path. If any part of the object path doesn’t exist, it will be created.

Parameters:

obj – Object to modify.
path – Target path to set value to.
value – Value to set.

Returns:

Modified obj.

Warning

obj is modified in place.

Example

>>> set_({}, 'a.b.c', 1)
{'a': {'b': {'c': 1}}}
>>> set_({}, 'a.0.c', 1)
{'a': {'0': {'c': 1}}}
>>> set_([1, 2], '[2][0]', 1)
[1, 2, [1]]
>>> set_({}, 'a.b[0].c', 1)
{'a': {'b': [{'c': 1}]}}

New in version 2.2.0.

Changed in version 3.3.0: Added set_() as main definition and deep_set() as alias.

Changed in version 4.0.0:

Modify obj in place.
Support creating default path values as list or dict based on whether key or index substrings are used.
Remove alias deep_set.

pydash.objects.set_with(obj: T, path: Hashable | List[Hashable], value: Any, customizer: Callable | None = None) → T[source]#

This method is like set_() except that it accepts customizer which is invoked to produce the objects of path. If customizer returns undefined path creation is handled by the method instead. The customizer is invoked with three arguments: (nested_value, key, nested_object).

Parameters:

obj – Object to modify.
path – Target path to set value to.
value – Value to set.
customizer – The function to customize assigned values.

Returns:

Modified obj.

Warning

obj is modified in place.

Example

>>> set_with({}, '[0][1]', 'a', lambda: {})
{0: {1: 'a'}}

New in version 4.0.0.

Changed in version 4.3.1: Fixed bug where a callable value was called when being set.

pydash.objects.to_boolean(obj: Any, true_values: Tuple[str, ...] = ('true', '1'), false_values: Tuple[str, ...] = ('false', '0')) → bool | None[source]#

Convert obj to boolean. This is not like the builtin bool function. By default, commonly considered strings values are converted to their boolean equivalent, i.e., '0' and 'false' are converted to False while '1' and 'true' are converted to True. If a string value is provided that isn’t recognized as having a common boolean conversion, then the returned value is None. Non-string values of obj are converted using bool. Optionally, true_values and false_values can be overridden but each value must be a string.

Parameters:

obj – Object to convert.
true_values – Values to consider True. Each value must be a string. Comparision is case-insensitive. Defaults to ('true', '1').
false_values – Values to consider False. Each value must be a string. Comparision is case-insensitive. Defaults to ('false', '0').

Returns:

Boolean value of obj.

Example

>>> to_boolean('true')
True
>>> to_boolean('1')
True
>>> to_boolean('false')
False
>>> to_boolean('0')
False
>>> assert to_boolean('a') is None

New in version 3.0.0.

pydash.objects.to_dict(obj: Mapping[T, T2]) → Dict[T, T2][source]#

pydash.objects.to_dict(obj: Iterable[T]) → Dict[int, T]

pydash.objects.to_dict(obj: Any) → Dict

Convert obj to dict by creating a new dict using obj keys and values.

Parameters:: obj – Object to convert.
Returns:: Object converted to dict.

Example

>>> obj = {'a': 1, 'b': 2}
>>> obj2 = to_dict(obj)
>>> obj2 == obj
True
>>> obj2 is not obj
True

New in version 3.0.0.

Changed in version 4.0.0: Removed alias to_plain_object.

Changed in version 4.2.0: Use pydash.helpers.iterator to generate key/value pairs.

Changed in version 4.7.1: Try to convert to dict using dict() first, then fallback to using pydash.helpers.iterator.

pydash.objects.to_integer(obj: Any) → int[source]#

Converts obj to an integer.

Parameters:: obj – Object to convert.
Returns:: Converted integer or 0 if it can’t be converted.

Example

>>> to_integer(3.2)
3
>>> to_integer('3.2')
3
>>> to_integer('3.9')
3
>>> to_integer('invalid')
0

New in version 4.0.0.

pydash.objects.to_list(obj: Dict[Any, T], split_strings: bool = True) → List[T][source]#

pydash.objects.to_list(obj: Iterable[T], split_strings: bool = True) → List[T]

pydash.objects.to_list(obj: T, split_strings: bool = True) → List[T]

Converts an obj, an iterable or a single item to a list.

Parameters:

obj – Object to convert item or wrap.
split_strings – Whether to split strings into single chars. Defaults to True.

Returns:

Converted obj or wrapped item.

Example

>>> results = to_list({'a': 1, 'b': 2, 'c': 3})
>>> assert set(results) == set([1, 2, 3])

>>> to_list((1, 2, 3, 4))
[1, 2, 3, 4]

>>> to_list(1)
[1]

>>> to_list([1])
[1]

>>> to_list(a for a in [1, 2, 3])
[1, 2, 3]

>>> to_list('cat')
['c', 'a', 't']

>>> to_list('cat', split_strings=False)
['cat']

New in version 1.0.0.

Changed in version 4.3.0:

Wrap non-iterable items in a list.
Convert other iterables to list.
Byte objects are returned as single character strings in Python 3.

pydash.objects.to_number(obj: Any, precision: int = 0) → float | None[source]#

Convert obj to a number. All numbers are retuned as float. If precision is negative, round obj to the nearest positive integer place. If obj can’t be converted to a number, None is returned.

Parameters:

obj – Object to convert.
precision – Precision to round number to. Defaults to 0.

Returns:

Converted number or None if it can’t be converted.

Example

>>> to_number('1234.5678')
1235.0
>>> to_number('1234.5678', 4)
1234.5678
>>> to_number(1, 2)
1.0

New in version 3.0.0.

pydash.objects.to_pairs(obj: Mapping[T, T2]) → List[List[T | T2]][source]#

pydash.objects.to_pairs(obj: Iterable[T]) → List[List[int | T]]

pydash.objects.to_pairs(obj: Any) → List

Creates a two-dimensional list of an object’s key-value pairs, i.e., [[key1, value1], [key2, value2]].

Parameters:: obj – Object to process.
Returns:: Two dimensional list of object’s key-value pairs.

Example

>>> to_pairs([1, 2, 3, 4])
[[0, 1], [1, 2], [2, 3], [3, 4]]
>>> to_pairs({'a': 1})
[['a', 1]]

New in version 1.0.0.

Changed in version 4.0.0: Renamed from pairs to to_pairs.

pydash.objects.to_string(obj: Any) → str[source]#

Converts an object to string.

Parameters:: obj – Object to convert.
Returns:: String representation of obj.

Example

>>> to_string(1) == '1'
True
>>> to_string(None) == ''
True
>>> to_string([1, 2, 3]) == '[1, 2, 3]'
True
>>> to_string('a') == 'a'
True

New in version 2.0.0.

Changed in version 3.0.0: Convert None to empty string.

pydash.objects.transform(obj: Mapping[T, T2], iteratee: Callable[[T3, T2, T, Dict[T, T2]], Any], accumulator: T3) → T3[source]#

pydash.objects.transform(obj: Mapping[T, T2], iteratee: Callable[[T3, T2, T], Any], accumulator: T3) → T3

pydash.objects.transform(obj: Mapping[Any, T2], iteratee: Callable[[T3, T2], Any], accumulator: T3) → T3

pydash.objects.transform(obj: Mapping[Any, Any], iteratee: Callable[[T3], Any], accumulator: T3) → T3

pydash.objects.transform(obj: Iterable[T], iteratee: Callable[[T3, T, int, List[T]], Any], accumulator: T3) → T3

pydash.objects.transform(obj: Iterable[T], iteratee: Callable[[T3, T, int], Any], accumulator: T3) → T3

pydash.objects.transform(obj: Iterable[T], iteratee: Callable[[T3, T], Any], accumulator: T3) → T3

pydash.objects.transform(obj: Iterable[Any], iteratee: Callable[[T3], Any], accumulator: T3) → T3

pydash.objects.transform(obj: Any, iteratee: Any = None, accumulator: Any = None) → Any

An alernative to pydash.collections.reduce(), this method transforms obj to a new accumulator object which is the result of running each of its properties through an iteratee, with each iteratee execution potentially mutating the accumulator object. The iteratee is invoked with four arguments: (accumulator, value, key, object). Iteratees may exit iteration early by explicitly returning False.

Parameters:

obj – Object to process.
iteratee – Iteratee applied per iteration.
accumulator – Accumulated object. Defaults to list.

Returns:

Accumulated object.

Example

>>> transform([1, 2, 3, 4], lambda acc, v, k: acc.append((k, v)))
[(0, 1), (1, 2), (2, 3), (3, 4)]

New in version 1.0.0.

pydash.objects.unset(obj: List | Dict, path: Hashable | List[Hashable]) → bool[source]#

Removes the property at path of obj.

Note

Only list, dict, or objects with a pop() method can be unset by this function.

Parameters:

obj – The object to modify.
path – The path of the property to unset.

Returns:

Whether the property was deleted.

Warning

obj is modified in place.

Example

>>> obj = {'a': [{'b': {'c': 7}}]}
>>> unset(obj, 'a[0].b.c')
True
>>> obj
{'a': [{'b': {}}]}
>>> unset(obj, 'a[0].b.c')
False

pydash.objects.update(obj: Dict[Any, T2], path: Hashable | List[Hashable], updater: Callable[[T2], Any]) → Dict[source]#

pydash.objects.update(obj: List[T], path: Hashable | List[Hashable], updater: Callable[[T], Any]) → List

pydash.objects.update(obj: T, path: Hashable | List[Hashable], updater: Callable) → T

This method is like set_() except that accepts updater to produce the value to set. Use update_with() to customize path creation. The updater is invoked with one argument: (value).

Parameters:

obj – Object to modify.
path – A string or list of keys that describe the object path to modify.
updater – Function that returns updated value.

Returns:

Updated obj.

Warning

obj is modified in place.

Example

>>> update({}, ['a', 'b'], lambda value: value)
{'a': {'b': None}}
>>> update([], [0, 0], lambda value: 1)
[[1]]

New in version 4.0.0.

pydash.objects.update_with(obj: Dict[Any, T2], path: Hashable | List[Hashable], updater: Callable[[T2], Any], customizer: Callable | None) → Dict[source]#

pydash.objects.update_with(obj: List[T], path: Hashable | List[Hashable], updater: Callable[[T], Any], customizer: Callable | None = None) → List

pydash.objects.update_with(obj: T, path: Hashable | List[Hashable], updater: Callable, customizer: Callable | None = None) → T

This method is like update() except that it accepts customizer which is invoked to produce the objects of path. If customizer returns None, path creation is handled by the method instead. The customizer is invoked with three arguments: (nested_value, key, nested_object).

