satella.coding.sequences package

Submodules

satella.coding.sequences.average module

class satella.coding.sequences.average.RollingArithmeticAverage(n=100)

Bases: object

A class to implement a rolling arithmetic average over n last entries

Parameters:

n (int) – amount of last entries to count

avg()

Compute current average

Returns:

current average

Raises:

ZeroDivisionError – the average buffer is empty

Return type:

float

clear()

Clear the rolling average buffer

Return type:

None

insert(x)

Add a value to the rolling average, discarding the previous entry if the buffer size is exceeded

Parameters:

x (float) – sample to insert

Return type:

None

n
queue
tot_sum

satella.coding.sequences.choose module

satella.coding.sequences.choose.choose(filter_fun, iterable, check_multiple=False)

Return a single value that exists in given iterable.

Essentially the same as:

>>> next(iter(filter(filter_fun, iterable)))

but raises a different exception if nothing matches (and if there are multiple matches and check_multiple is True). If check_multiple is True this guarantees to exhaust the generator (if passed).

Parameters:
  • filter_fun (Callable[[T], bool]) – function that returns bool on the single value

  • iterable (Union[Iterator[T], Iterable[T]]) – iterable to examine

  • check_multiple (bool) – if True, this will check if there are multiple entries matching filter_fun, and will raise ValueError if so. If True, this will exhaust the iterator. If left at default, False, this may not exhaust the iterator.

Returns:

single element in the iterable that matches given input

Raises:

ValueError – on multiple elements matching (if check_multiple), or none at all

Return type:

T

satella.coding.sequences.choose.choose_one(filter_fun, iterable)

Syntactic sugar for

>>> choose(filter_fun, iterable, check_multiple=True)

This exhausts the iterable.

Parameters:
  • filter_fun (Callable[[T], bool]) – function that returns bool on the single value

  • iterable (Union[Iterator[T], Iterable[T]]) – iterable to examine

Returns:

single element in the iterable that matches given input

Raises:

ValueError – on multiple elements matching, or none at all

Return type:

T

satella.coding.sequences.choose.choose_with_index(filter_fun, iterable)

Return a first found single value that exists in given iterable and filter_fun called on it returns True

Parameters:
  • filter_fun (Callable[[T], bool]) – function that returns bool on the single value

  • iterable (Union[Iterator[T], Iterable[T]]) – iterable to examine

Returns:

a tuple of (element, index)

Raises:

ValueError – element not found

Return type:

Tuple[T, int]

satella.coding.sequences.iterators module

class satella.coding.sequences.iterators.AlreadySeen

Bases: Generic[K]

Class to filter out unique objects. Objects must be hashable, barring that they must be eq-able, however passing it an non-hashable object will result in O(n^2) complexity, as the class uses a list to keep track of the objects.

Usage:

>>> als = AlreadySeen()
>>> for elem in sequence:
>>>     if als.is_unique(elem):
>>>         ... process the element ...
is_unique(key)

Has the element been spotted first time?

Add it to the set.

Parameters:

key (K) – element to check

Returns:

whether the element was seen for the first time

Return type:

bool

set: Union[list, set]
class satella.coding.sequences.iterators.ConstruableIterator(*args, **kwargs)

Bases: object

An iterator that you can attach arbitrary things at the end and consume them during iteration. Eg:

>>> a = ConstruableIterator([1, 2, 3])
>>> for b in a:
>>>   if b % 2 == 0:
>>>       a.add(6)

All arguments you provide to the constructor will be passed to underlying deque

add(t)

Schedule given value to be iterated over after current items

Parameters:

t (T) – value to iterate over

Return type:

None

add_immediate(t)

Schedule given value to be iterated over during the next __next__ call

Parameters:

t (T) – value to iterate over

Return type:

None

add_many(t)

Schedule given values to be iterated over after current items

Parameters:

t (Iterable[T]) – iterable of values

Return type:

None

add_many_immediate(t)

Schedule given values to be iterated over during the next __next__ call

Parameters:

t (Iterable[T]) – values to iterate over

Return type:

None

entries
class satella.coding.sequences.iterators.IteratorListAdapter(iterator)

Bases: object

A wrapper around an iterator that enables it to be processed as a list.

Ie. the generator will now support __contains__, __len__ and __getitem__. If a call to such a method is done, the generator will be unfolded in memory so this might take a ton of memory! You’ve been warned!

Deprecated since version 2.15.7: Use :class:`~satella.coding.sequences.ListWrapperIterator ` instead

Parameters:

iterator (Iterator) – iterator to unfold

iterator
list
pointer
unfolded
class satella.coding.sequences.iterators.ListWrapperIterator(iterator)

Bases: Sequence[T], Iterator[T]

A wrapped for an iterator, enabling using it as a normal list.

The first time this is evaluated, list is populated with elements.

The second time, items are taken from the list.

It never computes more than it needs to.

Essentially a class that lets you reuse one-shot iterators.

This is additionally a generic class.

Variables:

internal_pointer – (int) the number of element this list internally points to

Parameters:

iterator (Union[Iterator[T], Iterable[T]]) –

advance_to_item(i)

Makes the list be at least i in size

Parameters:

i (int) –

Return type:

None

exhaust()

Load all elements of this iterator into memory.

Return type:

None

exhausted
internal_pointer
iterator
list
satella.coding.sequences.iterators.append_sequence(seq, *elems_to_append)

Return an iterator which append elem_to_append to every tuple in seq.

