Developer Documentation

functional.streams

functional.streams.csv(csv_file, dialect='excel', **fmt_params)

Additional entry point to Sequence which parses the input of a csv stream or file according to the defined options. csv_file can be a filepath or an object that implements the iterator interface (defines next() or __next__() depending on python version).

>>> seq.csv('examples/camping_purchases.csv').take(2)
[['1', 'tent', '300'], ['2', 'food', '100']]
Parameters:
  • csv_file – path to file or iterator object
  • dialect – dialect of csv, passed to csv.reader
  • fmt_params – options passed to csv.reader
Returns:

Sequence wrapping csv file

functional.streams.json(json_file)

Additional entry point to Sequence which parses the input of a json file handler or file from the given path. Json files are parsed in the following ways depending on if the root is a dictionary or array. 1) If the json’s root is a dictionary, these are parsed into a sequence of (Key, Value) pairs 2) If the json’s root is an array, these are parsed into a sequence of entries

>>> seq.json('examples/users.json').first()
[u'sarah', {u'date_created': u'08/08', u'news_email': True, u'email': u'[email protected]'}]
Parameters:json_file – path or file containing json content
Returns:Sequence wrapping jsonl file
functional.streams.jsonl(jsonl_file)

Additional entry point to Sequence which parses the input of a jsonl file stream or file from the given path. Jsonl formatted files have a single valid json value on each line which is parsed by the python json module.

>>> seq.jsonl('examples/chat_logs.jsonl').first()
{u'date': u'10/09', u'message': u'hello anyone there?', u'user': u'bob'}
Parameters:jsonl_file – path or file containing jsonl content
Returns:Sequence wrapping jsonl file
functional.streams.open(path, delimiter=None, mode='r', buffering=-1, encoding=None, errors=None, newline=None)

Additional entry point to Sequence which parses input files as defined by options. Path specifies what file to parse. If delimiter is not None, then the file is read in bulk then split on it. If it is None (the default), then the file is parsed as sequence of lines. The rest of the options are passed directly to builtins.open with the exception that write/append file modes is not allowed.

>>> seq.open('examples/gear_list.txt').take(1)
[u'tent

‘]

param path:path to file
param delimiter:
 delimiter to split joined text on. if None, defaults to file.readlines()
param mode:file open mode
param buffering:
 passed to builtins.open
param encoding:passed to builtins.open
param errors:passed to builtins.open
param newline:passed to builtins.open
return:output of file depending on options wrapped in a Sequence via seq
functional.streams.range(*args)

Additional entry point to Sequence which wraps the builtin range generator. seq.range(args) is equivalent to seq(range(args)).

>>> seq.range(1, 8, 2)
[1, 3, 5, 7]
Parameters:args – args to range function
Returns:range(args) wrapped by a sequence
functional.streams.seq(*args)

Primary entrypoint for the functional package. Returns a functional.pipeline.Sequence wrapping the original sequence.

Additionally it parses various types of input to a Sequence as best it can.

>>> seq([1, 2, 3])
[1, 2, 3]
>>> seq(1, 2, 3)
[1, 2, 3]
>>> seq(1)
[1]
>>> seq(range(4))
[0, 1, 2, 3]
>>> type(seq([1, 2]))
functional.pipeline.Sequence
>>> type(Sequence([1, 2]))
functional.pipeline.Sequence
Parameters:args – Three types of arguments are valid. 1) Iterable which is then directly wrapped as a Sequence 2) A list of arguments is converted to a Sequence 3) A single non-iterable is converted to a single element Sequence
Returns:wrapped sequence

functional.pipeline

The pipeline module contains the primary data structure Sequence and entry point seq

class functional.pipeline.Sequence(sequence, transform=None)

Bases: object

Sequence is a wrapper around any type of sequence which provides access to common functional transformations and reductions in a data pipelining style

__add__(other)

Concatenates sequence with other.

Parameters:other – sequence to concatenate
Returns:concatenated sequence with other
__bool__()

Returns True if size is not zero.

Returns:True if size is not zero
__contains__(item)

Checks if item is in sequence.