Parameters:

obj – Object to modify.
path – A string or list of keys that describe the object path to modify.
updater – Function that returns updated value.
customizer – The function to customize assigned values.

Returns:

Updated obj.

Warning

obj is modified in place.

Example

>>> update_with({}, '[0][1]', lambda: 'a', lambda: {})
{0: {1: 'a'}}

New in version 4.0.0.

pydash.objects.values(obj: Mapping[Any, T2]) → List[T2][source]#

pydash.objects.values(obj: Iterable[T]) → List[T]

pydash.objects.values(obj: Any) → List

Creates a list composed of the values of obj.

Parameters:: obj – Object to extract values from.
Returns:: List of values.

Example

>>> results = values({'a': 1, 'b': 2, 'c': 3})
>>> set(results) == set([1, 2, 3])
True
>>> values([2, 4, 6, 8])
[2, 4, 6, 8]

New in version 1.0.0.

Changed in version 1.1.0: Added values_in as alias.

Changed in version 4.0.0: Removed alias values_in.

Predicates#

Predicate functions that return boolean evaluations of objects.

New in version 2.0.0.

pydash.predicates.eq(value: Any, other: Any) → bool[source]#

Checks if value is equal to other.

Parameters:

value – Value to compare.
other – Other value to compare.

Returns:

Whether value is equal to other.

Example

>>> eq(None, None)
True
>>> eq(None, '')
False
>>> eq('a', 'a')
True
>>> eq(1, str(1))
False

New in version 4.0.0.

pydash.predicates.gt(value: SupportsDunderGT[T], other: T) → bool[source]#

Checks if value is greater than other.

Parameters:

value – Value to compare.
other – Other value to compare.

Returns:

Whether value is greater than other.

Example

>>> gt(5, 3)
True
>>> gt(3, 5)
False
>>> gt(5, 5)
False

New in version 3.3.0.

pydash.predicates.gte(value: SupportsDunderGE[T], other: T) → bool[source]#

Checks if value is greater than or equal to other.

Parameters:

value – Value to compare.
other – Other value to compare.

Returns:

Whether value is greater than or equal to other.

Example

>>> gte(5, 3)
True
>>> gte(3, 5)
False
>>> gte(5, 5)
True

New in version 3.3.0.

pydash.predicates.in_range(value: Any, start: Any = 0, end: Any = None) → bool[source]#

Checks if value is between start and up to but not including end. If end is not specified it defaults to start with start becoming 0.

Parameters:

value – Number to check.
start – Start of range inclusive. Defaults to 0.
end – End of range exclusive. Defaults to start.

Returns:

Whether value is in range.

Example

>>> in_range(2, 4)
True
>>> in_range(4, 2)
False
>>> in_range(2, 1, 3)
True
>>> in_range(3, 1, 2)
False
>>> in_range(2.5, 3.5)
True
>>> in_range(3.5, 2.5)
False

New in version 3.1.0.

pydash.predicates.is_associative(value: Any) → bool[source]#

Checks if value is an associative object meaning that it can be accessed via an index or key.

Parameters:: value – Value to check.
Returns:: Whether value is associative.

Example

>>> is_associative([])
True
>>> is_associative({})
True
>>> is_associative(1)
False
>>> is_associative(True)
False

New in version 2.0.0.

pydash.predicates.is_blank(text: Any) → TypeGuard[str][source]#

Checks if text contains only whitespace characters.

Parameters:: text – String to test.
Returns:: Whether text is blank.

Example

>>> is_blank('')
True
>>> is_blank(' \r\n ')
True
>>> is_blank(False)
False

New in version 3.0.0.

pydash.predicates.is_boolean(value: Any) → TypeGuard[bool][source]#

Checks if value is a boolean value.

Parameters:: value – Value to check.
Returns:: Whether value is a boolean.

Example

>>> is_boolean(True)
True
>>> is_boolean(False)
True
>>> is_boolean(0)
False

New in version 1.0.0.

Changed in version 3.0.0: Added is_bool as alias.

Changed in version 4.0.0: Removed alias is_bool.

pydash.predicates.is_builtin(value: Any) → bool[source]#

Checks if value is a Python builtin function or method.

Parameters:: value – Value to check.
Returns:: Whether value is a Python builtin function or method.

Example

>>> is_builtin(1)
True
>>> is_builtin(list)
True
>>> is_builtin('foo')
False

New in version 3.0.0.

Changed in version 4.0.0: Removed alias is_native.

pydash.predicates.is_date(value: Any) → bool[source]#

Check if value is a date object.

Parameters:: value – Value to check.
Returns:: Whether value is a date object.

Example

>>> import datetime
>>> is_date(datetime.date.today())
True
>>> is_date(datetime.datetime.today())
True
>>> is_date('2014-01-01')
False

Note

This will also return True for datetime objects.

New in version 1.0.0.

pydash.predicates.is_decreasing(value: SupportsRichComparison | List[SupportsRichComparison]) → bool[source]#

Check if value is monotonically decreasing.

Parameters:: value – Value to check.
Returns:: Whether value is monotonically decreasing.

Example

>>> is_decreasing([5, 4, 4, 3])
True
>>> is_decreasing([5, 5, 5])
True
>>> is_decreasing([5, 4, 5])
False

New in version 2.0.0.

pydash.predicates.is_dict(value: Any) → bool[source]#

Checks if value is a dict.

Parameters:: value – Value to check.
Returns:: Whether value is a dict.

Example

>>> is_dict({})
True
>>> is_dict([])
False

New in version 1.0.0.

Changed in version 3.0.0: Added is_dict() as main definition and made is_plain_object` an alias.

Changed in version 4.0.0: Removed alias is_plain_object.

pydash.predicates.is_empty(value: Any) → bool[source]#

Checks if value is empty.

Parameters:: value – Value to check.
Returns:: Whether value is empty.

Example

>>> is_empty(0)
True
>>> is_empty(1)
True
>>> is_empty(True)
True
>>> is_empty('foo')
False
>>> is_empty(None)
True
>>> is_empty({})
True

Note

Returns True for booleans and numbers.

New in version 1.0.0.

pydash.predicates.is_equal(value: Any, other: Any) → bool[source]#

Performs a comparison between two values to determine if they are equivalent to each other.

Parameters:

value – Object to compare.
other – Object to compare.

Returns:

Whether value and other are equal.

Example

>>> is_equal([1, 2, 3], [1, 2, 3])
True
>>> is_equal('a', 'A')
False

New in version 1.0.0.

Changed in version 4.0.0: Removed iteratee from is_equal() and added it in is_equal_with().

pydash.predicates.is_equal_with(value: T, other: T2, customizer: Callable[[T, T2], T3]) → T3[source]#

pydash.predicates.is_equal_with(value: Any, other: Any, customizer: Callable) → bool

pydash.predicates.is_equal_with(value: Any, other: Any, customizer: None) → bool

This method is like is_equal() except that it accepts customizer which is invoked to compare values. A customizer is provided which will be executed to compare values. If the customizer returns None, comparisons will be handled by the method instead. The customizer is invoked with two arguments: (value, other).

Parameters:

value – Object to compare.
other – Object to compare.
customizer – Customizer used to compare values from value and other.

Returns:

Whether value and other are equal.

Example

>>> is_equal_with([1, 2, 3], [1, 2, 3], None)
True
>>> is_equal_with('a', 'A', None)
False
>>> is_equal_with('a', 'A', lambda a, b: a.lower() == b.lower())
True

New in version 4.0.0.

pydash.predicates.is_error(value: Any) → bool[source]#

Checks if value is an Exception.

Parameters:: value – Value to check.
Returns:: Whether value is an exception.

Example

>>> is_error(Exception())
True
>>> is_error(Exception)
False
>>> is_error(None)
False

New in version 1.1.0.

pydash.predicates.is_even(value: Any) → bool[source]#

Checks if value is even.

Parameters:: value – Value to check.
Returns:: Whether value is even.

Example

>>> is_even(2)
True
>>> is_even(3)
False
>>> is_even(False)
False

New in version 2.0.0.

pydash.predicates.is_float(value: Any) → TypeGuard[float][source]#

Checks if value is a float.

Parameters:: value – Value to check.
Returns:: Whether value is a float.

Example

>>> is_float(1.0)
True
>>> is_float(1)
False

New in version 2.0.0.

pydash.predicates.is_function(value: Any) → bool[source]#

Checks if value is a function.

Parameters:: value – Value to check.
Returns:: Whether value is callable.

Example

>>> is_function(list)
True
>>> is_function(lambda: True)
True
>>> is_function(1)
False

New in version 1.0.0.

pydash.predicates.is_increasing(value: SupportsRichComparison | List[SupportsRichComparison]) → bool[source]#

Check if value is monotonically increasing.

Parameters:: value – Value to check.
Returns:: Whether value is monotonically increasing.

Example

>>> is_increasing([1, 3, 5])
True
>>> is_increasing([1, 1, 2, 3, 3])
True
>>> is_increasing([5, 5, 5])
True
>>> is_increasing([1, 2, 4, 3])
False

New in version 2.0.0.

pydash.predicates.is_indexed(value: Any) → bool[source]#

Checks if value is integer indexed, i.e., list, str or tuple.

Parameters:: value – Value to check.
Returns:: Whether value is integer indexed.

Example

>>> is_indexed('')
True
>>> is_indexed([])
True
>>> is_indexed(())
True
>>> is_indexed({})
False

New in version 2.0.0.

Changed in version 3.0.0: Return True for tuples.

pydash.predicates.is_instance_of(value: Any, types: type | Tuple[type, ...]) → bool[source]#

Checks if value is an instance of types.

Parameters:

value – Value to check.
types – Types to check against. Pass as tuple to check if value is one of multiple types.

Returns:

Whether value is an instance of types.

Example

>>> is_instance_of({}, dict)
True
>>> is_instance_of({}, list)
False

New in version 2.0.0.

pydash.predicates.is_integer(value: Any) → TypeGuard[int][source]#

Checks if value is a integer.

Parameters:: value – Value to check.
Returns:: Whether value is an integer.

Example

>>> is_integer(1)
True
>>> is_integer(1.0)
False
>>> is_integer(True)
False

New in version 2.0.0.

Changed in version 3.0.0: Added is_int as alias.