Example:

>>> a = [(1, ), (2, ), (3, )]
>>> assert list(append_sequence(a, 1, 2)) == [(1, 1, 2), (2, 1, 2), (3, 1, 2)]

If every element of seq is not a tuple, it will be cast to one.

Parameters:
  • seq (Iterator[tuple]) – sequence to append

  • elems_to_append – element(s) to append

Returns:

an iterator

Return type:

Iterator[tuple]

satella.coding.sequences.iterators.count(sq, start=None, step=1, start_at=None)

Return a sequence of integers, for each entry in the sequence with provided step.

Essentially the same (if step were ignored) as:

>>> (i for i, x in enumerate(sq, start=start_at))

Deprecated since version 2.14.22: Use start instead

Parameters:
  • sq (Union[Iterator[T], Iterable[T]]) – sequence to enumerate

  • start (Optional[int]) – alias for start_at. Prefer it in regards to start_at. Default is 0

  • step (int) – number to add to internal counter after each element

  • start_at (Optional[int]) – deprecated alias for start

Returns:

an iterator of subsequent integers

Return type:

Iterator[int]

satella.coding.sequences.iterators.enumerate2(iterable, start=0, step=1)

Enumerate with a custom step

Parameters:
  • iterable (Union[Iterator[T], Iterable[T]]) – iterable to enumerate

  • start (int) – value to start at

  • step (int) – step to add during each iteration

Return type:

Iterator[Tuple[int, T]]

satella.coding.sequences.iterators.even(sq)

Return only elements with even indices in this iterable (first element will be returned, as indices are counted from 0)

Parameters:

sq (Union[Iterator[T], Iterable[T]]) –

Return type:

Iterator[T]

satella.coding.sequences.iterators.f_range(*args)

A range() that supports float.

Note that this behaves correctly when given a negative step.

Call either:

>>> f_range(stop)   # will start from 0 and step 1
>>> f_range(start, stop)    # will start from start and continue until the result is gte stop
>>> # will start from start and continue by step until the result is gte stop
>>> f_range(start, stop, step)
Raises:

TypeError – invalid number of arguments

Parameters:

args (float) –

Return type:

Iterator[float]

satella.coding.sequences.iterators.infinite_counter(start_at=0, step=1)

Infinite counter, starting at start_at

Deprecated since version 2.14.22: Use itertools.count instead.

Parameters:
  • start_at (int) – value at which to start counting. It will be yielded as first

  • step (int) – step by which to progress the counter

Return type:

Iterator[int]

satella.coding.sequences.iterators.is_empty(iterable, exhaust=True)

Checks whether an iterator is empty.

This will exhaust the iterator if exhaust is left at default, or True

Parameters:
  • iterable (Union[Iterator[T], Iterable[T]]) – iterator to check

  • exhaust (bool) – if set to False, at most a single element will be consumed from the iterator

Returns:

whether the iterator is empty

Return type:

bool

satella.coding.sequences.iterators.is_instance(classes)
Parameters:

classes (Union[Tuple[type, ...], type]) –

Return type:

Callable[[object], bool]

satella.coding.sequences.iterators.iter_dict_of_list(dct)

Presents a simple way to iterate over a dictionary whose values are lists.

This will return the dictionary key and each of the value contained in the list attached to the key.

Parameters:

dct (Dict[T, List[U]]) –

Return type:

Generator[Tuple[T, U], None, None]

satella.coding.sequences.iterators.iterate_callable(clbl, start_from=0, exc_classes=(<class 'IndexError'>, <class 'ValueError'>))

Given a callable that accepts an integer and returns the n-th entry, iterate over it until it starts to throw some exception.

Parameters:
  • clbl (Callable[[int], V]) – callable to call

  • start_from (int) – number to start from

  • exc_classes – exceptions that being thrown show that the list was exhausted

Returns:

an iterator

Return type:

Iterator[V]

satella.coding.sequences.iterators.length(iterator)

Return the length of an iterator, exhausting it by the way

Parameters:

iterator (Union[Iterator[T], Iterable[T]]) –

Return type:

int

satella.coding.sequences.iterators.map_list(fun, iterable)

A syntactic sugar for

>>> list(map(fun, iterable))
Parameters:
  • fun (Callable) – function to apply

  • iterable (Union[Iterator[T], Iterable[T]]) – iterable to iterate over

Return type:

List

satella.coding.sequences.iterators.n_th(iterator, n=0)

Obtain n-th element (counting from 0) of an iterable

Parameters:
  • iterator (Union[Iterator[T], Iterable[T]]) – iterable to process

  • n (int) – element to return. Note that we’re counting from 0

Raises:

IndexError – iterable was too short

Return type:

T

satella.coding.sequences.iterators.odd(sq)

Return only elements with odd indices in this iterable.

Parameters:

sq (Union[Iterator[T], Iterable[T]]) –

Return type:

Iterator[T]

satella.coding.sequences.iterators.other_sequence_no_longer_than(base_sequence, other_sequence)

Return every item in other_sequence, but limit it’s p_len to that of base_sequence.

If other_sequence is shorter than base_sequence, the shorter one will be returned.