Parameters:item – item to check
Returns:True if item is in sequence
__dict__ = dict_proxy({'all': <function all at 0x7f52c9f5b230>, 'set': <function set at 0x7f52c9f5c5f0>, 'symmetric_difference': <function symmetric_difference at 0x7f52c9f49b90>, '__str__': <function __str__ at 0x7f52c9f5ade8>, '_unwrap_sequence': <function _unwrap_sequence at 0x7f52c9f5ab18>, 'to_jsonl': <function to_jsonl at 0x7f52c9f5c7d0>, 'to_json': <function to_json at 0x7f52c9f5c848>, 'enumerate': <function enumerate at 0x7f52c9f5bcf8>, '__dict__': <attribute '__dict__' of 'Sequence' objects>, '__weakref__': <attribute '__weakref__' of 'Sequence' objects>, 'find': <function find at 0x7f52c9f5b578>, 'select': <function select at 0x7f52c9f49c80>, 'size': <function size at 0x7f52c9f5b050>, 'min': <function min at 0x7f52c9f5b410>, 'difference': <function difference at 0x7f52c9f49b18>, 'order_by': <function order_by at 0x7f52c9f5c230>, 'zip': <function zip at 0x7f52c9f5bc08>, 'grouped': <function grouped at 0x7f52c9f5c0c8>, 'distinct': <function distinct at 0x7f52c9f5c320>, '__eq__': <function __eq__ at 0x7f52c9f5ac08>, 'cache': <function cache at 0x7f52c9f49320>, 'init': <function init at 0x7f52c9f495f0>, 'drop_right': <function drop_right at 0x7f52c9f49848>, 'tail': <function tail at 0x7f52c9f49668>, 'group_by': <function group_by at 0x7f52c9f5b6e0>, 'dict': <function dict at 0x7f52c9f5c6e0>, 'right_join': <function right_join at 0x7f52c9f5bed8>, 'to_file': <function to_file at 0x7f52c9f5c758>, '__doc__': '\n Sequence is a wrapper around any type of sequence which provides access to common\n functional transformations and reductions in a data pipelining style\n ', 'empty': <function empty at 0x7f52c9f5b0c8>, 'count': <function count at 0x7f52c9f49ed8>, 'head': <function head at 0x7f52c9f49398>, 'make_string': <function make_string at 0x7f52c9f5b8c0>, '__getitem__': <function __getitem__ at 0x7f52c9f5af50>, 'non_empty': <function non_empty at 0x7f52c9f5b140>, 'to_csv': <function to_csv at 0x7f52c9f5c8c0>, '__iter__': <function __iter__ at 0x7f52c9f5ab90>, 'drop_while': <function drop_while at 0x7f52c9f498c0>, 'inits': <function inits at 0x7f52c9f496e0>, '__bool__': <function __bool__ at 0x7f52c9f5ae60>, 'sorted': <function sorted at 0x7f52c9f5c1b8>, 'intersection': <function intersection at 0x7f52c9f49aa0>, 'max_by': <function max_by at 0x7f52c9f5b488>, 'last_option': <function last_option at 0x7f52c9f49578>, 'to_set': <function to_set at 0x7f52c9f5c578>, '__reversed__': <function __reversed__ at 0x7f52c9f49050>, '__nonzero__': <function __nonzero__ at 0x7f52c9f5aed8>, 'drop': <function drop at 0x7f52c9f497d0>, 'list': <function list at 0x7f52c9f5c500>, 'to_list': <function to_list at 0x7f52c9f5c488>, 'distinct_by': <function distinct_by at 0x7f52c9f5c398>, 'to_dict': <function to_dict at 0x7f52c9f5c668>, '__hash__': <function __hash__ at 0x7f52c9f5acf8>, 'where': <function where at 0x7f52c9f49e60>, '__module__': 'functional.pipeline', '_transform': <function _transform at 0x7f52c9f49230>, 'exists': <function exists at 0x7f52c9f5b2a8>, 'sequence': <property object at 0x7f52c9f4fc58>, 'reduce': <function reduce at 0x7f52c9f5b848>, 'min_by': <function min_by at 0x7f52c9f5b500>, 'fold_left': <function fold_left at 0x7f52c9f5bb18>, 'flatten': <function flatten at 0x7f52c9f5b5f0>, 'for_all': <function for_all at 0x7f52c9f5b320>, 'flat_map': <function flat_map at 0x7f52c9f5b668>, 'any': <function any at 0x7f52c9f5b1b8>, '__init__': <function __init__ at 0x7f52c9f5aaa0>, 'slice': <function slice at 0x7f52c9f5c410>, 'join': <function join at 0x7f52c9f5bde8>, '__contains__': <function __contains__ at 0x7f52c9f490c8>, 'sum': <function sum at 0x7f52c9f5b9b0>, 'for_each': <function for_each at 0x7f52c9f49cf8>, 'fold_right': <function fold_right at 0x7f52c9f5bb90>, 'partition': <function partition at 0x7f52c9f5c050>, 'inner_join': <function inner_join at 0x7f52c9f5bd70>, 'take': <function take at 0x7f52c9f49938>, 'max': <function max at 0x7f52c9f5b398>, 'sliding': <function sliding at 0x7f52c9f5c140>, '__ne__': <function __ne__ at 0x7f52c9f5ac80>, 'product': <function product at 0x7f52c9f5b938>, 'outer_join': <function outer_join at 0x7f52c9f5bf50>, 'take_while': <function take_while at 0x7f52c9f499b0>, 'len': <function len at 0x7f52c9f49f50>, '_evaluate': <function _evaluate at 0x7f52c9f491b8>, 'zip_with_index': <function zip_with_index at 0x7f52c9f5bc80>, '__add__': <function __add__ at 0x7f52c9f49140>, 'aggregate': <function aggregate at 0x7f52c9f5baa0>, 'reduce_by_key': <function reduce_by_key at 0x7f52c9f5b7d0>, 'last': <function last at 0x7f52c9f49500>, 'reverse': <function reverse at 0x7f52c9f5c2a8>, 'group_by_key': <function group_by_key at 0x7f52c9f5b758>, 'average': <function average at 0x7f52c9f5ba28>, 'left_join': <function left_join at 0x7f52c9f5be60>, 'filter_not': <function filter_not at 0x7f52c9f49de8>, 'filter': <function filter at 0x7f52c9f49d70>, 'union': <function union at 0x7f52c9f49a28>, 'map': <function map at 0x7f52c9f49c08>, '__repr__': <function __repr__ at 0x7f52c9f5ad70>, 'tails': <function tails at 0x7f52c9f49758>, 'head_option': <function head_option at 0x7f52c9f49488>, 'first': <function first at 0x7f52c9f49410>})
__eq__(other)

Checks for equality with the sequence’s equality operator.

Parameters:other – object to compare to
Returns:true if the underlying sequence is equal to other
__getitem__(item)

Gets item at given index.

Parameters:item – key to use for getitem
Returns:item at index key
__hash__()

Return the hash of the sequence.

Returns:hash of sequence
__init__(sequence, transform=None)

Takes a sequence and wraps it around a Sequence object.

If the sequence is already an instance of Sequence, __init__ will insure that it is at most wrapped exactly once.

If the sequence is a list or tuple, it is set as the sequence.

If it is an iterable, then it is expanded into a list then set to the sequence

If the object does not fit any of these classes, a TypeError is thrown

Parameters:sequence – sequence of items to wrap in a Sequence
Returns:sequence wrapped in a Sequence
__iter__()

Return iterator of sequence.

Returns:iterator of sequence
__module__ = 'functional.pipeline'
__ne__(other)

Checks for inequality with the sequence’s inequality operator.

Parameters:other – object to compare to
Returns:true if the underlying sequence is not equal to other
__nonzero__()

Returns True if size is not zero.

Returns:True if size is not zero
__repr__()

Return repr using sequence’s repr function.

Returns:sequence’s repr
__reversed__()

Return reversed sequence using sequence’s reverse function

Returns:reversed sequence
__str__()

Return string using sequence’s string function.

Returns:sequence’s string
__weakref__

list of weak references to the object (if defined)

_evaluate()

Creates and returns an iterator which applies all the transformations in the lineage

Returns:iterator over the transformed sequence
_transform(transform)

Copies the given Sequence and appends new transformation :param transform: transform to apply :return: transformed sequence

_unwrap_sequence()

Retrieves the root sequence wrapped by one or more Sequence objects. Will not evaluate lineage, used internally in fetching lineage and the base sequence to use.