Changed in version 4.0.0: Removed alias is_int.

pydash.predicates.is_iterable(value: Any) → bool[source]#

Checks if value is an iterable.

Parameters:: value – Value to check.
Returns:: Whether value is an iterable.

Example

>>> is_iterable([])
True
>>> is_iterable({})
True
>>> is_iterable(())
True
>>> is_iterable(5)
False
>>> is_iterable(True)
False

New in version 3.3.0.

pydash.predicates.is_json(value: Any) → bool[source]#

Checks if value is a valid JSON string.

Parameters:: value – Value to check.
Returns:: Whether value is JSON.

Example

>>> is_json({})
False
>>> is_json('{}')
True
>>> is_json({"hello": 1, "world": 2})
False
>>> is_json('{"hello": 1, "world": 2}')
True

New in version 2.0.0.

pydash.predicates.is_list(value: Any) → bool[source]#

Checks if value is a list.

Parameters:: value – Value to check.
Returns:: Whether value is a list.

Example

>>> is_list([])
True
>>> is_list({})
False
>>> is_list(())
False

New in version 1.0.0.

pydash.predicates.is_match(obj: Any, source: Any) → bool[source]#

Performs a partial deep comparison between obj and source to determine if obj contains equivalent property values.

Parameters:

obj – Object to compare.
source – Object of property values to match.

Returns:

Whether obj is a match or not.

Example

>>> is_match({'a': 1, 'b': 2}, {'b': 2})
True
>>> is_match({'a': 1, 'b': 2}, {'b': 3})
False
>>> is_match({'a': [{'b': [{'c': 3, 'd': 4}]}]},                     {'a': [{'b': [{'d': 4}]}]})
True

New in version 3.0.0.

Changed in version 3.2.0: Don’t compare obj and source using type. Use isinstance exclusively.

Changed in version 4.0.0: Move iteratee argument to is_match_with().

pydash.predicates.is_match_with(obj: ~typing.Any, source: ~typing.Any, customizer: ~typing.Any = None, _key: ~typing.Any = <pydash.helpers.Unset object>, _obj: ~typing.Any = <pydash.helpers.Unset object>, _source: ~typing.Any = <pydash.helpers.Unset object>) → bool[source]#

This method is like is_match() except that it accepts customizer which is invoked to compare values. If customizer returns None, comparisons are handled by the method instead. The customizer is invoked with five arguments: (obj_value, src_value, index|key, obj, source).

Parameters:

obj – Object to compare.
source – Object of property values to match.
customizer – Customizer used to compare values from obj and source.

Returns:

Whether obj is a match or not.

Example

>>> is_greeting = lambda val: val in ('hello', 'hi')
>>> customizer = lambda ov, sv: is_greeting(ov) and is_greeting(sv)
>>> obj = {'greeting': 'hello'}
>>> src = {'greeting': 'hi'}
>>> is_match_with(obj, src, customizer)
True

New in version 4.0.0.

pydash.predicates.is_monotone(value: T | List[T], op: Callable[[T, T], Any]) → bool[source]#

Checks if value is monotonic when operator used for comparison.

Parameters:

value – Value to check.
op – Operation to used for comparison.

Returns:

Whether value is monotone.

Example

>>> is_monotone([1, 1, 2, 3], operator.le)
True
>>> is_monotone([1, 1, 2, 3], operator.lt)
False

New in version 2.0.0.

pydash.predicates.is_nan(value: Any) → bool[source]#

Checks if value is not a number.

Parameters:: value – Value to check.
Returns:: Whether value is not a number.

Example

>>> is_nan('a')
True
>>> is_nan(1)
False
>>> is_nan(1.0)
False

New in version 1.0.0.

pydash.predicates.is_negative(value: Any) → bool[source]#

Checks if value is negative.

Parameters:: value – Value to check.
Returns:: Whether value is negative.

Example

>>> is_negative(-1)
True
>>> is_negative(0)
False
>>> is_negative(1)
False

New in version 2.0.0.

pydash.predicates.is_none(value: Any) → TypeGuard[None][source]#

Checks if value is None.

Parameters:: value – Value to check.
Returns:: Whether value is None.

Example

>>> is_none(None)
True
>>> is_none(False)
False

New in version 1.0.0.

pydash.predicates.is_number(value: Any) → bool[source]#

Checks if value is a number.

Parameters:: value – Value to check.
Returns:: Whether value is a number.

Note

Returns True for int, long (PY2), float, and decimal.Decimal.

Example

>>> is_number(1)
True
>>> is_number(1.0)
True
>>> is_number('a')
False

New in version 1.0.0.

Changed in version 3.0.0: Added is_num as alias.

Changed in version 4.0.0: Removed alias is_num.

pydash.predicates.is_object(value: Any) → bool[source]#

Checks if value is a list or dict.

Parameters:: value – Value to check.
Returns:: Whether value is list or dict.

Example

>>> is_object([])
True
>>> is_object({})
True
>>> is_object(())
False
>>> is_object(1)
False

New in version 1.0.0.

pydash.predicates.is_odd(value: Any) → bool[source]#

Checks if value is odd.

Parameters:: value – Value to check.
Returns:: Whether value is odd.

Example

>>> is_odd(3)
True
>>> is_odd(2)
False
>>> is_odd('a')
False

New in version 2.0.0.

pydash.predicates.is_positive(value: Any) → bool[source]#

Checks if value is positive.

Parameters:: value – Value to check.
Returns:: Whether value is positive.

Example

>>> is_positive(1)
True
>>> is_positive(0)
False
>>> is_positive(-1)
False

New in version 2.0.0.

pydash.predicates.is_reg_exp(value: Any) → TypeGuard[Pattern][source]#

Checks if value is a RegExp object.

Parameters:: value – Value to check.
Returns:: Whether value is a RegExp object.

Example

>>> is_reg_exp(re.compile(''))
True
>>> is_reg_exp('')
False

New in version 1.1.0.

Changed in version 4.0.0: Removed alias is_re.

pydash.predicates.is_set(value: Any) → bool[source]#

Checks if the given value is a set object or not.

Parameters:: value – Value passed in by the user.
Returns:: True if the given value is a set else False.

Example

>>> is_set(set([1, 2]))
True
>>> is_set([1, 2, 3])
False

New in version 4.0.0.

pydash.predicates.is_strictly_decreasing(value: SupportsRichComparison | List[SupportsRichComparison]) → bool[source]#

Check if value is strictly decreasing.

Parameters:: value – Value to check.
Returns:: Whether value is strictly decreasing.

Example

>>> is_strictly_decreasing([4, 3, 2, 1])
True
>>> is_strictly_decreasing([4, 4, 2, 1])
False

New in version 2.0.0.

pydash.predicates.is_strictly_increasing(value: SupportsRichComparison | List[SupportsRichComparison]) → bool[source]#

Check if value is strictly increasing.

Parameters:: value – Value to check.
Returns:: Whether value is strictly increasing.

Example

>>> is_strictly_increasing([1, 2, 3, 4])
True
>>> is_strictly_increasing([1, 1, 3, 4])
False

New in version 2.0.0.

pydash.predicates.is_string(value: Any) → TypeGuard[str][source]#

Checks if value is a string.

Parameters:: value – Value to check.
Returns:: Whether value is a string.

Example

>>> is_string('')
True
>>> is_string(1)
False

New in version 1.0.0.

pydash.predicates.is_tuple(value: Any) → bool[source]#

Checks if value is a tuple.

Parameters:: value – Value to check.
Returns:: Whether value is a tuple.

Example

>>> is_tuple(())
True
>>> is_tuple({})
False
>>> is_tuple([])
False

New in version 3.0.0.

pydash.predicates.is_zero(value: Any) → TypeGuard[int][source]#

Checks if value is 0.

Parameters:: value – Value to check.
Returns:: Whether value is 0.

Example

>>> is_zero(0)
True
>>> is_zero(1)
False

New in version 2.0.0.

pydash.predicates.lt(value: SupportsDunderLT[T], other: T) → bool[source]#

Checks if value is less than other.

Parameters:

value – Value to compare.
other – Other value to compare.

Returns:

Whether value is less than other.

Example

>>> lt(5, 3)
False
>>> lt(3, 5)
True
>>> lt(5, 5)
False

New in version 3.3.0.

pydash.predicates.lte(value: SupportsDunderLE[T], other: T) → bool[source]#

Checks if value is less than or equal to other.

Parameters:

value – Value to compare.
other – Other value to compare.

Returns:

Whether value is less than or equal to other.

Example

>>> lte(5, 3)
False
>>> lte(3, 5)
True
>>> lte(5, 5)
True

New in version 3.3.0.

Strings#

String functions.

New in version 1.1.0.

pydash.strings.camel_case(text: Any) → str[source]#

Converts text to camel case.

Parameters:: text – String to convert.
Returns:: String converted to camel case.

Example

>>> camel_case('FOO BAR_bAz')
'fooBarBAz'

New in version 1.1.0.

Changed in version 5.0.0: Improved unicode word support.

pydash.strings.capitalize(text: Any, strict: bool = True) → str[source]#

Capitalizes the first character of text.

Parameters:

text – String to capitalize.
strict – Whether to cast rest of string to lower case. Defaults to True.

Returns:

Capitalized string.

Example

>>> capitalize('once upon a TIME')
'Once upon a time'
>>> capitalize('once upon a TIME', False)
'Once upon a TIME'

New in version 1.1.0.

Changed in version 3.0.0: Added strict option.

pydash.strings.chars(text: Any) → List[str][source]#

Split text into a list of single characters.

Parameters:: text – String to split up.
Returns:: List of individual characters.

Example

>>> chars('onetwo')
['o', 'n', 'e', 't', 'w', 'o']

New in version 3.0.0.

pydash.strings.chop(text: Any, step: int) → List[str][source]#

Break up text into intervals of length step.

Parameters:

text – String to chop.
step – Interval to chop text.

Returns:

List of chopped characters. If text is None an empty list is returned.

Example

>>> chop('abcdefg', 3)
['abc', 'def', 'g']

New in version 3.0.0.

pydash.strings.chop_right(text: Any, step: int) → List[str][source]#

Like chop() except text is chopped from right.

Parameters:

text – String to chop.
step – Interval to chop text.

Returns:

List of chopped characters.

Example

>>> chop_right('abcdefg', 3)
['a', 'bcd', 'efg']

New in version 3.0.0.

pydash.strings.clean(text: Any) → str[source]#

Trim and replace multiple spaces with a single space.

Parameters:: text – String to clean.
Returns:: Cleaned string.