Parameters:
  • base_sequence (Union[Iterator[T], Iterable[T]]) – sequence whose p_len should be taken

  • other_sequence (Union[Iterator[T], Iterable[T]]) – sequence to output values from

Return type:

Iterator[T]

satella.coding.sequences.iterators.shift(iterable_, shift_factor)

Return this sequence, but shifted by factor elements, so that elements will appear sooner by factor.

Eg:

>>> assert list(shift([1,2, 3], 1)) == [2, 3, 1]

However note that this will result in iterators which have negative shift to be readed entirely into memory (converted internally to lists). This can be avoided by passing in a Reversible iterable.

Parameters:
  • iterable – iterable to shift

  • shift_factor (int) – factor by which shift elements.

  • iterable_ (Union[Reversible[T], Iterator[T], Iterable[T]]) –

Returns:

shifted sequence

Return type:

Iterator[T]

satella.coding.sequences.iterators.skip_first(iterator, n)

Skip first n elements from given iterator.

Returned iterator may be empty, if source iterator is shorter or equal to n.

Deprecated since version 2.14.22: Use itertools.islice instead

Parameters:
  • iterator (Union[Iterator[T], Iterable[T]]) –

  • n (int) –

Return type:

Iterator[T]

satella.coding.sequences.iterators.smart_enumerate(iterator, start=0, step=1)

An enumerate that talks pretty with lists of tuples. Consider

>>> a = [(1, 2), (3, 4), (5, 6)]
>>> for i, b in enumerate(a):
>>>     c, d = b
>>>     ...

This function allows you just to write: >>> for i, c, d in enumerate(a): >>> …

Note that elements in your iterable must be either a list of a tuple for that to work, or need to be able to be coerced to a tuple. Otherwise, TypeError will be thrown.

Parameters:
  • iterator (Union[Iterator[T], Iterable[T]]) – iterator to enumerate

  • start (int) – value to start counting at

  • step (int) – step to advance the enumeration with

Raises:

TypeError – could not coerce the elements in your iterable to a tuple

Return type:

Iterator[Tuple]

satella.coding.sequences.iterators.smart_zip(*iterators)

Zip in such a way that resulted tuples are automatically expanded.

Ie:

>>> b = list(smart_zip([(1, 1), (1, 2)], [1, 2]))
>>> assert b == [(1, 1, 1), (1, 2, 2)]

Note that an element of the zipped iterator must be a tuple (ie. isinstance tuple) in order for it to be appended to resulting iterator element!

Deprecated since version Use: the for (a, b), c syntax instead.

Parameters:

iterators (Union[Iterator[T], Iterable[T]]) – list of iterators to zip together

Returns:

an iterator zipping the arguments in a smart way

Return type:

Iterator[Tuple[T, …]]

satella.coding.sequences.iterators.stop_after(iterator, n)

Stop this iterator after returning n elements, even if it’s longer than that.

The resulting iterator may be shorter than n, if the source element is so.

Deprecated since version 2.14.22: Use itertools.islice instead

Parameters:
  • iterator (Union[Iterator[T], Iterable[T]]) – iterator or iterable to examine

  • n (int) – elements to return

Return type:

Iterator[T]

satella.coding.sequences.iterators.take_n(iterator, n, skip=0)

Take (first) n elements of an iterator, or the entire iterator, whichever comes first

Parameters:
  • iterator (Union[Iterator[T], Iterable[T]]) – iterator to take from

  • n (int) – amount of elements to take

  • skip (int) – elements from the start to skip

Returns:

list of p_len n (or shorter)

Return type:

List[T]

satella.coding.sequences.iterators.to_iterator(fun)

Convert function to an iterator. You can replace the following code:

>>> def iterator(x):
>>>     for y in x:
>>>         yield fun(y)

with

>>> @to_iterator
>>> def fun(y):
>>>     ...

and now call fun instead of iterator. fun will accept a single argument - the iterable, and assume that the function you decorate also takes a single argument - the item

satella.coding.sequences.iterators.try_close(iterator)

Try to invoke close() on an iterator. Do nothing if provided iterator doesn’t have a .close() method.

Parameters:

iterator (Iterator) – iterator to close

Return type:

None

satella.coding.sequences.iterators.unique(lst)

Return each element from lst, but return every element only once.

Take care for elements of T to be __eq__-able and hashable!

This will keep internally a set of elements encountered, and skip them if same element appears twice

Parameters:

lst (Union[Iterator[T], Iterable[T]]) – iterable to process

Returns:

a generator yielding unique items from lst

Return type:

Iterator[T]

satella.coding.sequences.iterators.walk(obj, child_getter=<class 'list'>, deep_first=True, leaves_only=False)

Return every node of a nested structure.

Parameters:
  • obj (T) – structure to traverse. This will not appear in generator

  • child_getter (Callable[[T], Optional[List[T]]]) – a callable to return a list of children of T. Should return an empty list or None of there are no more children.

  • deep_first (bool) – if True, deep first will be returned, else it will be breadth first

  • leaves_only (bool) – if True, only leaf nodes (having no children) will be returned

Return type:

Iterator[T]

satella.coding.sequences.iterators.zip_shifted(*args)

Construct an iterator, just like zip but first by cycling it’s elements by it’s shift factor. Elements will be shifted by a certain factor, this means that they will appear earlier.

Example:

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

This will work on arbitrary iterators and iterables.

Shift can be negative, in which case the last elements will appear sooner, eg.