Returns:root sequence
aggregate(*args)

Aggregates the sequence by specified arguments. Its behavior varies depending on if one, two, or three arguments are passed. Assuming the type of the sequence is A:

One Argument: argument specifies a function of the type f(current: B, next: A => result: B. current represents results computed so far, and next is the next element to aggregate into current in order to return result.

Two Argument: the first argument is the seed value for the aggregation. The second argument is the same as for the one argument case.

Three Argument: the first two arguments are the same as for one and two argument calls. The additional third parameter is a function applied to the result of the aggregation before returning the value.

Parameters:args – options for how to execute the aggregation
Returns:aggregated value
all()

Returns True if the truth value of all items in the sequence true.

>>> seq([True, True]).all()
True
>>> seq([True, False]).all()
False
Returns:True if all items truth value evaluates to True
any()

Returns True if any element in the sequence has truth value True

>>> seq([True, False]).any()
True
>>> seq([False, False]).any()
False
Returns:True if any element is True
average(projection=None)

Takes the average of elements in the sequence

>>> seq([1, 2]).average()
1.5
>>> seq([('a', 1), ('b', 2)]).average(lambda x: x[1])
Parameters:projection – function to project on the sequence before taking the average
Returns:average of elements in the sequence
cache(delete_lineage=False)

Caches the result of the Sequence so far. This means that any functions applied on the pipeline before cache() are evaluated, and the result is stored in the Sequence. This is primarily used internally and is no more helpful than to_list() externally. delete_lineage allows for cache() to be used in internal initialization calls without the caller having knowledge of the internals via the lineage

Parameters:delete_lineage – If set to True, it will cache then erase the lineage
count(func)

Counts the number of elements in the sequence which satisfy the predicate func.

>>> seq([-1, -2, 1, 2]).count(lambda x: x > 0)
2
Parameters:func – predicate to count elements on
Returns:count of elements that satisfy predicate
dict(default=None)

Converts sequence of (Key, Value) pairs to a dictionary.

>>> type(seq([('a', 1)]).dict())
dict
>>> seq([('a', 1), ('b', 2)]).dict()
{'a': 1, 'b': 2}
Parameters:default – Can be a callable zero argument function. When not None, the returned dictionary is a collections.defaultdict with default as value for missing keys. If the value is not callable, then a zero argument lambda function is created returning the value and used for collections.defaultdict
Returns:dictionary from sequence of (Key, Value) elements
difference(other)

New sequence with unique elements present in sequence but not in other.

>>> seq([1, 2, 3]).difference([2, 3, 4])
[1]
Parameters:other – sequence to perform difference with
Returns:difference of sequence and other
distinct()

Returns sequence of distinct elements. Elements must be hashable.

>>> seq([1, 1, 2, 3, 3, 3, 4]).distinct()
[1, 2, 3, 4]
Returns:sequence of distinct elements
distinct_by(func)

Returns sequence of elements who are distinct by the passed function. The return value of func must be hashable. When two elements are distinct by func, the first is taken.

Parameters:func – function to use for determining distinctness
Returns:elements distinct by func
drop(n)

Drop the first n elements of the sequence.

>>> seq([1, 2, 3, 4, 5]).drop(2)
[3, 4, 5]
Parameters:n – number of elements to drop
Returns:sequence without first n elements
drop_right(n)

Drops the last n elements of the sequence.

>>> seq([1, 2, 3, 4, 5]).drop_right(2)
[1, 2, 3]
Parameters:n – number of elements to drop
Returns:sequence with last n elements dropped
drop_while(func)

Drops elements in the sequence while func evaluates to True, then returns the rest.

>>> seq([1, 2, 3, 4, 5, 1, 2]).drop_while(lambda x: x < 3)
[3, 4, 5, 1, 2]
Parameters:func – truth returning function
Returns:elements including and after func evaluates to False
empty()

Returns True if the sequence has length zero.

>>> seq([]).empty()
True
>>> seq([1]).empty()
False
Returns:True if sequence length is zero
enumerate(start=0)

Uses python enumerate to to zip the sequence with indexes starting at start.

>>> seq(['a', 'b', 'c']).enumerate(start=1)
[(1, 'a'), (2, 'b'), (3, 'c')]
Parameters:start – Beginning of zip
Returns:enumerated sequence starting at start
exists(func)

Returns True if an element in the sequence makes func evaluate to True.

>>> seq([1, 2, 3, 4]).exists(lambda x: x == 2)
True
>>> seq([1, 2, 3, 4]).exists(lambda x: x < 0)
False
Parameters:func – existence check function
Returns:True if any element satisfies func
filter(func)

Filters sequence to include only elements where func is True.

>>> seq([-1, 1, -2, 2]).filter(lambda x: x > 0)
[1, 2]
Parameters:func – function to filter on
Returns:filtered sequence
filter_not(func)

Filters sequence to include only elements where func is False.

>>> seq([-1, 1, -2, 2]).filter_not(lambda x: x > 0)
[-1, -2]
Parameters:func – function to filter_not on
Returns:filtered sequence
find(func)

Finds the first element of the sequence that satisfies func. If no such element exists, then return None.

>>> seq(["abc", "ab", "bc"]).find(lambda x: len(x) == 2)
'ab'
Parameters:func – function to find with
Returns:first element to satisfy func or None
first()

Returns the first element of the sequence.

>>> seq([1, 2, 3]).first()
1

Raises IndexError when the sequence is empty.

>>> seq([]).first()
Traceback (most recent call last):
 ...
IndexError: list index out of range
Returns:first element of sequence
flat_map(func)

Applies func to each element of the sequence, which themselves should be sequences. Then appends each element of each sequence to a final result

>>> seq([[1, 2], [3, 4], [5, 6]]).flat_map(lambda x: x)
[1, 2, 3, 4, 5, 6]
>>> seq(["a", "bc", "def"]).flat_map(list)
['a', 'b', 'c', 'd', 'e', 'f']
>>> seq([[1], [2], [3]]).flat_map(lambda x: x * 2)
[1, 1, 2, 2, 3, 3]
Parameters:func – function to apply to each sequence in the sequence
Returns:application of func to elements followed by flattening
flatten()

Flattens a sequence of sequences to a single sequence of elements.

>>> seq([[1, 2], [3, 4], [5, 6]])
[1, 2, 3, 4, 5, 6]
Returns:flattened sequence
fold_left(zero_value, func)

Assuming that the sequence elements are of type A, folds from left to right starting with the seed value given by zero_value (of type A) using a function of type func(current: B, next: A) => B. current represents the folded value so far and next is the next element from the sequence to fold into current.