Example

>>> clean('a  b   c    d')
'a b c d'

New in version 3.0.0.

pydash.strings.count_substr(text: Any, subtext: Any) → int[source]#

Count the occurrences of subtext in text.

Parameters:

text – Source string to count from.
subtext – String to count.

Returns:

Number of occurrences of subtext in text.

Example

>>> count_substr('aabbccddaabbccdd', 'bc')
2

New in version 3.0.0.

pydash.strings.deburr(text: Any) → str[source]#

Deburrs text by converting latin-1 supplementary letters to basic latin letters.

Parameters:: text – String to deburr.
Returns:: Deburred string.

Example

>>> deburr('déjà vu')
'...
>>> 'deja vu'
'deja vu'

New in version 2.0.0.

pydash.strings.decapitalize(text: Any) → str[source]#

Decaptitalizes the first character of text.

Parameters:: text – String to decapitalize.
Returns:: Decapitalized string.

Example

>>> decapitalize('FOO BAR')
'fOO BAR'

New in version 3.0.0.

pydash.strings.ends_with(text: Any, target: Any, position: int | None = None) → bool[source]#

Checks if text ends with a given target string.

Parameters:

text – String to check.
target – String to check for.
position – Position to search from. Defaults to end of text.

Returns:

Whether text ends with target.

Example

>>> ends_with('abc def', 'def')
True
>>> ends_with('abc def', 4)
False

New in version 1.1.0.

pydash.strings.ensure_ends_with(text: Any, suffix: Any) → str[source]#

Append a given suffix to a string, but only if the source string does not end with that suffix.

Parameters:

text – Source string to append suffix to.
suffix – String to append to the source string if the source string does not end with suffix.

Returns:

source string possibly extended by suffix.

Example

>>> ensure_ends_with('foo bar', '!')
'foo bar!'
>>> ensure_ends_with('foo bar!', '!')
'foo bar!'

New in version 2.4.0.

pydash.strings.ensure_starts_with(text: Any, prefix: Any) → str[source]#

Prepend a given prefix to a string, but only if the source string does not start with that prefix.

Parameters:

text – Source string to prepend prefix to.
prefix – String to prepend to the source string if the source string does not start with prefix.

Returns:

source string possibly prefixed by prefix

Example

>>> ensure_starts_with('foo bar', 'Oh my! ')
'Oh my! foo bar'
>>> ensure_starts_with('Oh my! foo bar', 'Oh my! ')
'Oh my! foo bar'

New in version 2.4.0.

pydash.strings.escape(text: Any) → str[source]#

Converts the characters &, <, >, ", ', and \` in text to their corresponding HTML entities.

Parameters:: text – String to escape.
Returns:: HTML escaped string.

Example

>>> escape('"1 > 2 && 3 < 4"')
'&quot;1 &gt; 2 &amp;&amp; 3 &lt; 4&quot;'

New in version 1.0.0.

Changed in version 1.1.0: Moved function to pydash.strings.

pydash.strings.escape_reg_exp(text: Any) → str[source]#

Escapes the RegExp special characters in text.

Parameters:: text – String to escape.
Returns:: RegExp escaped string.

Example

>>> escape_reg_exp('[()]')
'\\[\\(\\)\\]'

New in version 1.1.0.

Changed in version 4.0.0: Removed alias escape_re

pydash.strings.has_substr(text: Any, subtext: Any) → bool[source]#

Returns whether subtext is included in text.

Parameters:

text – String to search.
subtext – String to search for.

Returns:

Whether subtext is found in text.

Example

>>> has_substr('abcdef', 'bc')
True
>>> has_substr('abcdef', 'bb')
False

New in version 3.0.0.

pydash.strings.human_case(text: Any) → str[source]#

Converts text to human case which has only the first letter capitalized and each word separated by a space.

Parameters:: text – String to convert.
Returns:: String converted to human case.

Example

>>> human_case('abc-def_hij lmn')
'Abc def hij lmn'
>>> human_case('user_id')
'User'

New in version 3.0.0.

Changed in version 5.0.0: Improved unicode word support.

pydash.strings.insert_substr(text: Any, index: int, subtext: Any) → str[source]#

Insert subtext in text starting at position index.

Parameters:

text – String to add substring to.
index – String index to insert into.
subtext – String to insert.

Returns:

Modified string.

Example

>>> insert_substr('abcdef', 3, '--')
'abc--def'

New in version 3.0.0.

pydash.strings.join(array: Iterable[Any], separator: Any = '') → str[source]#

Joins an iterable into a string using separator between each element.

Parameters:

array – Iterable to implode.
separator – Separator to using when joining. Defaults to ''.

Returns:

Joined string.

Example

>>> join(['a', 'b', 'c']) == 'abc'
True
>>> join([1, 2, 3, 4], '&') == '1&2&3&4'
True
>>> join('abcdef', '-') == 'a-b-c-d-e-f'
True

New in version 2.0.0.

Changed in version 4.0.0: Removed alias implode.

pydash.strings.kebab_case(text: Any) → str[source]#

Converts text to kebab case (a.k.a. spinal case).

Parameters:: text – String to convert.
Returns:: String converted to kebab case.

Example

>>> kebab_case('a b c_d-e!f')
'a-b-c-d-e-f'

New in version 1.1.0.

Changed in version 5.0.0: Improved unicode word support.

pydash.strings.lines(text: Any) → List[str][source]#

Split lines in text into an array.

Parameters:: text – String to split.
Returns:: String split by lines.

Example

>>> lines('a\nb\r\nc')
['a', 'b', 'c']

New in version 3.0.0.

pydash.strings.lower_case(text: Any) → str[source]#

Converts string to lower case as space separated words.

Parameters:: text – String to convert.
Returns:: String converted to lower case as space separated words.

Example

>>> lower_case('fooBar')
'foo bar'
>>> lower_case('--foo-Bar--')
'foo bar'
>>> lower_case('/?*Foo10/;"B*Ar')
'foo 10 b ar'

New in version 4.0.0.

Changed in version 5.0.0: Improved unicode word support.

pydash.strings.lower_first(text: str) → str[source]#

Converts the first character of string to lower case.

Parameters:: text – String passed in by the user.
Returns:: String in which the first character is converted to lower case.

Example

>>> lower_first('FRED')
'fRED'
>>> lower_first('Foo Bar')
'foo Bar'
>>> lower_first('1foobar')
'1foobar'
>>> lower_first(';foobar')
';foobar'

New in version 4.0.0.

pydash.strings.number_format(number: float | int | Decimal, scale: int = 0, decimal_separator: str = '.', order_separator: str = ',') → str[source]#

Format a number to scale with custom decimal and order separators.

Parameters:

number – Number to format.
scale – Number of decimals to include. Defaults to 0.
decimal_separator – Decimal separator to use. Defaults to '.'.
order_separator – Order separator to use. Defaults to ','.

Returns:

Number formatted as string.

Example

>>> number_format(1234.5678)
'1,235'
>>> number_format(1234.5678, 2, ',', '.')
'1.234,57'

New in version 3.0.0.

pydash.strings.pad(text: Any, length: int, chars: Any = ' ') → str[source]#

Pads text on the left and right sides if it is shorter than the given padding length. The chars string may be truncated if the number of padding characters can’t be evenly divided by the padding length.

Parameters:

text – String to pad.
length – Amount to pad.
chars – Characters to pad with. Defaults to " ".

Returns:

Padded string.

Example

>>> pad('abc', 5)
' abc '
>>> pad('abc', 6, 'x')
'xabcxx'
>>> pad('abc', 5, '...')
'.abc.'

New in version 1.1.0.

Changed in version 3.0.0: Fix handling of multiple chars so that padded string isn’t over padded.

pydash.strings.pad_end(text: Any, length: int, chars: Any = ' ') → str[source]#

Pads text on the right side if it is shorter than the given padding length. The chars string may be truncated if the number of padding characters can’t be evenly divided by the padding length.

Parameters:

text – String to pad.
length – Amount to pad.
chars – Characters to pad with. Defaults to " ".

Returns:

Padded string.

Example

>>> pad_end('abc', 5)
'abc  '
>>> pad_end('abc', 5, '.')
'abc..'

New in version 1.1.0.

Changed in version 4.0.0: Renamed from pad_right to pad_end.

pydash.strings.pad_start(text: Any, length: int, chars: Any = ' ') → str[source]#

Pads text on the left side if it is shorter than the given padding length. The chars string may be truncated if the number of padding characters can’t be evenly divided by the padding length.

Parameters:

text – String to pad.
length – Amount to pad.
chars – Characters to pad with. Defaults to " ".

Returns:

Padded string.

Example

>>> pad_start('abc', 5)
'  abc'
>>> pad_start('abc', 5, '.')
'..abc'

New in version 1.1.0.

Changed in version 4.0.0: Renamed from pad_left to pad_start.

pydash.strings.pascal_case(text: Any, strict: bool = True) → str[source]#

Like camel_case() except the first letter is capitalized.

Parameters:

text – String to convert.
strict – Whether to cast rest of string to lower case. Defaults to True.

Returns:

String converted to class case.

Example

>>> pascal_case('FOO BAR_bAz')
'FooBarBaz'
>>> pascal_case('FOO BAR_bAz', False)
'FooBarBAz'

New in version 3.0.0.

Changed in version 5.0.0: Improved unicode word support.

pydash.strings.predecessor(char: Any) → str[source]#

Return the predecessor character of char.

Parameters:: char – Character to find the predecessor of.
Returns:: Predecessor character.

Example

>>> predecessor('c')
'b'
>>> predecessor('C')
'B'
>>> predecessor('3')
'2'

New in version 3.0.0.

pydash.strings.prune(text: Any, length: int = 0, omission: str = '...') → str[source]#

Like truncate() except it ensures that the pruned string doesn’t exceed the original length, i.e., it avoids half-chopped words when truncating. If the pruned text + omission text is longer than the original text, then the original text is returned.

Parameters:

text – String to prune.
length – Target prune length. Defaults to 0.
omission – Omission text to append to the end of the pruned string. Defaults to '...'.

Returns:

Pruned string.

Example

>>> prune('Fe fi fo fum', 5)
'Fe fi...'
>>> prune('Fe fi fo fum', 6)
'Fe fi...'
>>> prune('Fe fi fo fum', 7)
'Fe fi...'
>>> prune('Fe fi fo fum', 8, ',,,')
'Fe fi fo,,,'

New in version 3.0.0.

pydash.strings.quote(text: Any, quote_char: Any = '"') → str[source]#

Quote a string with another string.