>>> zip_shifted(([1, 2, 3, 4], -1), ([1, 2, 3, 4], 0)) == [(4, 1), (1, 2), (2, 3), (3, 4)]

Same memory considerations as shift() apply.

The resulting iterator will be as long as the shortest sequence.

Deprecated since version 2.14.22: Use zip(shift(…)) instead

Parameters:

args (Union[Iterator[T], Iterable[T], Tuple[Union[Iterator[T], Iterable[T]], int]]) – a tuple with the iterator/iterable and amount of shift. If a non-tuple is given, it is assumed that the shift is zero.

Return type:

Iterator[Tuple[T, …]]

satella.coding.sequences.sequences module

class satella.coding.sequences.sequences.Multirun(sequence, dont_return_list=False)

Bases: object

A class to launch the same operation on the entire sequence.

Consider:

>>> class Counter:
>>>     def __init__(self, value=0):
>>>         self.count = value
>>>     def add(self, v):
>>>         self.count += 1
>>>     def __eq__(self, other):
>>>          return self.count == other.count
>>>     def __iadd__(self, other):
>>>         self.add(other)
>>> a = [Counter(), Counter()]

The following:

>>> for b in a:
>>>     b.add(2)

Can be replaced with

>>> Multirun(a).add(2)

And the following:

>>> for b in a:
>>>     b += 3

With this

>>> b = Mulirun(a)
>>> b += 3

Furthermore note that:

>>> Multirun(a).add(2) == [Counter(2), Counter(2)]
Parameters:
  • sequence (Iterable) – sequence to execute these operations for

  • dont_return_list (bool) – the operation won’t return a list if this is True

dont_return_list
sequence
satella.coding.sequences.sequences.add_next(lst, wrap_over=False, skip_last=False)

Yields a 2-tuple of given iterable, presenting the next element as second element of the tuple.

The last element will be the last element alongside with a None, if wrap_over is False, or the first element if wrap_over was True

Example:

>>> list(add_next([1, 2, 3, 4, 5])) == [(1, 2), (2, 3), (3, 4), (4, 5), (5, None)]
>>> list(add_next([1, 2, 3, 4, 5], True)) == [(1, 2), (2, 3), (3, 4), (4, 5), (5, 1)]
Parameters:
  • lst (Union[Iterator[T], Iterable[T]]) – iterable to iterate over

  • wrap_over (bool) – whether to attach the first element to the pair of the last element instead of None

  • skip_last (bool) – if this is True, then last element, alongside with a None, won’t be output

Return type:

Iterator[Tuple[T, Optional[T]]]

satella.coding.sequences.sequences.filter_out_false(y)

Return all elements, as a list, that are True

Parameters:

y (Sequence[T]) – a sequence of items

Returns:

a list of all subelements, in order, that are not None

Return type:

List[T]

satella.coding.sequences.sequences.filter_out_nones(y)

Return all elements, as a list, that are not None

Parameters:

y (Sequence[T]) – a sequence of items

Returns:

a list of all subelements, in order, that are not None

Return type:

List[T]

satella.coding.sequences.sequences.group_quantity(length, seq)

Slice an iterable into lists containing at most len entries.

Eg.

>>> assert list(group_quantity(3, [1, 2, 3, 4, 5, 6, 7, 8, 9, 10])) == [[1, 2, 3], [4, 5, 6],
>>>                                                                     [7, 8, 9], [10]]

This correctly detects sequences, and uses an optimized variant via slicing if a sequence is passed.

You can safely pass ranges

Parameters:
  • length (int) – p_len for the returning sequences

  • seq (Union[Iterator[T], Iterable[T]]) – sequence to split

Return type:

Iterator[List[T]]

satella.coding.sequences.sequences.half_cartesian(seq, include_same_pairs=True)

Generate half of the Cartesian product of both sequences.

Useful when you have a commutative operation that you’d like to execute on both elements (eg. checking for collisions).

Example:

>>> list(half_cartesian([1, 2, 3], [1, 2, 3])) ==     >>>     [(1, 1), (1, 2), (1, 3), (2, 2), (2, 3), (3, 3)]
Parameters:
  • seq (Iterable[T]) – The sequence

  • include_same_pairs (bool) – if True, then pairs returning two of the same objects will be returned. For example, if False, the following will be true:

Return type:

Iterator[Tuple[T, T]]

>>> list(half_cartesian([1, 2, 3], [1, 2, 3], include_same_pairs=False)) ==     >>>     [(1, 2), (1, 3), (2, 3)]
satella.coding.sequences.sequences.index_of(predicate, seq)

Return an index of first met element that calling predicate on it returns True

Parameters:
  • predicate (Callable[[T], bool]) – predicate to apply

  • seq (Sequence[T]) – sequence to examine

Returns:

index of the element

Raises:

ValueError – if no element found

Return type:

int

satella.coding.sequences.sequences.index_of_max(seq)

Return the index of the maximum element

Parameters:

seq (Sequence[T]) – sequence to examine

Returns:

index of the maximum element

Raises:

ValueError – sequence was empty

Return type:

int

satella.coding.sequences.sequences.infinite_iterator(returns=None, return_factory=None)

Return an infinite number of objects.

Parameters:
  • returns (Optional[T]) – object to return. Note that this will be this very object, it will not be copied.

  • return_factory (Optional[Callable[[], T]]) – a callable that takes 0 args and returns an element to return.