>>> seq('a', 'b', 'c').fold_left(['start'], lambda current, next: current + [next]))
['start', 'a', 'b', 'c']
Parameters:
  • zero_value – zero value to reduce into
  • func – Two parameter function as described by function docs
Returns:

value from folding values with func into zero_value from left to right.

fold_right(zero_value, func)

Assuming that the sequence elements are of type A, folds from right to left starting with the seed value given by zero_value (of type A) using a function of type func(next: A, current: B) => B. current represents the folded value so far and next is the next element from the sequence to fold into current.

>>> seq('a', 'b', 'c').fold_left(['start'], lambda next, current: current + [next])
['start', 'c', 'b', a']
Parameters:
  • zero_value – zero value to reduce into
  • func – Two parameter function as described by function docs
Returns:

value from folding values with func into zero_value from right to left

for_all(func)

Returns True if all elements in sequence make func evaluate to True.

>>> seq([1, 2, 3]).for_all(lambda x: x > 0)
True
>>> seq([1, 2, -1]).for_all(lambda x: x > 0)
False
Parameters:func – function to check truth value of all elements with
Returns:True if all elements make func evaluate to True
for_each(func)

Executes func on each element of the sequence.

>>> l = []
>>> seq([1, 2, 3, 4]).for_each(l.append)
>>> l
[1, 2, 3, 4]
Parameters:func – function to execute
group_by(func)

Group elements into a list of (Key, Value) tuples where func creates the key and maps to values matching that key.

>>> seq(["abc", "ab", "z", "f", "qw"]).group_by(len)
[(1, ['z', 'f']), (2, ['ab', 'qw']), (3, ['abc'])]
Parameters:func – group by result of this function
Returns:grouped sequence
group_by_key()

Group sequence of (Key, Value) elements by Key.

>>> seq([('a', 1), ('b', 2), ('b', 3), ('b', 4), ('c', 3), ('c', 0)]).group_by_key()
[('a', [1]), ('c', [3, 0]), ('b', [2, 3, 4])]
Returns:sequence grouped by key
grouped(size)

Partitions the elements into groups of length size.

>>> seq([1, 2, 3, 4, 5, 6, 7, 8]).grouped(2)
[[1, 2], [3, 4], [5, 6], [7, 8]]
>>> seq([1, 2, 3, 4, 5, 6, 7, 8]).grouped(3)
[[1, 2, 3], [4, 5, 6], [7, 8]]

The last partition has at least one element but may have less than size elements.

Parameters:size – size of the partitions
Returns:sequence partitioned into groups of length size
head()

Returns the first element of the sequence.

>>> seq([1, 2, 3]).head()
1

Raises IndexError when the sequence is empty.

>>> seq([]).head()
Traceback (most recent call last):
 ...
IndexError: list index out of range
Returns:first element of sequence
head_option()

Returns the first element of the sequence or None, if the sequence is empty.

>>> seq([1, 2, 3]).head_option()
1
>>> seq([]).head_option()
None
Returns:first element of sequence or None if sequence is empty
init()

Returns the sequence, without its last element.

>>> seq([1, 2, 3]).init()
[1, 2]
Returns:sequence without last element
inits()

Returns consecutive inits of the sequence.

>>> seq([1, 2, 3]).inits()
[[1, 2, 3], [1, 2], [1], []]
Returns:consecutive init()s on sequence
inner_join(other)

Sequence and other must be composed of (Key, Value) pairs. If self.sequence contains (K, V) pairs and other contains (K, W) pairs, the return result is a sequence of (K, (V, W)) pairs. Will return only elements where the key exists in both sequences.

>>> seq([('a', 1), ('b', 2), ('c', 3)]).inner_join([('a', 2), ('c', 5)])
[('a', (1, 2)), ('c', (3, 5))]
Parameters:other – sequence to join with
Returns:joined sequence of (K, (V, W)) pairs
intersection(other)

New sequence with unique elements present in sequence and other.

>>> seq([1, 1, 2, 3]).intersection([2, 3, 4])
[2, 3]
Parameters:other – sequence to perform intersection with
Returns:intersection of sequence and other
join(other, join_type='inner')

Sequence and other must be composed of (Key, Value) pairs. If self.sequence contains (K, V) pairs and other contains (K, W) pairs, the return result is a sequence of (K, (V, W)) pairs. If join_type is “left”, V values will always be present, W values may be present or None. If join_type is “right”, W values will always be present, W values may be present or None. If join_type is “outer”, V or W may be present or None, but never at the same time.

>>> seq([('a', 1), ('b', 2), ('c', 3)]).join([('a', 2), ('c', 5)], "inner")
[('a', (1, 2)), ('c', (3, 5))]
>>> seq([('a', 1), ('b', 2), ('c', 3)]).join([('a', 2), ('c', 5)])
[('a', (1, 2)), ('c', (3, 5))]
>>> seq([('a', 1), ('b', 2)]).join([('a', 3), ('c', 4)], "left")
[('a', (1, 3)), ('b', (2, None)]
>>> seq([('a', 1), ('b', 2)]).join([('a', 3), ('c', 4)], "right")
[('a', (1, 3)), ('c', (None, 4)]
>>> seq([('a', 1), ('b', 2)]).join([('a', 3), ('c', 4)], "outer")
[('a', (1, 3)), ('b', (2, None)), ('c', (None, 4))]
Parameters:
  • other – sequence to join with
  • join_type – specifies join_type, may be “left”, “right”, or “outer”
Returns:

side joined sequence of (K, (V, W)) pairs

last()

Returns the last element of the sequence.

>>> seq([1, 2, 3]).last()
3

Raises IndexError when the sequence is empty.

>>> seq([]).last()
Traceback (most recent call last):
 ...
IndexError: list index out of range
Returns:last element of sequence
last_option()

Returns the last element of the sequence or None, if the sequence is empty.

>>> seq([1, 2, 3]).last_option()
3
>>> seq([]).last_option()
None
Returns:last element of sequence or None if sequence is empty
left_join(other)

Sequence and other must be composed of (Key, Value) pairs. If self.sequence contains (K, V) pairs and other contains (K, W) pairs, the return result is a sequence of (K, (V, W)) pairs. V values will always be present, W values may be present or None.