Parameters:

text – String to be quoted.
quote_char – the quote character. Defaults to '"'.

Returns:

the quoted string.

Example

>>> quote('To be or not to be')
'"To be or not to be"'
>>> quote('To be or not to be', "'")
"'To be or not to be'"

New in version 2.4.0.

pydash.strings.reg_exp_js_match(text: Any, reg_exp: str) → List[str][source]#

Return list of matches using Javascript style regular expression.

Parameters:

text – String to evaluate.
reg_exp – Javascript style regular expression.

Returns:

List of matches.

Example

>>> reg_exp_js_match('aaBBcc', '/bb/')
[]
>>> reg_exp_js_match('aaBBcc', '/bb/i')
['BB']
>>> reg_exp_js_match('aaBBccbb', '/bb/i')
['BB']
>>> reg_exp_js_match('aaBBccbb', '/bb/gi')
['BB', 'bb']

New in version 2.0.0.

Changed in version 3.0.0: Reordered arguments to make text first.

Changed in version 4.0.0: Renamed from js_match to reg_exp_js_match.

pydash.strings.reg_exp_js_replace(text: Any, reg_exp: str, repl: str | Callable[[Match], str]) → str[source]#

Replace text with repl using Javascript style regular expression to find matches.

Parameters:

text – String to evaluate.
reg_exp – Javascript style regular expression.
repl – Replacement string or callable.

Returns:

Modified string.

Example

>>> reg_exp_js_replace('aaBBcc', '/bb/', 'X')
'aaBBcc'
>>> reg_exp_js_replace('aaBBcc', '/bb/i', 'X')
'aaXcc'
>>> reg_exp_js_replace('aaBBccbb', '/bb/i', 'X')
'aaXccbb'
>>> reg_exp_js_replace('aaBBccbb', '/bb/gi', 'X')
'aaXccX'

New in version 2.0.0.

Changed in version 3.0.0: Reordered arguments to make text first.

Changed in version 4.0.0: Renamed from js_replace to reg_exp_js_replace.

pydash.strings.reg_exp_replace(text: Any, pattern: Any, repl: str | Callable[[Match], str], ignore_case: bool = False, count: int = 0) → str[source]#

Replace occurrences of regex pattern with repl in text. Optionally, ignore case when replacing. Optionally, set count to limit number of replacements.

Parameters:

text – String to replace.
pattern – Pattern to find and replace.
repl – String to substitute pattern with.
ignore_case – Whether to ignore case when replacing. Defaults to False.
count – Maximum number of occurrences to replace. Defaults to 0 which replaces all.

Returns:

Replaced string.

Example

>>> reg_exp_replace('aabbcc', 'b', 'X')
'aaXXcc'
>>> reg_exp_replace('aabbcc', 'B', 'X', ignore_case=True)
'aaXXcc'
>>> reg_exp_replace('aabbcc', 'b', 'X', count=1)
'aaXbcc'
>>> reg_exp_replace('aabbcc', '[ab]', 'X')
'XXXXcc'

New in version 3.0.0.

Changed in version 4.0.0: Renamed from re_replace to reg_exp_replace.

pydash.strings.repeat(text: Any, n: SupportsInt = 0) → str[source]#

Repeats the given string n times.

Parameters:

text – String to repeat.
n – Number of times to repeat the string.

Returns:

Repeated string.

Example

>>> repeat('.', 5)
'.....'

New in version 1.1.0.

pydash.strings.replace(text: Any, pattern: Any, repl: str | Callable[[Match], str], ignore_case: bool = False, count: int = 0, escape: bool = True, from_start: bool = False, from_end: bool = False) → str[source]#

Replace occurrences of pattern with repl in text. Optionally, ignore case when replacing. Optionally, set count to limit number of replacements.

Parameters:

text – String to replace.
pattern – Pattern to find and replace.
repl – String to substitute pattern with.
ignore_case – Whether to ignore case when replacing. Defaults to False.
count – Maximum number of occurrences to replace. Defaults to 0 which replaces all.
escape – Whether to escape pattern when searching. This is needed if a literal replacement is desired when pattern may contain special regular expression characters. Defaults to True.
from_start – Whether to limit replacement to start of string.
from_end – Whether to limit replacement to end of string.

Returns:

Replaced string.

Example

>>> replace('aabbcc', 'b', 'X')
'aaXXcc'
>>> replace('aabbcc', 'B', 'X', ignore_case=True)
'aaXXcc'
>>> replace('aabbcc', 'b', 'X', count=1)
'aaXbcc'
>>> replace('aabbcc', '[ab]', 'X')
'aabbcc'
>>> replace('aabbcc', '[ab]', 'X', escape=False)
'XXXXcc'

New in version 3.0.0.

Changed in version 4.1.0: Added from_start and from_end arguments.

Changed in version 5.0.0: Added support for pattern as typing.Pattern object.

pydash.strings.replace_end(text: Any, pattern: Any, repl: str | Callable[[Match], str], ignore_case: bool = False, escape: bool = True) → str[source]#

Like replace() except it only replaces text with repl if pattern mathces the end of text.

Parameters:

text – String to replace.
pattern – Pattern to find and replace.
repl – String to substitute pattern with.
ignore_case – Whether to ignore case when replacing. Defaults to False.
escape – Whether to escape pattern when searching. This is needed if a literal replacement is desired when pattern may contain special regular expression characters. Defaults to True.

Returns:

Replaced string.

Example

>>> replace_end('aabbcc', 'b', 'X')
'aabbcc'
>>> replace_end('aabbcc', 'c', 'X')
'aabbcX'

New in version 4.1.0.

pydash.strings.replace_start(text: Any, pattern: Any, repl: str | Callable[[Match], str], ignore_case: bool = False, escape: bool = True) → str[source]#

Like replace() except it only replaces text with repl if pattern mathces the start of text.

Parameters:

text – String to replace.
pattern – Pattern to find and replace.
repl – String to substitute pattern with.
ignore_case – Whether to ignore case when replacing. Defaults to False.
escape – Whether to escape pattern when searching. This is needed if a literal replacement is desired when pattern may contain special regular expression characters. Defaults to True.

Returns:

Replaced string.

Example

>>> replace_start('aabbcc', 'b', 'X')
'aabbcc'
>>> replace_start('aabbcc', 'a', 'X')
'Xabbcc'

New in version 4.1.0.

pydash.strings.separator_case(text: Any, separator: str) → str[source]#

Splits text on words and joins with separator.

Parameters:

text – String to convert.
separator – Separator to join words with.

Returns:

Converted string.

Example

>>> separator_case('a!!b___c.d', '-')
'a-b-c-d'

New in version 3.0.0.

Changed in version 5.0.0: Improved unicode word support.

pydash.strings.series_phrase(items: List[Any], separator: Any = ', ', last_separator: Any = ' and ', serial: bool = False) → str[source]#

Join items into a grammatical series phrase, e.g., "item1, item2, item3 and item4".

Parameters:

items – List of string items to join.
separator – Item separator. Defaults to ', '.
last_separator – Last item separator. Defaults to ' and '.
serial – Whether to include separator with last_separator when number of items is greater than 2. Defaults to False.

Returns:

Joined string.

Example

>>> series_phrase(['apples', 'bananas', 'peaches'])
'apples, bananas and peaches'
>>> series_phrase(['apples', 'bananas', 'peaches'], serial=True)
'apples, bananas, and peaches'
>>> series_phrase(['apples', 'bananas', 'peaches'], '; ', ', or ')
'apples; bananas, or peaches'

New in version 3.0.0.

pydash.strings.series_phrase_serial(items: List[Any], separator: Any = ', ', last_separator: Any = ' and ') → str[source]#

Join items into a grammatical series phrase using a serial separator, e.g., "item1, item2, item3, and item4".

Parameters:

items – List of string items to join.
separator – Item separator. Defaults to ', '.
last_separator – Last item separator. Defaults to ' and '.

Returns:

Joined string.

Example

>>> series_phrase_serial(['apples', 'bananas', 'peaches'])
'apples, bananas, and peaches'

New in version 3.0.0.

pydash.strings.slugify(text: Any, separator: str = '-') → str[source]#

Convert text into an ASCII slug which can be used safely in URLs. Incoming text is converted to unicode and noramlzied using the NFKD form. This results in some accented characters being converted to their ASCII “equivalent” (e.g. é is converted to e). Leading and trailing whitespace is trimmed and any remaining whitespace or other special characters without an ASCII equivalent are replaced with -.

Parameters:

text – String to slugify.
separator – Separator to use. Defaults to '-'.

Returns:

Slugified string.

Example

>>> slugify('This is a slug.') == 'this-is-a-slug'
True
>>> slugify('This is a slug.', '+') == 'this+is+a+slug'
True

New in version 3.0.0.

Changed in version 5.0.0: Improved unicode word support.

Changed in version 7.0.0: Remove single quotes from output.

pydash.strings.snake_case(text: Any) → str[source]#

Converts text to snake case.

Parameters:: text – String to convert.
Returns:: String converted to snake case.

Example

>>> snake_case('This is Snake Case!')
'this_is_snake_case'

New in version 1.1.0.

Changed in version 4.0.0: Removed alias underscore_case.

Changed in version 5.0.0: Improved unicode word support.

pydash.strings.split(text: ~typing.Any, separator: str | ~pydash.helpers.Unset | None = <pydash.helpers.Unset object>) → List[str][source]#

Splits text on separator. If separator not provided, then text is split on whitespace. If separator is falsey, then text is split on every character.

Parameters:

text – String to explode.
separator – Separator string to split on. Defaults to NoValue.

Returns:

Split string.

Example

>>> split('one potato, two potatoes, three potatoes, four!')
['one', 'potato,', 'two', 'potatoes,', 'three', 'potatoes,', 'four!']
>>> split('one potato, two potatoes, three potatoes, four!', ',')
['one potato', ' two potatoes', ' three potatoes', ' four!']

New in version 2.0.0.

Changed in version 3.0.0: Changed separator default to NoValue and supported splitting on whitespace by default.

Changed in version 4.0.0: Removed alias explode.

pydash.strings.start_case(text: Any) → str[source]#

Convert text to start case.

Parameters:: text – String to convert.
Returns:: String converted to start case.

Example

>>> start_case("fooBar")
'Foo Bar'

New in version 3.1.0.