Returns:

an infinite iterator of provided values

Return type:

Iterator[T]

satella.coding.sequences.sequences.is_last(lst)

Return every element of the list, alongside a flag telling is this the last element.

Use like:

>>> for is_last, element in is_last(my_list):
>>>     if is_last:
>>>         ...
Parameters:

lst (Union[Iterator[T], Iterable[T]]) – list to iterate thru

Returns:

a p_gen returning (bool, T)

Return type:

Iterator[Tuple[bool, T]]

Note that this returns a nice, O(1) iterator.

satella.coding.sequences.sequences.make_list(element, n, deep_copy=False)

Make a list consisting of n times element. Element will be copied via copy.copy before adding to list.

Parameters:
  • element (T) – element

  • n (int) – times to repeat the element

  • deep_copy (bool) – whether to use copy.deepcopy instead of copy.copy

Returns:

list of length n

Return type:

List[T]

Module contents

class satella.coding.sequences.AlreadySeen

Bases: Generic[K]

Class to filter out unique objects. Objects must be hashable, barring that they must be eq-able, however passing it an non-hashable object will result in O(n^2) complexity, as the class uses a list to keep track of the objects.

Usage:

>>> als = AlreadySeen()
>>> for elem in sequence:
>>>     if als.is_unique(elem):
>>>         ... process the element ...
is_unique(key)

Has the element been spotted first time?

Add it to the set.

Parameters:

key (K) – element to check

Returns:

whether the element was seen for the first time

Return type:

bool

set: Union[list, set]
class satella.coding.sequences.ConstruableIterator(*args, **kwargs)

Bases: object

An iterator that you can attach arbitrary things at the end and consume them during iteration. Eg:

>>> a = ConstruableIterator([1, 2, 3])
>>> for b in a:
>>>   if b % 2 == 0:
>>>       a.add(6)

All arguments you provide to the constructor will be passed to underlying deque

add(t)

Schedule given value to be iterated over after current items

Parameters:

t (T) – value to iterate over

Return type:

None

add_immediate(t)

Schedule given value to be iterated over during the next __next__ call

Parameters:

t (T) – value to iterate over

Return type:

None

add_many(t)

Schedule given values to be iterated over after current items

Parameters:

t (Iterable[T]) – iterable of values

Return type:

None

add_many_immediate(t)

Schedule given values to be iterated over during the next __next__ call

Parameters:

t (Iterable[T]) – values to iterate over

Return type:

None

entries
class satella.coding.sequences.IteratorListAdapter(iterator)

Bases: object

A wrapper around an iterator that enables it to be processed as a list.

Ie. the generator will now support __contains__, __len__ and __getitem__. If a call to such a method is done, the generator will be unfolded in memory so this might take a ton of memory! You’ve been warned!

Deprecated since version 2.15.7: Use :class:`~satella.coding.sequences.ListWrapperIterator ` instead

Parameters:

iterator (Iterator) – iterator to unfold

iterator
list
pointer
unfolded
class satella.coding.sequences.ListWrapperIterator(iterator)

Bases: Sequence[T], Iterator[T]

A wrapped for an iterator, enabling using it as a normal list.

The first time this is evaluated, list is populated with elements.

The second time, items are taken from the list.

It never computes more than it needs to.

Essentially a class that lets you reuse one-shot iterators.

This is additionally a generic class.

Variables:

internal_pointer – (int) the number of element this list internally points to

Parameters:

iterator (Union[Iterator[T], Iterable[T]]) –

advance_to_item(i)

Makes the list be at least i in size

Parameters:

i (int) –

Return type:

None

exhaust()

Load all elements of this iterator into memory.

Return type:

None

exhausted
internal_pointer
iterator
list
class satella.coding.sequences.Multirun(sequence, dont_return_list=False)

Bases: object

A class to launch the same operation on the entire sequence.

Consider:

>>> class Counter:
>>>     def __init__(self, value=0):
>>>         self.count = value
>>>     def add(self, v):
>>>         self.count += 1
>>>     def __eq__(self, other):
>>>          return self.count == other.count
>>>     def __iadd__(self, other):
>>>         self.add(other)
>>> a = [Counter(), Counter()]

The following:

>>> for b in a:
>>>     b.add(2)

Can be replaced with

>>> Multirun(a).add(2)

And the following:

>>> for b in a:
>>>     b += 3

With this

>>> b = Mulirun(a)
>>> b += 3

Furthermore note that:

>>> Multirun(a).add(2) == [Counter(2), Counter(2)]
Parameters:
  • sequence (Iterable) – sequence to execute these operations for

  • dont_return_list (bool) – the operation won’t return a list if this is True

dont_return_list
sequence
class satella.coding.sequences.RollingArithmeticAverage(n=100)

Bases: object

A class to implement a rolling arithmetic average over n last entries

Parameters:

n (int) – amount of last entries to count

avg()

Compute current average

Returns:

current average

Raises:

ZeroDivisionError – the average buffer is empty

Return type:

float

clear()

Clear the rolling average buffer

Return type:

None

insert(x)

Add a value to the rolling average, discarding the previous entry if the buffer size is exceeded

Parameters:

x (float) – sample to insert

Return type:

None

n
queue
tot_sum
satella.coding.sequences.add_next(lst, wrap_over=False, skip_last=False)

Yields a 2-tuple of given iterable, presenting the next element as second element of the tuple.