>>> seq([('a', 1), ('b', 2)]).join([('a', 3), ('c', 4)])
[('a', (1, 3)), ('b', (2, None)]
Parameters:other – sequence to join with
Returns:left joined sequence of (K, (V, W)) pairs
len()

Return length of sequence using its length function.

>>> seq([1, 2, 3]).len()
3
Returns:length of sequence
list()

Converts sequence to list of elements.

>>> type(seq([]).list())
list
>>> type(seq([]))
functional.pipeline.Sequence
>>> seq([1, 2, 3]).list()
[1, 2, 3]
Returns:list of elements in sequence
make_string(separator)

Concatenate the elements of the sequence into a string separated by separator.

>>> seq([1, 2, 3]).make_string("@")
'[email protected]@3'
Parameters:separator – string separating elements in string
Returns:concatenated string separated by separator
map(func)

Maps f onto the elements of the sequence.

>>> seq([1, 2, 3, 4]).map(lambda x: x * -1)
[-1, -2, -3, -4]
Parameters:func – function to map with
Returns:sequence with func mapped onto it
max()

Returns the largest element in the sequence. If the sequence has multiple maximal elements, only the first one is returned.

The compared objects must have defined comparison methods. Raises TypeError when the objects are not comparable.

The sequence can not be empty. Raises ValueError when the sequence is empty.

>>> seq([2, 4, 5, 1, 3]).max()
5
>>> seq('aa', 'xyz', 'abcd', 'xyy').max()
'xyz'
>>> seq([1, "a"]).max()
Traceback (most recent call last):
 ...
TypeError: unorderable types: int() < str()
>>> seq([]).max()
Traceback (most recent call last):
 ...
ValueError: max() arg is an empty sequence
Returns:Maximal value of sequence
max_by(func)

Returns the largest element in the sequence. Provided function is used to generate key used to compare the elements. If the sequence has multiple maximal elements, only the first one is returned.

The sequence can not be empty. Raises ValueError when the sequence is empty.

>>> seq([2, 4, 5, 1, 3]).max_by(lambda num: num % 4)
3
>>> seq('aa', 'xyz', 'abcd', 'xyy').max_by(len)
'abcd'
>>> seq([]).max_by(lambda x: x)
Traceback (most recent call last):
 ...
ValueError: max() arg is an empty sequence
Parameters:func – function to compute max by
Returns:Maximal element by func(element)
min()

Returns the smallest element in the sequence. If the sequence has multiple minimal elements, only the first one is returned.

The compared objects must have defined comparison methods. Raises TypeError when the objects are not comparable.

The sequence can not be empty. Raises ValueError when the sequence is empty.

>>> seq([2, 4, 5, 1, 3]).min()
1
>>> seq('aa', 'xyz', 'abcd', 'xyy').min()
'aa'
>>> seq([1, "a"]).min()
Traceback (most recent call last):
 ...
TypeError: unorderable types: int() < str()
>>> seq([]).min()
Traceback (most recent call last):
 ...
ValueError: min() arg is an empty sequence
Returns:Minimal value of sequence
min_by(func)

Returns the smallest element in the sequence. Provided function is used to generate key used to compare the elements. If the sequence has multiple minimal elements, only the first one is returned.

The sequence can not be empty. Raises ValueError when the sequence is empty.

>>> seq([2, 4, 5, 1, 3]).min_by(lambda num: num % 6)
5
>>> seq('aa', 'xyz', 'abcd', 'xyy').min_by(len)
'aa'
>>> seq([]).min_by(lambda x: x)
Traceback (most recent call last):
 ...
ValueError: min() arg is an empty sequence
Parameters:func – function to compute min by
Returns:Maximal element by func(element)
non_empty()

Returns True if the sequence does not have length zero.

>>> seq([]).non_empty()
False
>>> seq([1]).non_empty()
True
Returns:True if sequence length is not zero
order_by(func)

Orders the input according to func

>>> seq([(2, 'a'), (1, 'b'), (4, 'c'), (3, 'd')]).order_by(lambda x: x[0])
[1, 2, 3, 4]
Parameters:func – order by funciton
Returns:ordered sequence
outer_join(other)

Sequence and other must be composed of (Key, Value) pairs. If self.sequence contains (K, V) pairs and other contains (K, W) pairs, the return result is a sequence of (K, (V, W)) pairs. One of V or W will always be not None, but the other may be None

>>> seq([('a', 1), ('b', 2)]).outer_join([('a', 3), ('c', 4)], "outer")
[('a', (1, 3)), ('b', (2, None)), ('c', (None, 4))]
Parameters:other – sequence to join with
Returns:outer joined sequence of (K, (V, W)) pairs
partition(func)

Partition the sequence based on satisfying the predicate func.

>>> seq([-1, 1, -2, 2]).partition(lambda x: x < 0)
([-1, -2], [1, 2])
Parameters:func – predicate to partition on
Returns:tuple of partitioned sequences
product(projection=None)

Takes product of elements in sequence.

>>> seq([1, 2, 3, 4]).product()
24
>>> seq([]).product()
1
>>> seq([(1, 2), (1, 3), (1, 4)]).product(lambda x: x[0])
1
Parameters:projection – function to project on the sequence before taking the product
Returns:product of elements in sequence
reduce(func)

Reduce sequence of elements using func.

>>> seq([1, 2, 3]).reduce(lambda x, y: x + y)
6
Parameters:func – two parameter, associative reduce function
Returns:reduced value using func
reduce_by_key(func)

Reduces a sequence of (Key, Value) using func on each sequence of values.

>>> seq([('a', 1), ('b', 2), ('b', 3), ('b', 4), ('c', 3), ('c', 0)])                 .reduce_by_key(lambda x, y: x + y)
[('a', 1), ('c', 3), ('b', 9)]
Parameters:func – reduce each list of values using two parameter, associative func
Returns:Sequence of tuples where the value is reduced with func
reverse()

Returns the reversed sequence.

>>> seq([1, 2, 3]).reverse()
[3, 2, 1]
Returns:reversed sequence
right_join(other)

Sequence and other must be composed of (Key, Value) pairs. If self.sequence contains (K, V) pairs and other contains (K, W) pairs, the return result is a sequence of (K, (V, W)) pairs. W values will always bepresent, V values may be present or None.