Changed in version 5.0.0: Improved unicode word support.

pydash.strings.starts_with(text: Any, target: Any, position: int = 0) → bool[source]#

Checks if text starts with a given target string.

Parameters:

text – String to check.
target – String to check for.
position – Position to search from. Defaults to beginning of text.

Returns:

Whether text starts with target.

Example

>>> starts_with('abcdef', 'a')
True
>>> starts_with('abcdef', 'b')
False
>>> starts_with('abcdef', 'a', 1)
False

New in version 1.1.0.

pydash.strings.strip_tags(text: Any) → str[source]#

Removes all HTML tags from text.

Parameters:: text – String to strip.
Returns:: String without HTML tags.

Example

>>> strip_tags('<a href="#">Some link</a>')
'Some link'

New in version 3.0.0.

pydash.strings.substr_left(text: Any, subtext: str) → str[source]#

Searches text from left-to-right for subtext and returns a substring consisting of the characters in text that are to the left of subtext or all string if no match found.

Parameters:

text – String to partition.
subtext – String to search for.

Returns:

Substring to left of subtext.

Example

>>> substr_left('abcdefcdg', 'cd')
'ab'

New in version 3.0.0.

pydash.strings.substr_left_end(text: Any, subtext: str) → str[source]#

Searches text from right-to-left for subtext and returns a substring consisting of the characters in text that are to the left of subtext or all string if no match found.

Parameters:

text – String to partition.
subtext – String to search for.

Returns:

Substring to left of subtext.

Example

>>> substr_left_end('abcdefcdg', 'cd')
'abcdef'

New in version 3.0.0.

pydash.strings.substr_right(text: Any, subtext: str) → str[source]#

Searches text from right-to-left for subtext and returns a substring consisting of the characters in text that are to the right of subtext or all string if no match found.

Parameters:

text – String to partition.
subtext – String to search for.

Returns:

Substring to right of subtext.

Example

>>> substr_right('abcdefcdg', 'cd')
'efcdg'

New in version 3.0.0.

pydash.strings.substr_right_end(text: Any, subtext: str) → str[source]#

Searches text from left-to-right for subtext and returns a substring consisting of the characters in text that are to the right of subtext or all string if no match found.

Parameters:

text – String to partition.
subtext – String to search for.

Returns:

Substring to right of subtext.

Example

>>> substr_right_end('abcdefcdg', 'cd')
'g'

New in version 3.0.0.

pydash.strings.successor(char: Any) → str[source]#

Return the successor character of char.

Parameters:: char – Character to find the successor of.
Returns:: Successor character.

Example

>>> successor('b')
'c'
>>> successor('B')
'C'
>>> successor('2')
'3'

New in version 3.0.0.

pydash.strings.surround(text: Any, wrapper: Any) → str[source]#

Surround a string with another string.

Parameters:

text – String to surround with wrapper.
wrapper – String by which text is to be surrounded.

Returns:

Surrounded string.

Example

>>> surround('abc', '"')
'"abc"'
>>> surround('abc', '!')
'!abc!'

New in version 2.4.0.

pydash.strings.swap_case(text: Any) → str[source]#

Swap case of text characters.

Parameters:: text – String to swap case.
Returns:: String with swapped case.

Example

>>> swap_case('aBcDeF')
'AbCdEf'

New in version 3.0.0.

pydash.strings.title_case(text: Any) → str[source]#

Convert text to title case.

Parameters:: text – String to convert.
Returns:: String converted to title case.

Example

>>> title_case("bob's shop")
"Bob's Shop"

New in version 3.0.0.

pydash.strings.to_lower(text: Any) → str[source]#

Converts the given text to lower text.

Parameters:: text – String to convert.
Returns:: String converted to lower case.

Example

>>> to_lower('--Foo-Bar--')
'--foo-bar--'
>>> to_lower('fooBar')
'foobar'
>>> to_lower('__FOO_BAR__')
'__foo_bar__'

New in version 4.0.0.

pydash.strings.to_upper(text: Any) → str[source]#

Converts the given text to upper text.

Parameters:: text – String to convert.
Returns:: String converted to upper case.

Example

>>> to_upper('--Foo-Bar--')
'--FOO-BAR--'
>>> to_upper('fooBar')
'FOOBAR'
>>> to_upper('__FOO_BAR__')
'__FOO_BAR__'

New in version 4.0.0.

pydash.strings.trim(text: Any, chars: str | None = None) → str[source]#

Removes leading and trailing whitespace or specified characters from text.

Parameters:

text – String to trim.
chars – Specific characters to remove.

Returns:

Trimmed string.

Example

>>> trim('  abc efg\r\n ')
'abc efg'

New in version 1.1.0.

pydash.strings.trim_end(text: Any, chars: str | None = None) → str[source]#

Removes trailing whitespace or specified characters from text.

Parameters:

text – String to trim.
chars – Specific characters to remove.

Returns:

Trimmed string.

Example

>>> trim_end('  abc efg\r\n ')
'  abc efg'

New in version 1.1.0.

Changed in version 4.0.0: Renamed from trim_right to trim_end.

pydash.strings.trim_start(text: Any, chars: str | None = None) → str[source]#

Removes leading whitespace or specified characters from text.

Parameters:

text – String to trim.
chars – Specific characters to remove.

Returns:

Trimmed string.

Example

>>> trim_start('  abc efg\r\n ')
'abc efg\r\n '

New in version 1.1.0.

Changed in version 4.0.0: Renamed from trim_left to trim_start.

pydash.strings.truncate(text: Any, length: int = 30, omission: str = '...', separator: str | Pattern | None = None) → str[source]#

Truncates text if it is longer than the given maximum string length. The last characters of the truncated string are replaced with the omission string which defaults to ....

Parameters:

text – String to truncate.
length – Maximum string length. Defaults to 30.
omission – String to indicate text is omitted.
separator – Separator pattern to truncate to.

Returns:

Truncated string.

Example

>>> truncate('hello world', 5)
'he...'
>>> truncate('hello world', 5, '..')
'hel..'
>>> truncate('hello world', 10)
'hello w...'
>>> truncate('hello world', 10, separator=' ')
'hello...'

New in version 1.1.0.

Changed in version 4.0.0: Removed alias trunc.

pydash.strings.unescape(text: Any) → str[source]#

The inverse of escape(). This method converts the HTML entities &, <, >, ", ', and ` in text to their corresponding characters.

Parameters:: text – String to unescape.
Returns:: HTML unescaped string.

Example

>>> results = unescape('&quot;1 &gt; 2 &amp;&amp; 3 &lt; 4&quot;')
>>> results == '"1 > 2 && 3 < 4"'
True

New in version 1.0.0.

Changed in version 1.1.0: Moved to pydash.strings.

pydash.strings.unquote(text: Any, quote_char: Any = '"') → str[source]#

Unquote text by removing quote_char if text begins and ends with it.

Parameters:

text – String to unquote.
quote_char – Quote character to remove. Defaults to “.

Returns:

Unquoted string.

Example

>>> unquote('"abc"')
'abc'
>>> unquote('"abc"', '#')
'"abc"'
>>> unquote('#abc', '#')
'#abc'
>>> unquote('#abc#', '#')
'abc'

New in version 3.0.0.

pydash.strings.upper_case(text: Any) → str[source]#

Converts string to upper case, as space separated words.

Parameters:: text – String to be converted to uppercase.
Returns:: String converted to uppercase, as space separated words.

Example

>>> upper_case('--foo-bar--')
'FOO BAR'
>>> upper_case('fooBar')
'FOO BAR'
>>> upper_case('/?*Foo10/;"B*Ar')
'FOO 10 B AR'

New in version 4.0.0.

Changed in version 5.0.0: Improved unicode word support.

pydash.strings.upper_first(text: str) → str[source]#

Converts the first character of string to upper case.

Parameters:: text – String passed in by the user.
Returns:: String in which the first character is converted to upper case.

Example

>>> upper_first('fred')
'Fred'
>>> upper_first('foo bar')
'Foo bar'
>>> upper_first('1foobar')
'1foobar'
>>> upper_first(';foobar')
';foobar'

New in version 4.0.0.

pydash.strings.url(*paths: Any, **params: Any) → str[source]#

Combines a series of URL paths into a single URL. Optionally, pass in keyword arguments to append query parameters.

Parameters:: paths – URL paths to combine.
Keyword Arguments:: params – Query parameters.
Returns:: URL string.

Example

>>> link = url('a', 'b', ['c', 'd'], '/', q='X', y='Z')
>>> path, params = link.split('?')
>>> path == 'a/b/c/d/'
True
>>> set(params.split('&')) == set(['q=X', 'y=Z'])
True

New in version 2.2.0.

pydash.strings.words(text: Any, pattern: str | None = None) → List[str][source]#

Return list of words contained in text.

References

https://github.com/lodash/lodash/blob/master/words.js#L30

Parameters:

text – String to split.
pattern – Custom pattern to split words on. Defaults to None.

Returns:

List of words.

Example

>>> words('a b, c; d-e')
['a', 'b', 'c', 'd', 'e']
>>> words('fred, barney, & pebbles', '/[^, ]+/g')
['fred', 'barney', '&', 'pebbles']

New in version 2.0.0.

Changed in version 3.2.0: Added pattern argument.

Changed in version 3.2.0: Improved matching for one character words.

Changed in version 5.0.0: Improved unicode word support.

Utilities#

Utility functions.

New in version 1.0.0.

pydash.utilities.attempt(func: ~typing.Callable[[~P], ~pydash.utilities.T], *args: ~typing.~P, **kwargs: ~typing.~P) → T | Exception[source]#

Attempts to execute func, returning either the result or the caught error object.

Parameters:: func – The function to attempt.
Returns:: Returns the func result or error object.

Example

>>> results = attempt(lambda x: x/0, 1)
>>> assert isinstance(results, ZeroDivisionError)

New in version 1.1.0.

pydash.utilities.cond(pairs: List[Tuple[Callable[[P], Any], Callable[[P], T]]], *extra_pairs: Tuple[Callable[[P], Any], Callable[[P], T]]) → Callable[[P], T][source]#

pydash.utilities.cond(pairs: List[List[Callable[[P], Any]]], *extra_pairs: List[Callable[[P], Any]]) → Callable[[P], Any]

Creates a function that iterates over pairs and invokes the corresponding function of the first predicate to return truthy.

Parameters:: pairs – A list of predicate-function pairs.
Returns:: Returns the new composite function.