The last element will be the last element alongside with a None, if wrap_over is False, or the first element if wrap_over was True

Example:

>>> list(add_next([1, 2, 3, 4, 5])) == [(1, 2), (2, 3), (3, 4), (4, 5), (5, None)]
>>> list(add_next([1, 2, 3, 4, 5], True)) == [(1, 2), (2, 3), (3, 4), (4, 5), (5, 1)]
Parameters:
  • lst (Union[Iterator[T], Iterable[T]]) – iterable to iterate over

  • wrap_over (bool) – whether to attach the first element to the pair of the last element instead of None

  • skip_last (bool) – if this is True, then last element, alongside with a None, won’t be output

Return type:

Iterator[Tuple[T, Optional[T]]]

satella.coding.sequences.append_sequence(seq, *elems_to_append)

Return an iterator which append elem_to_append to every tuple in seq.

Example:

>>> a = [(1, ), (2, ), (3, )]
>>> assert list(append_sequence(a, 1, 2)) == [(1, 1, 2), (2, 1, 2), (3, 1, 2)]

If every element of seq is not a tuple, it will be cast to one.

Parameters:
  • seq (Iterator[tuple]) – sequence to append

  • elems_to_append – element(s) to append

Returns:

an iterator

Return type:

Iterator[tuple]

satella.coding.sequences.choose(filter_fun, iterable, check_multiple=False)

Return a single value that exists in given iterable.

Essentially the same as:

>>> next(iter(filter(filter_fun, iterable)))

but raises a different exception if nothing matches (and if there are multiple matches and check_multiple is True). If check_multiple is True this guarantees to exhaust the generator (if passed).

Parameters:
  • filter_fun (Callable[[T], bool]) – function that returns bool on the single value

  • iterable (Union[Iterator[T], Iterable[T]]) – iterable to examine

  • check_multiple (bool) – if True, this will check if there are multiple entries matching filter_fun, and will raise ValueError if so. If True, this will exhaust the iterator. If left at default, False, this may not exhaust the iterator.

Returns:

single element in the iterable that matches given input

Raises:

ValueError – on multiple elements matching (if check_multiple), or none at all

Return type:

T

satella.coding.sequences.choose_one(filter_fun, iterable)

Syntactic sugar for

>>> choose(filter_fun, iterable, check_multiple=True)

This exhausts the iterable.

Parameters:
  • filter_fun (Callable[[T], bool]) – function that returns bool on the single value

  • iterable (Union[Iterator[T], Iterable[T]]) – iterable to examine

Returns:

single element in the iterable that matches given input

Raises:

ValueError – on multiple elements matching, or none at all

Return type:

T

satella.coding.sequences.choose_with_index(filter_fun, iterable)

Return a first found single value that exists in given iterable and filter_fun called on it returns True

Parameters:
  • filter_fun (Callable[[T], bool]) – function that returns bool on the single value

  • iterable (Union[Iterator[T], Iterable[T]]) – iterable to examine

Returns:

a tuple of (element, index)

Raises:

ValueError – element not found

Return type:

Tuple[T, int]

satella.coding.sequences.count(sq, start=None, step=1, start_at=None)

Return a sequence of integers, for each entry in the sequence with provided step.

Essentially the same (if step were ignored) as:

>>> (i for i, x in enumerate(sq, start=start_at))

Deprecated since version 2.14.22: Use start instead

Parameters:
  • sq (Union[Iterator[T], Iterable[T]]) – sequence to enumerate

  • start (Optional[int]) – alias for start_at. Prefer it in regards to start_at. Default is 0

  • step (int) – number to add to internal counter after each element

  • start_at (Optional[int]) – deprecated alias for start

Returns:

an iterator of subsequent integers

Return type:

Iterator[int]

satella.coding.sequences.enumerate2(iterable, start=0, step=1)

Enumerate with a custom step

Parameters:
  • iterable (Union[Iterator[T], Iterable[T]]) – iterable to enumerate

  • start (int) – value to start at

  • step (int) – step to add during each iteration

Return type:

Iterator[Tuple[int, T]]

satella.coding.sequences.even(sq)

Return only elements with even indices in this iterable (first element will be returned, as indices are counted from 0)

Parameters:

sq (Union[Iterator[T], Iterable[T]]) –

Return type:

Iterator[T]

satella.coding.sequences.f_range(*args)

A range() that supports float.

Note that this behaves correctly when given a negative step.

Call either:

>>> f_range(stop)   # will start from 0 and step 1
>>> f_range(start, stop)    # will start from start and continue until the result is gte stop
>>> # will start from start and continue by step until the result is gte stop
>>> f_range(start, stop, step)
Raises:

TypeError – invalid number of arguments

Parameters:

args (float) –

Return type:

Iterator[float]

satella.coding.sequences.filter_out_false(y)

Return all elements, as a list, that are True

Parameters:

y (Sequence[T]) – a sequence of items

Returns:

a list of all subelements, in order, that are not None

Return type:

List[T]

satella.coding.sequences.filter_out_nones(y)

Return all elements, as a list, that are not None

Parameters:

y (Sequence[T]) – a sequence of items

Returns:

a list of all subelements, in order, that are not None

Return type:

List[T]

satella.coding.sequences.group_quantity(length, seq)

Slice an iterable into lists containing at most len entries.

Eg.