>>> seq([('a', 1), ('b', 2)]).join([('a', 3), ('c', 4)])
[('a', (1, 3)), ('b', (2, None)]
Parameters:other – sequence to join with
Returns:right joined sequence of (K, (V, W)) pairs
select(func)

Selects f from the elements of the sequence.

>>> seq([1, 2, 3, 4]).select(lambda x: x * -1)
[-1, -2, -3, -4]
Parameters:func – function to select with
Returns:sequence with func mapped onto it
sequence

Alias for to_list used internally for brevity

Returns:result of to_list() on sequence
set()

Converts sequence to a set of elements.

>>> type(seq([])).to_set()
set
>>> type(seq([]))
functional.pipeline.Sequence
>>> seq([1, 1, 2, 2]).set()
{1, 2}

:return:set of elements in sequence

size()

Return size of sequence using its length function.

Returns:size of sequence
slice(start, until)

Takes a slice of the sequence starting at start and until but not including until.

>>> seq([1, 2, 3, 4]).slice(1, 2)
[2]
>>> seq([1, 2, 3, 4]).slice(1, 3)
[2, 3]
Parameters:
  • start – starting index
  • until – ending index
Returns:

slice including start until but not including until

sliding(size, step=1)

Groups elements in fixed size blocks by passing a sliding window over them.

The last window has at least one element but may have less than size elements

Parameters:
  • size – size of sliding window
  • step – step size between windows
Returns:

sequence of sliding windows

sorted(key=None, reverse=False)

Uses python sort and its passed arguments to sort the input.

>>> seq([2, 1, 4, 3]).sorted()
[1, 2, 3, 4]
Parameters:
  • key – sort using key function
  • reverse – return list reversed or not
Returns:

sorted sequence

sum(projection=None)

Takes sum of elements in sequence.

>>> seq([1, 2, 3, 4]).sum()
10
>>> seq([(1, 2), (1, 3), (1, 4)]).sum(lambda x: x[0])
3
Parameters:projection – function to project on the sequence before taking the sum
Returns:sum of elements in sequence
symmetric_difference(other)

New sequence with elements in either sequence or other, but not both.

>>> seq([1, 2, 3, 3]).symmetric_difference([2, 4, 5])
[1, 3, 4, 5]
Parameters:other – sequence to perform symmetric difference with
Returns:symmetric difference of sequence and other
tail()

Returns the sequence, without its first element.

>>> seq([1, 2, 3]).init()
[2, 3]
Returns:sequence without first element
tails()

Returns consecutive tails of the sequence.

>>> seq([1, 2, 3]).tails()
[[1, 2, 3], [2, 3], [3], []]
Returns:consecutive tail()s of the sequence
take(n)

Take the first n elements of the sequence.

>>> seq([1, 2, 3, 4]).take(2)
[1, 2]
Parameters:n – number of elements to take
Returns:first n elements of sequence
take_while(func)

Take elements in the sequence until func evaluates to False, then return them.

>>> seq([1, 2, 3, 4, 5, 1, 2]).take_while(lambda x: x < 3)
[1, 2]
Parameters:func – truth returning function
Returns:elements taken until func evaluates to False
to_csv(path, mode='wb', dialect='excel', **fmtparams)

Saves the sequence to a csv file. Each element should be an iterable which will be expanded to the elements of each row.

Parameters:
  • path – path to write file
  • dialect – passed to csv.writer
  • fmtparams – passed to csv.writer
to_dict(default=None)

Converts sequence of (Key, Value) pairs to a dictionary.

>>> type(seq([('a', 1)]).to_dict())
dict
>>> seq([('a', 1), ('b', 2)]).to_dict()
{'a': 1, 'b': 2}
Parameters:default – Can be a callable zero argument function. When not None, the returned dictionary is a collections.defaultdict with default as value for missing keys. If the value is not callable, then a zero argument lambda function is created returning the value and used for collections.defaultdict
Returns:dictionary from sequence of (Key, Value) elements
to_file(path, delimiter=None, mode='w', buffering=-1, encoding=None, errors=None, newline=None)

Saves the sequence to a file by executing str(self) which becomes str(self.to_list()). If delimiter is defined will instead execute self.make_string(delimiter)

Parameters:
  • path – path to write file
  • delimiter – if defined, will call make_string(delimiter) and save that to file.
  • mode – file open mode
  • buffering – passed to builtins.open
  • encoding – passed to builtins.open
  • errors – passed to builtins.open
  • newline – passed to builtins.open
to_json(path, root_array=True, mode='wb')

Saves the sequence to a json file. If root_array is True, then the sequence will be written to json with an array at the root. If it is False, then the sequence will be converted from a sequence of (Key, Value) pairs to a dictionary so that the json root is a dictionary.

Parameters:
  • path – path to write file
  • root_array – write json root as an array or dictionary
  • mode – file open mode
to_jsonl(path, mode='w')

Saves the sequence to a jsonl file. Each element is mapped using json.dumps then written with a newline separating each element.

Parameters:
  • path – path to write file
  • mode – mode to write in, defaults to ‘w’ to overwrite contents
to_list()

Converts sequence to list of elements.

>>> type(seq([]).to_list())
list
>>> type(seq([]))
functional.pipeline.Sequence
>>> seq([1, 2, 3]).to_list()
[1, 2, 3]
Returns:list of elements in sequence
to_set()

Converts sequence to a set of elements.

>>> type(seq([])).to_set()
set
>>> type(seq([]))
functional.pipeline.Sequence
>>> seq([1, 1, 2, 2]).to_set()
{1, 2}

:return:set of elements in sequence

union(other)

New sequence with unique elements from self and other.

>>> seq([1, 1, 2, 3, 3]).union([1, 4, 5])
[1, 2, 3, 4, 5]
Parameters:other – sequence to union with
Returns:union of sequence and other
where(func)

Selects elements where func evaluates to True.

>>> seq([-1, 1, -2, 2]).where(lambda x: x > 0)
[1, 2]
Parameters:func – function to filter on
Returns:filtered sequence
zip(sequence)

Zips the stored sequence with the given sequence.

>>> seq([1, 2, 3]).zip([4, 5, 6])
[(1, 4), (2, 5), (3, 6)]
Parameters:sequence – second sequence to zip
Returns:stored sequence zipped with given sequence
zip_with_index(start=0)

Zips the sequence to its index, with the index being the second element of each tuple.