Example

>>> func = cond([[matches({'a': 1}), constant('matches A')],                         [matches({'b': 2}), constant('matches B')],                         [stub_true, lambda value: value]])
>>> func({'a': 1, 'b': 2})
'matches A'
>>> func({'a': 0, 'b': 2})
'matches B'
>>> func({'a': 0, 'b': 0}) == {'a': 0, 'b': 0}
True

New in version 4.0.0.

Changed in version 4.2.0: Fixed missing argument passing to matched function and added support for passing in a single list of pairs instead of just pairs as separate arguments.

pydash.utilities.conforms(source: Dict[T, Callable[[T2], Any]]) → Callable[[Dict[T, T2]], bool][source]#

pydash.utilities.conforms(source: List[Callable[[T], Any]]) → Callable[[List[T]], bool]

Creates a function that invokes the predicate properties of source with the corresponding property values of a given object, returning True if all predicates return truthy, else False.

Parameters:: source – The object of property predicates to conform to.
Returns:: Returns the new spec function.

Example

>>> func = conforms({'b': lambda n: n > 1})
>>> func({'b': 2})
True
>>> func({'b': 0})
False
>>> func = conforms([lambda n: n > 1, lambda n: n == 0])
>>> func([2, 0])
True
>>> func([0, 0])
False

New in version 4.0.0.

pydash.utilities.conforms_to(obj: Dict[T, T2], source: Dict[T, Callable[[T2], Any]]) → bool[source]#

pydash.utilities.conforms_to(obj: List[T], source: List[Callable[[T], Any]]) → bool

Checks if obj conforms to source by invoking the predicate properties of source with the corresponding property values of obj.

Parameters:

obj – The object to inspect.
source – The object of property predicates to conform to.

Example

>>> conforms_to({'b': 2}, {'b': lambda n: n > 1})
True
>>> conforms_to({'b': 0}, {'b': lambda n: n > 1})
False
>>> conforms_to([2, 0], [lambda n: n > 1, lambda n: n == 0])
True
>>> conforms_to([0, 0], [lambda n: n > 1, lambda n: n == 0])
False

New in version 4.0.0.

pydash.utilities.constant(value: T) → Callable[[...], T][source]#

Creates a function that returns value.

Parameters:: value – Constant value to return.
Returns:: Function that always returns value.

Example

>>> pi = constant(3.14)
>>> pi() == 3.14
True

New in version 1.0.0.

Changed in version 4.0.0: Returned function ignores arguments instead of raising exception.

pydash.utilities.default_to(value: T | None, default_value: T2) → T | T2[source]#

Checks value to determine whether a default value should be returned in its place. The default_value is returned if value is None.

Parameters:: default_value – Default value passed in by the user.
Returns:: Returns value if value is given otherwise returns default_value.

Example

>>> default_to(1, 10)
1
>>> default_to(None, 10)
10

New in version 4.0.0.

pydash.utilities.default_to_any(value: None, *default_values: None) → None[source]#

pydash.utilities.default_to_any(value: T | None, default_value1: None, default_value2: T2) → T | T2

pydash.utilities.default_to_any(value: T | None, default_value1: None, default_value2: None, default_value3: T2) → T | T2

pydash.utilities.default_to_any(value: T | None, default_value1: None, default_value2: None, default_value3: None, default_value4: T2) → T | T2

pydash.utilities.default_to_any(value: T | None, default_value1: None, default_value2: None, default_value3: None, default_value4: None, default_value5: T2) → T | T2

pydash.utilities.default_to_any(value: T | None, *default_values: T2) → T | T2

Checks value to determine whether a default value should be returned in its place. The first item that is not None of the default_values is returned.

Parameters:

value – Value passed in by the user.
*default_values – Default values passed in by the user.

Returns:

Returns value if value is given otherwise returns the first not None value: of default_values.

Example

>>> default_to_any(1, 10, 20)
1
>>> default_to_any(None, 10, 20)
10
>>> default_to_any(None, None, 20)
20

New in version 4.9.0.

pydash.utilities.identity(arg: T, *args: Any) → T[source]#

pydash.utilities.identity(arg: None = None, *args: Any) → None

Return the first argument provided to it.

Parameters:: *args – Arguments.
Returns:: First argument or None.

Example

>>> identity(1)
1
>>> identity(1, 2, 3)
1
>>> identity() is None
True

New in version 1.0.0.

pydash.utilities.iteratee(func: Callable[[P], T]) → Callable[[P], T][source]#

pydash.utilities.iteratee(func: Any) → Callable

Return a pydash style iteratee. If func is a property name the created iteratee will return the property value for a given element. If func is an object the created iteratee will return True for elements that contain the equivalent object properties, otherwise it will return False.

Parameters:: func – Object to create iteratee function from.
Returns:: Iteratee function.

Example

>>> get_data = iteratee('data')
>>> get_data({'data': [1, 2, 3]})
[1, 2, 3]
>>> is_active = iteratee({'active': True})
>>> is_active({'active': True})
True
>>> is_active({'active': 0})
False
>>> iteratee(['a', 5])({'a': 5})
True
>>> iteratee(['a.b'])({'a.b': 5})
5
>>> iteratee('a.b')({'a': {'b': 5}})
5
>>> iteratee(('a', ['c', 'd', 'e']))({'a': 1, 'c': {'d': {'e': 3}}})
[1, 3]
>>> iteratee(lambda a, b: a + b)(1, 2)
3
>>> ident = iteratee(None)
>>> ident('a')
'a'
>>> ident(1, 2, 3)
1

New in version 1.0.0.

Changed in version 2.0.0: Renamed create_iteratee() to iteratee().

Changed in version 3.0.0: Made pluck style iteratee support deep property access.

Changed in version 3.1.0: - Added support for shallow pluck style property access via single item list/tuple. - Added support for matches property style iteratee via two item list/tuple.

Changed in version 4.0.0: Removed alias callback.

Changed in version 4.1.0: Return properties() callback when func is a tuple.

pydash.utilities.matches(source: Any) → Callable[[Any], bool][source]#

Creates a matches-style predicate function which performs a deep comparison between a given object and the source object, returning True if the given object has equivalent property values, else False.

Parameters:

source – Source object used for comparision.

Returns:

Function that compares an object to source and returns whether the two objects: contain the same items.

Example

>>> matches({'a': {'b': 2}})({'a': {'b': 2, 'c':3}})
True
>>> matches({'a': 1})({'b': 2, 'a': 1})
True
>>> matches({'a': 1})({'b': 2, 'a': 2})
False

New in version 1.0.0.

Changed in version 3.0.0: Use pydash.predicates.is_match() as matching function.

pydash.utilities.matches_property(key: Any, value: Any) → Callable[[Any], bool][source]#

Creates a function that compares the property value of key on a given object to value.

Parameters:

key – Object key to match against.
value – Value to compare to.

Returns:

Function that compares value to an object’s key and returns whether they are: equal.

Example

>>> matches_property('a', 1)({'a': 1, 'b': 2})
True
>>> matches_property(0, 1)([1, 2, 3])
True
>>> matches_property('a', 2)({'a': 1, 'b': 2})
False

New in version 3.1.0.

pydash.utilities.memoize(func: Callable[[P], T], resolver: None = None) → MemoizedFunc[P, T, str][source]#

pydash.utilities.memoize(func: Callable[[P], T], resolver: Callable[[P], T2] | None = None) → MemoizedFunc[P, T, T2]

Creates a function that memoizes the result of func. If resolver is provided it will be used to determine the cache key for storing the result based on the arguments provided to the memoized function. By default, all arguments provided to the memoized function are used as the cache key. The result cache is exposed as the cache property on the memoized function.

Parameters:

func – Function to memoize.
resolver – Function that returns the cache key to use.

Returns:

Memoized function.

Example

>>> ident = memoize(identity)
>>> ident(1)
1
>>> ident.cache['(1,){}'] == 1
True
>>> ident(1, 2, 3)
1
>>> ident.cache['(1, 2, 3){}'] == 1
True

New in version 1.0.0.

pydash.utilities.method(path: Hashable | List[Hashable], *args: Any, **kwargs: Any) → Callable[[...], Any][source]#

Creates a function that invokes the method at path on a given object. Any additional arguments are provided to the invoked method.

Parameters:

path – Object path of method to invoke.
*args – Global arguments to apply to method when invoked.
**kwargs – Global keyword argument to apply to method when invoked.

Returns:

Function that invokes method located at path for object.

Example

>>> obj = {'a': {'b': [None, lambda x: x]}}
>>> echo = method('a.b.1')
>>> echo(obj, 1) == 1
True
>>> echo(obj, 'one') == 'one'
True

New in version 3.3.0.

pydash.utilities.method_of(obj: Any, *args: Any, **kwargs: Any) → Callable[[...], Any][source]#

The opposite of method(). This method creates a function that invokes the method at a given path on object. Any additional arguments are provided to the invoked method.

Parameters:

obj – The object to query.
*args – Global arguments to apply to method when invoked.
**kwargs – Global keyword argument to apply to method when invoked.

Returns:

Function that invokes method located at path for object.

Example

>>> obj = {'a': {'b': [None, lambda x: x]}}
>>> dispatch = method_of(obj)
>>> dispatch('a.b.1', 1) == 1
True
>>> dispatch('a.b.1', 'one') == 'one'
True

New in version 3.3.0.

pydash.utilities.noop(*args: Any, **kwargs: Any) → None[source]#: A no-operation function.

New in version 1.0.0.

pydash.utilities.now() → int[source]#

Return the number of milliseconds that have elapsed since the Unix epoch (1 January 1970 00:00:00 UTC).

Returns:: Milliseconds since Unix epoch.

New in version 1.0.0.

Changed in version 3.0.0: Use datetime module for calculating elapsed time.

pydash.utilities.nth_arg(pos: int = 0) → Callable[[...], Any][source]#

Creates a function that gets the argument at index n. If n is negative, the nth argument from the end is returned.

Parameters:: pos – The index of the argument to return.
Returns:: Returns the new pass-thru function.

Example

>>> func = nth_arg(1)
>>> func(11, 22, 33, 44)
22
>>> func = nth_arg(-1)
>>> func(11, 22, 33, 44)
44

New in version 4.0.0.

pydash.utilities.over(funcs: Iterable[Callable[[P], T]]) → Callable[[P], List[T]][source]#

Creates a function that invokes all functions in funcs with the arguments it receives and returns their results.

Parameters:: funcs – List of functions to be invoked.
Returns:: Returns the new pass-thru function.