>>> assert list(group_quantity(3, [1, 2, 3, 4, 5, 6, 7, 8, 9, 10])) == [[1, 2, 3], [4, 5, 6],
>>>                                                                     [7, 8, 9], [10]]

This correctly detects sequences, and uses an optimized variant via slicing if a sequence is passed.

You can safely pass ranges

Parameters:
  • length (int) – p_len for the returning sequences

  • seq (Union[Iterator[T], Iterable[T]]) – sequence to split

Return type:

Iterator[List[T]]

satella.coding.sequences.half_cartesian(seq, include_same_pairs=True)

Generate half of the Cartesian product of both sequences.

Useful when you have a commutative operation that you’d like to execute on both elements (eg. checking for collisions).

Example:

>>> list(half_cartesian([1, 2, 3], [1, 2, 3])) ==     >>>     [(1, 1), (1, 2), (1, 3), (2, 2), (2, 3), (3, 3)]
Parameters:
  • seq (Iterable[T]) – The sequence

  • include_same_pairs (bool) – if True, then pairs returning two of the same objects will be returned. For example, if False, the following will be true:

Return type:

Iterator[Tuple[T, T]]

>>> list(half_cartesian([1, 2, 3], [1, 2, 3], include_same_pairs=False)) ==     >>>     [(1, 2), (1, 3), (2, 3)]
satella.coding.sequences.index_of(predicate, seq)

Return an index of first met element that calling predicate on it returns True

Parameters:
  • predicate (Callable[[T], bool]) – predicate to apply

  • seq (Sequence[T]) – sequence to examine

Returns:

index of the element

Raises:

ValueError – if no element found

Return type:

int

satella.coding.sequences.index_of_max(seq)

Return the index of the maximum element

Parameters:

seq (Sequence[T]) – sequence to examine

Returns:

index of the maximum element

Raises:

ValueError – sequence was empty

Return type:

int

satella.coding.sequences.infinite_counter(start_at=0, step=1)

Infinite counter, starting at start_at

Deprecated since version 2.14.22: Use itertools.count instead.

Parameters:
  • start_at (int) – value at which to start counting. It will be yielded as first

  • step (int) – step by which to progress the counter

Return type:

Iterator[int]

satella.coding.sequences.infinite_iterator(returns=None, return_factory=None)

Return an infinite number of objects.

Parameters:
  • returns (Optional[T]) – object to return. Note that this will be this very object, it will not be copied.

  • return_factory (Optional[Callable[[], T]]) – a callable that takes 0 args and returns an element to return.

Returns:

an infinite iterator of provided values

Return type:

Iterator[T]

satella.coding.sequences.is_empty(iterable, exhaust=True)

Checks whether an iterator is empty.

This will exhaust the iterator if exhaust is left at default, or True

Parameters:
  • iterable (Union[Iterator[T], Iterable[T]]) – iterator to check

  • exhaust (bool) – if set to False, at most a single element will be consumed from the iterator

Returns:

whether the iterator is empty

Return type:

bool

satella.coding.sequences.is_instance(classes)
Parameters:

classes (Union[Tuple[type, ...], type]) –

Return type:

Callable[[object], bool]

satella.coding.sequences.is_last(lst)

Return every element of the list, alongside a flag telling is this the last element.

Use like:

>>> for is_last, element in is_last(my_list):
>>>     if is_last:
>>>         ...
Parameters:

lst (Union[Iterator[T], Iterable[T]]) – list to iterate thru

Returns:

a p_gen returning (bool, T)

Return type:

Iterator[Tuple[bool, T]]

Note that this returns a nice, O(1) iterator.

satella.coding.sequences.iter_dict_of_list(dct)

Presents a simple way to iterate over a dictionary whose values are lists.

This will return the dictionary key and each of the value contained in the list attached to the key.

Parameters:

dct (Dict[T, List[U]]) –

Return type:

Generator[Tuple[T, U], None, None]

satella.coding.sequences.iterate_callable(clbl, start_from=0, exc_classes=(<class 'IndexError'>, <class 'ValueError'>))

Given a callable that accepts an integer and returns the n-th entry, iterate over it until it starts to throw some exception.

Parameters:
  • clbl (Callable[[int], V]) – callable to call

  • start_from (int) – number to start from

  • exc_classes – exceptions that being thrown show that the list was exhausted

Returns:

an iterator

Return type:

Iterator[V]

satella.coding.sequences.length(iterator)

Return the length of an iterator, exhausting it by the way

Parameters:

iterator (Union[Iterator[T], Iterable[T]]) –

Return type:

int

satella.coding.sequences.make_list(element, n, deep_copy=False)

Make a list consisting of n times element. Element will be copied via copy.copy before adding to list.

Parameters:
  • element (T) – element

  • n (int) – times to repeat the element

  • deep_copy (bool) – whether to use copy.deepcopy instead of copy.copy

Returns:

list of length n

Return type:

List[T]

satella.coding.sequences.map_list(fun, iterable)

A syntactic sugar for

>>> list(map(fun, iterable))
Parameters:
  • fun (Callable) – function to apply

  • iterable (Union[Iterator[T], Iterable[T]]) – iterable to iterate over

Return type:

List

satella.coding.sequences.n_th(iterator, n=0)

Obtain n-th element (counting from 0) of an iterable

Parameters:
  • iterator (Union[Iterator[T], Iterable[T]]) – iterable to process

  • n (int) – element to return. Note that we’re counting from 0

Raises:

IndexError – iterable was too short

Return type:

T

satella.coding.sequences.odd(sq)

Return only elements with odd indices in this iterable.