>>> seq(['a', 'b', 'c']).zip_with_index()
[('a', 0), ('b', 1), ('c', 2)]
Returns:sequence zipped to its index
functional.pipeline._wrap(value)

Wraps the passed value in a Sequence if it is not a primitive. If it is a string argument it is expanded to a list of characters.

>>> _wrap(1)
1
>>> _wrap("abc")
['a', 'b', 'c']
>>> type(_wrap([1, 2]))
functional.pipeline.Sequence
Parameters:value – value to wrap
Returns:wrapped or not wrapped value

functional.lineage

class functional.lineage.Lineage(prior_lineage=None)

Bases: object

Class for tracking the lineage of transformations, and applying them to a given sequence.

__dict__ = dict_proxy({'__module__': 'functional.lineage', '__getitem__': <function __getitem__ at 0x7f52c9f5a500>, 'evaluate': <function evaluate at 0x7f52c9f5a5f0>, '__dict__': <attribute '__dict__' of 'Lineage' objects>, '__len__': <function __len__ at 0x7f52c9f5a488>, 'cache_scan': <function cache_scan at 0x7f52c9f5a668>, 'apply': <function apply at 0x7f52c9f5a578>, '__weakref__': <attribute '__weakref__' of 'Lineage' objects>, '__doc__': '\n Class for tracking the lineage of transformations, and applying them to a given sequence.\n ', '__init__': <function __init__ at 0x7f52c9f5a398>, '__repr__': <function __repr__ at 0x7f52c9f5a410>})
__getitem__(item)
__init__(prior_lineage=None)

Construct an empty lineage if prior_lineage is None or if its not use it as the list of current transformations

Parameters:prior_lineage – Lineage object to inherit
Returns:new Lineage object
__len__()

Number of transformations in lineage

Returns:number of transformations
__module__ = 'functional.lineage'
__repr__()

Returns readable representation of Lineage

Returns:readable Lineage
__weakref__

list of weak references to the object (if defined)

apply(transform)
cache_scan()
evaluate(sequence)

functional.transformations

class functional.transformations.ExecutionStrategies

Bases: object

Enum like object listing the types of execution strategies

PRE_COMPUTE = 0
__dict__ = dict_proxy({'__dict__': <attribute '__dict__' of 'ExecutionStrategies' objects>, '__module__': 'functional.transformations', '__weakref__': <attribute '__weakref__' of 'ExecutionStrategies' objects>, '__doc__': '\n Enum like object listing the types of execution strategies\n ', 'PRE_COMPUTE': 0})
__module__ = 'functional.transformations'
__weakref__

list of weak references to the object (if defined)

class functional.transformations.Transformation(name, function, execution_strategies)

Bases: tuple

__dict__ = dict_proxy({'function': <property object at 0x7f52c9f4f788>, '__module__': 'functional.transformations', '__getstate__': <function __getstate__ at 0x7f52ca1b9d70>, '__new__': <staticmethod object at 0x7f52c9f504e8>, 'execution_strategies': <property object at 0x7f52c9f4f7e0>, '_make': <classmethod object at 0x7f52c9f50478>, '_replace': <function _replace at 0x7f52ca1b9c80>, '__slots__': (), '_asdict': <function _asdict at 0x7f52ca1b9c08>, '__repr__': <function __repr__ at 0x7f52ca1b9b90>, '__dict__': <property object at 0x7f52c9f4f6d8>, '_fields': ('name', 'function', 'execution_strategies'), '__getnewargs__': <function __getnewargs__ at 0x7f52ca1b9cf8>, '__doc__': 'Transformation(name, function, execution_strategies)', 'name': <property object at 0x7f52c9f4f730>})
__getnewargs__()

Return self as a plain tuple. Used by copy and pickle.

__getstate__()

Exclude the OrderedDict from pickling

__module__ = 'functional.transformations'
static __new__(_cls, name, function, execution_strategies)

Create new instance of Transformation(name, function, execution_strategies)

__repr__()

Return a nicely formatted representation string

__slots__ = ()
_asdict()

Return a new OrderedDict which maps field names to their values

_fields = ('name', 'function', 'execution_strategies')
classmethod _make(iterable, new=<built-in method __new__ of type object at 0x9192c0>, len=<built-in function len>)

Make a new Transformation object from a sequence or iterable

_replace(_self, **kwds)

Return a new Transformation object replacing specified fields with new values

execution_strategies

Alias for field number 2

function

Alias for field number 1

name

Alias for field number 0

functional.transformations.difference_t(other)

Transformation for Sequence.difference :param other: sequence to different with :return: transformation

functional.transformations.distinct_by_t(func)

Transformation for Sequence.distinct_by :param func: distinct_by function :return: transformation

functional.transformations.distinct_t()

Transformation for Sequence.distinct :return: transformation

functional.transformations.drop_right_t(n)

Transformation for Sequence.drop_right :param n: number to drop from right :return: transformation

functional.transformations.drop_t(n)

Transformation for Sequence.drop :param n: number to drop from left :return: transformation

functional.transformations.drop_while_t(func)

Transformation for Sequence.drop_while :param func: drops while func is true :return: transformation

functional.transformations.enumerate_t(start)

Transformation for Sequence.enumerate :param start: start index for enumerate :return: transformation

functional.transformations.filter_not_t(func)

Transformation for Sequence.filter_not :param func: filter_not function :return: transformation

functional.transformations.filter_t(func)

Transformation for Sequence.filter :param func: filter function :return: transformation

functional.transformations.flat_map_impl(func, sequence)

Implementation for flat_map_t :param func: function to map :param sequence: sequence to flat_map over :return: flat_map generator

functional.transformations.flat_map_t(func)

Transformation for Sequence.flat_map :param func: function to flat_map :return: transformation

functional.transformations.flatten_t()

Transformation for Sequence.flatten :return: transformation

functional.transformations.group_by_impl(func, sequence)

Implementation for group_by_t :param func: grouping function :param sequence: sequence to group :return: grouped sequence

functional.transformations.group_by_key_impl(sequence)

Implementation for group_by_key_t :param sequence: sequence to group :return: grouped sequence

functional.transformations.group_by_key_t()

Transformation for Sequence.group_by_key :return: transformation

functional.transformations.group_by_t(func)

Transformation for Sequence.group_by :param func: grouping function :return: transformation

functional.transformations.grouped_impl(wrap, size, sequence)