Example

>>> func = over([max, min])
>>> func(1, 2, 3, 4)
[4, 1]

New in version 4.0.0.

pydash.utilities.over_every(funcs: Iterable[Callable[[P], Any]]) → Callable[[P], bool][source]#

Creates a function that checks if all the functions in funcs return truthy when invoked with the arguments it receives.

Parameters:: funcs – List of functions to be invoked.
Returns:: Returns the new pass-thru function.

Example

>>> func = over_every([bool, lambda x: x is not None])
>>> func(1)
True

New in version 4.0.0.

pydash.utilities.over_some(funcs: Iterable[Callable[[P], Any]]) → Callable[[P], bool][source]#

Creates a function that checks if any of the functions in funcs return truthy when invoked with the arguments it receives.

Parameters:: funcs – List of functions to be invoked.
Returns:: Returns the new pass-thru function.

Example

>>> func = over_some([bool, lambda x: x is None])
>>> func(1)
True

New in version 4.0.0.

pydash.utilities.properties(*paths: Any) → Callable[[Any], Any][source]#

Like property_() except that it returns a list of values at each path in paths.

Parameters:: *path – Path values to fetch from object.
Returns:: Function that returns object’s path value.

Example

>>> getter = properties('a', 'b', ['c', 'd', 'e'])
>>> getter({'a': 1, 'b': 2, 'c': {'d': {'e': 3}}})
[1, 2, 3]

New in version 4.1.0.

pydash.utilities.property_(path: Hashable | List[Hashable]) → Callable[[Any], Any][source]#

Creates a function that returns the value at path of a given object.

Parameters:: path – Path value to fetch from object.
Returns:: Function that returns object’s path value.

Example

>>> get_data = property_('data')
>>> get_data({'data': 1})
1
>>> get_data({}) is None
True
>>> get_first = property_(0)
>>> get_first([1, 2, 3])
1

New in version 1.0.0.

Changed in version 4.0.1: Made property accessor work with deep path strings.

pydash.utilities.property_of(obj: Any) → Callable[[Hashable | List[Hashable]], Any][source]#

The inverse of property_(). This method creates a function that returns the key value of a given key on obj.

Parameters:: obj – Object to fetch values from.
Returns:: Function that returns object’s key value.

Example

>>> getter = property_of({'a': 1, 'b': 2, 'c': 3})
>>> getter('a')
1
>>> getter('b')
2
>>> getter('x') is None
True

New in version 3.0.0.

Changed in version 4.0.0: Removed alias prop_of.

pydash.utilities.random(start: int = 0, stop: int = 1, *, floating: Literal[False] = False) → int[source]#

pydash.utilities.random(start: float, stop: int = 1, floating: bool = False) → float

pydash.utilities.random(start: int = 0, *, stop: float, floating: bool = False) → float

pydash.utilities.random(start: float, stop: float, floating: bool = False) → float

pydash.utilities.random(start: float | int = 0, stop: float | int = 1, *, floating: Literal[True]) → float

Produces a random number between start and stop (inclusive). If only one argument is provided a number between 0 and the given number will be returned. If floating is truthy or either start or stop are floats a floating-point number will be returned instead of an integer.

Parameters:

start – Minimum value.
stop – Maximum value.
floating – Whether to force random value to float. Defaults to False.

Returns:

Random value.

Example

>>> 0 <= random() <= 1
True
>>> 5 <= random(5, 10) <= 10
True
>>> isinstance(random(floating=True), float)
True

New in version 1.0.0.

pydash.utilities.range_(stop: int) → Generator[int, None, None][source]#

pydash.utilities.range_(start: int, stop: int, step: int = 1) → Generator[int, None, None]

Creates a list of numbers (positive and/or negative) progressing from start up to but not including end. If start is less than stop, a zero-length range is created unless a negative step is specified.

Parameters:

start – Integer to start with. Defaults to 0.
stop – Integer to stop at.
step – The value to increment or decrement by. Defaults to 1.

Yields:

Next integer in range.

Example

>>> list(range_(5))
[0, 1, 2, 3, 4]
>>> list(range_(1, 4))
[1, 2, 3]
>>> list(range_(0, 6, 2))
[0, 2, 4]
>>> list(range_(4, 1))
[4, 3, 2]

New in version 1.0.0.

Changed in version 1.1.0: Moved to pydash.uilities.

Changed in version 3.0.0: Return generator instead of list.

Changed in version 4.0.0: Support decrementing when start argument is greater than stop argument.

pydash.utilities.range_right(stop: int) → Generator[int, None, None][source]#

pydash.utilities.range_right(start: int, stop: int, step: int = 1) → Generator[int, None, None]

Similar to range_(), except that it populates the values in descending order.

Parameters:

start – Integer to start with. Defaults to 0.
stop – Integer to stop at.
step – The value to increment or decrement by. Defaults to 1 if start < stop else -1.

Yields:

Next integer in range.

Example

>>> list(range_right(5))
[4, 3, 2, 1, 0]
>>> list(range_right(1, 4))
[3, 2, 1]
>>> list(range_right(0, 6, 2))
[4, 2, 0]

New in version 4.0.0.

pydash.utilities.result(obj: None, key: Any, default: None = None) → None[source]#

pydash.utilities.result(obj: None, key: Any, default: T) → T

pydash.utilities.result(obj: Any, key: Any, default: Any = None) → Any

Return the value of property key on obj. If key value is a function it will be invoked and its result returned, else the property value is returned. If obj is falsey then default is returned.

Parameters:

obj – Object to retrieve result from.
key – Key or index to get result from.
default – Default value to return if obj is falsey. Defaults to None.

Returns:

Result of obj[key] or None.

Example

>>> result({'a': 1, 'b': lambda: 2}, 'a')
1
>>> result({'a': 1, 'b': lambda: 2}, 'b')
2
>>> result({'a': 1, 'b': lambda: 2}, 'c') is None
True
>>> result({'a': 1, 'b': lambda: 2}, 'c', default=False)
False

New in version 1.0.0.

Changed in version 2.0.0: Added default argument.

pydash.utilities.retry(attempts: int = 3, delay: int | float = 0.5, max_delay: int | float = 150.0, scale: int | float = 2.0, jitter: int | float | ~typing.Tuple[float | int, float | int] = 0, exceptions: ~typing.Iterable[~typing.Type[Exception]] = (<class 'Exception'>,), on_exception: ~typing.Callable[[Exception, int], ~typing.Any] | None = None) → Callable[[CallableT], CallableT][source]#

Decorator that retries a function multiple times if it raises an exception with an optional delay between each attempt.

When a delay is supplied, there will be a sleep period in between retry attempts. The first delay time will always be equal to delay. After subsequent retries, the delay time will be scaled by scale up to max_delay. If max_delay is 0, then delay can increase unbounded.

Parameters:

attempts – Number of retry attempts. Defaults to 3.
delay – Base amount of seconds to sleep between retry attempts. Defaults to 0.5.
max_delay – Maximum number of seconds to sleep between retries. Is ignored when equal to 0. Defaults to 150.0 (2.5 minutes).
scale – Scale factor to increase delay after first retry fails. Defaults to 2.0.
jitter – Random jitter to add to delay time. Can be a positive number or 2-item tuple of numbers representing the random range to choose from. When a number is given, the random range will be from [0, jitter]. When jitter is a float or contains a float, then a random float will be chosen; otherwise, a random integer will be selected. Defaults to 0 which disables jitter.
exceptions – Tuple of exceptions that trigger a retry attempt. Exceptions not in the tuple will be ignored. Defaults to (Exception,) (all exceptions).
on_exception – Function that is called when a retryable exception is caught. It is invoked with on_exception(exc, attempt) where exc is the caught exception and attempt is the attempt count. All arguments are optional. Defaults to None.

Example

>>> @retry(attempts=3, delay=0)
... def do_something():
...     print('something')
...     raise Exception('something went wrong')
>>> try: do_something()
... except Exception: print('caught something')
something
something
something
caught something

..versionadded:: 4.4.0

..versionchanged:: 4.5.0: Added jitter argument.

pydash.utilities.stub_dict() → Dict[source]#

Returns empty “dict”.

Returns:: Empty dict.

Example

>>> stub_dict()
{}

New in version 4.0.0.

pydash.utilities.stub_false() → Literal[False][source]#

Returns False.

Returns:: False

Example

>>> stub_false()
False

New in version 4.0.0.

pydash.utilities.stub_list() → List[source]#

Returns empty “list”.

Returns:: Empty list.

Example

>>> stub_list()
[]

New in version 4.0.0.

pydash.utilities.stub_string() → str[source]#

Returns an empty string.

Returns:: Empty string

Example

>>> stub_string()
''

New in version 4.0.0.

pydash.utilities.stub_true() → Literal[True][source]#

Returns True.

Returns:: True

Example

>>> stub_true()
True

New in version 4.0.0.

pydash.utilities.times(n: int, iteratee: Callable[[...], T]) → List[T][source]#

pydash.utilities.times(n: int, iteratee: None = None) → List[int]

Executes the iteratee n times, returning a list of the results of each iteratee execution. The iteratee is invoked with one argument: (index).

Parameters:

n – Number of times to execute iteratee.
iteratee – Function to execute.

Returns:

A list of results from calling iteratee.

Example

>>> times(5, lambda i: i)
[0, 1, 2, 3, 4]

New in version 1.0.0.

Changed in version 3.0.0: Reordered arguments to make iteratee first.

Changed in version 4.0.0:

Re-reordered arguments to make iteratee last argument.
Added functionality for handling iteratee with zero positional arguments.

pydash.utilities.to_path(value: Hashable | List[Hashable]) → List[Hashable][source]#

Converts values to a property path array.

Parameters:: value – Value to convert.
Returns:: Returns the new property path array.

Example

>>> to_path('a.b.c')
['a', 'b', 'c']
>>> to_path('a[0].b.c')
['a', 0, 'b', 'c']
>>> to_path('a[0][1][2].b.c')
['a', 0, 1, 2, 'b', 'c']

New in version 4.0.0.

Changed in version 4.2.1: Ensure returned path is always a list.

pydash.utilities.unique_id(prefix: str | None = None) → str[source]#

Generates a unique ID. If prefix is provided the ID will be appended to it.

Parameters:: prefix – String prefix to prepend to ID value.
Returns:: ID value.

Example

>>> unique_id()
'1'
>>> unique_id('id_')
'id_2'
>>> unique_id()
'3'

New in version 1.0.0.