Implementation for grouped_t :param wrap: wrap children values with this :param size: size of groups :param sequence: sequence to group :return: grouped sequence

functional.transformations.grouped_t(wrap, size)

Transformation for Sequence.grouped :param wrap: wrap children values with this :param size: size of groups :return: transformation

functional.transformations.init_t()

Transformation for Sequence.init :return: transformation

functional.transformations.inits_t(wrap)

Transformation for Sequence.inits :param wrap: wrap children values with this :return: transformation

functional.transformations.inner_join_impl(other, sequence)

Implementation for part of join_impl :param other: other sequence to join with :param sequence: first sequence to join with :return: joined sequence

functional.transformations.intersection_t(other)

Transformation for Sequence.intersection :param other: sequence to intersect with :return: transformation

functional.transformations.join_impl(other, join_type, sequence)

Implementation for join_t :param other: other sequence to join with :param join_type: join type (inner, outer, left, right) :param sequence: first sequence to join with :return: joined sequence

functional.transformations.join_t(other, join_type)

Transformation for Sequence.join, Sequence.inner_join, Sequence.outer_join, Sequence.right_join, and Sequence.left_join :param other: other sequence to join with :param join_type: join type from left, right, inner, and outer :return: transformation

functional.transformations.map_t(func)

Transformation for Sequence.map :param func: map function :return: transformation

functional.transformations.name(function)

Retrieve a pretty name for the function :param function: function to get name from :return: pretty name

functional.transformations.order_by_t(func)

Transformation for Sequence.order_by :param func: order_by function :return: transformation

functional.transformations.partition_t(wrap, func)

Transformation for Sequence.partition :param wrap: wrap children values with this :param func: partition function :return: transformation

functional.transformations.reduce_by_key_t(func)

Transformation for Sequence.reduce_by_key :param func: reduce function :return: transformation

functional.transformations.reversed_t()

Transformation for Sequence.reverse :return: transformation

functional.transformations.select_t(func)

Transformation for Sequence.select :param func: select function :return: transformation

functional.transformations.slice_t(start, until)

Transformation for Sequence.slice :param start: start index :param until: until index (does not include element at until) :return: transformation

functional.transformations.sliding_impl(wrap, size, step, sequence)

Implementation for sliding_t :param wrap: wrap children values with this :param size: size of window :param step: step size :param sequence: sequence to create sliding windows from :return: sequence of sliding windows

functional.transformations.sliding_t(wrap, size, step)

Transformation for Sequence.sliding :param wrap: wrap children values with this :param size: size of window :param step: step size :return: transformation

functional.transformations.sorted_t(key=None, reverse=False)

Transformation for Sequence.sorted :param key: key to sort by :param reverse: reverse or not :return: transformation

functional.transformations.symmetric_difference_t(other)

Transformation for Sequence.symmetric_difference :param other: sequence to symmetric_difference with :return: transformation

functional.transformations.tail_t()

Transformation for Sequence.tail :return: transformation

functional.transformations.tails_t(wrap)

Transformation for Sequence.tails :param wrap: wrap children values with this :return: transformation

functional.transformations.take_t(n)

Transformation for Sequence.take :param n: number to take :return: transformation

functional.transformations.take_while_t(func)

Transformation for Sequence.take_while :param func: takes while func is True :return: transformation

functional.transformations.union_t(other)

Transformation for Sequence.union :param other: sequence to union with :return: transformation

functional.transformations.where_t(func)

Transformation for Sequence.where :param func: where function :return: transformation

functional.transformations.zip_t(zip_sequence)

Transformation for Sequence.zip :param zip_sequence: sequence to zip with :return: transformation

functional.transformations.zip_with_index_t(start)

Transformation for Sequence.zip_with_index :return: transformation

functional.util

class functional.util.ReusableFile(path, delimiter=None, mode='r', buffering=-1, encoding=None, errors=None, newline=None)

Bases: object

Class which emulates the builtin file except that calling iter() on it will return separate iterators on different file handlers (which are automatically closed when iteration stops). This is useful for allowing a file object to be iterated over multiple times while keep evaluation lazy.

__dict__ = dict_proxy({'__module__': 'functional.util', '__iter__': <function __iter__ at 0x7f52c9f5aa28>, '__dict__': <attribute '__dict__' of 'ReusableFile' objects>, '__weakref__': <attribute '__weakref__' of 'ReusableFile' objects>, '__doc__': '\n Class which emulates the builtin file except that calling iter() on it will return separate\n iterators on different file handlers (which are automatically closed when iteration stops). This\n is useful for allowing a file object to be iterated over multiple times while keep evaluation\n lazy.\n ', '__init__': <function __init__ at 0x7f52c9f5a9b0>})
__init__(path, delimiter=None, mode='r', buffering=-1, encoding=None, errors=None, newline=None)

Constructor arguments are passed directly to builtins.open :param path: passed to open :param delimiter: passed to open :param mode: passed to open :param buffering: passed to open :param encoding: passed to open :param errors: passed to open :param newline: passed to open :return: ReusableFile from the arguments

__iter__()

Returns a new iterator over the file using the arguments from the constructor. Each call to __iter__ returns a new iterator independent of all others :return: iterator over file

__module__ = 'functional.util'
__weakref__

list of weak references to the object (if defined)

functional.util.identity(arg)

Function which returns the argument. Used as a default lambda function.

>>> obj = object()
>>> obj is identity(obj)
True
Parameters:arg – object to take identity of
Returns:return arg
functional.util.is_iterable(val)

Check if val is not a list, but is a collections.Iterable type. This is used to determine when list() should be called on val

>>> l = [1, 2]
>>> is_iterable(l)
False
>>> is_iterable(iter(l))
True
Parameters:val – value to check
Returns:True if it is not a list, but is a collections.Iterable
functional.util.is_namedtuple(val)

Use Duck Typing to check if val is a named tuple. Checks that val is of type tuple and contains the attribute _fields which is defined for named tuples. :param val: value to check type of :return: True if val is a namedtuple

functional.util.is_primitive(val)

Checks if the passed value is a primitive type.

>>> is_primitive(1)
True
>>> is_primitive("abc")
True
>>> is_primitive(True)
True
>>> is_primitive({})
False
>>> is_primitive([])
False
>>> is_primitive(set([]))
Parameters:val – value to check
Returns:True if value is a primitive, else False