Parameters:

sq (Union[Iterator[T], Iterable[T]]) –

Return type:

Iterator[T]

satella.coding.sequences.other_sequence_no_longer_than(base_sequence, other_sequence)

Return every item in other_sequence, but limit it’s p_len to that of base_sequence.

If other_sequence is shorter than base_sequence, the shorter one will be returned.

Parameters:
  • base_sequence (Union[Iterator[T], Iterable[T]]) – sequence whose p_len should be taken

  • other_sequence (Union[Iterator[T], Iterable[T]]) – sequence to output values from

Return type:

Iterator[T]

satella.coding.sequences.shift(iterable_, shift_factor)

Return this sequence, but shifted by factor elements, so that elements will appear sooner by factor.

Eg:

>>> assert list(shift([1,2, 3], 1)) == [2, 3, 1]

However note that this will result in iterators which have negative shift to be readed entirely into memory (converted internally to lists). This can be avoided by passing in a Reversible iterable.

Parameters:
  • iterable – iterable to shift

  • shift_factor (int) – factor by which shift elements.

  • iterable_ (Union[Reversible[T], Iterator[T], Iterable[T]]) –

Returns:

shifted sequence

Return type:

Iterator[T]

satella.coding.sequences.skip_first(iterator, n)

Skip first n elements from given iterator.

Returned iterator may be empty, if source iterator is shorter or equal to n.

Deprecated since version 2.14.22: Use itertools.islice instead

Parameters:
  • iterator (Union[Iterator[T], Iterable[T]]) –

  • n (int) –

Return type:

Iterator[T]

satella.coding.sequences.smart_enumerate(iterator, start=0, step=1)

An enumerate that talks pretty with lists of tuples. Consider

>>> a = [(1, 2), (3, 4), (5, 6)]
>>> for i, b in enumerate(a):
>>>     c, d = b
>>>     ...

This function allows you just to write: >>> for i, c, d in enumerate(a): >>> …

Note that elements in your iterable must be either a list of a tuple for that to work, or need to be able to be coerced to a tuple. Otherwise, TypeError will be thrown.

Parameters:
  • iterator (Union[Iterator[T], Iterable[T]]) – iterator to enumerate

  • start (int) – value to start counting at

  • step (int) – step to advance the enumeration with

Raises:

TypeError – could not coerce the elements in your iterable to a tuple

Return type:

Iterator[Tuple]

satella.coding.sequences.smart_zip(*iterators)

Zip in such a way that resulted tuples are automatically expanded.

Ie:

>>> b = list(smart_zip([(1, 1), (1, 2)], [1, 2]))
>>> assert b == [(1, 1, 1), (1, 2, 2)]

Note that an element of the zipped iterator must be a tuple (ie. isinstance tuple) in order for it to be appended to resulting iterator element!

Deprecated since version Use: the for (a, b), c syntax instead.

Parameters:

iterators (Union[Iterator[T], Iterable[T]]) – list of iterators to zip together

Returns:

an iterator zipping the arguments in a smart way

Return type:

Iterator[Tuple[T, …]]

satella.coding.sequences.stop_after(iterator, n)

Stop this iterator after returning n elements, even if it’s longer than that.

The resulting iterator may be shorter than n, if the source element is so.

Deprecated since version 2.14.22: Use itertools.islice instead

Parameters:
  • iterator (Union[Iterator[T], Iterable[T]]) – iterator or iterable to examine

  • n (int) – elements to return

Return type:

Iterator[T]

satella.coding.sequences.take_n(iterator, n, skip=0)

Take (first) n elements of an iterator, or the entire iterator, whichever comes first

Parameters:
  • iterator (Union[Iterator[T], Iterable[T]]) – iterator to take from

  • n (int) – amount of elements to take

  • skip (int) – elements from the start to skip

Returns:

list of p_len n (or shorter)

Return type:

List[T]

satella.coding.sequences.to_iterator(fun)

Convert function to an iterator. You can replace the following code:

>>> def iterator(x):
>>>     for y in x:
>>>         yield fun(y)

with

>>> @to_iterator
>>> def fun(y):
>>>     ...

and now call fun instead of iterator. fun will accept a single argument - the iterable, and assume that the function you decorate also takes a single argument - the item

satella.coding.sequences.try_close(iterator)

Try to invoke close() on an iterator. Do nothing if provided iterator doesn’t have a .close() method.

Parameters:

iterator (Iterator) – iterator to close

Return type:

None

satella.coding.sequences.unique(lst)

Return each element from lst, but return every element only once.

Take care for elements of T to be __eq__-able and hashable!

This will keep internally a set of elements encountered, and skip them if same element appears twice

Parameters:

lst (Union[Iterator[T], Iterable[T]]) – iterable to process

Returns:

a generator yielding unique items from lst

Return type:

Iterator[T]

satella.coding.sequences.walk(obj, child_getter=<class 'list'>, deep_first=True, leaves_only=False)

Return every node of a nested structure.

Parameters:
  • obj (T) – structure to traverse. This will not appear in generator

  • child_getter (Callable[[T], Optional[List[T]]]) – a callable to return a list of children of T. Should return an empty list or None of there are no more children.

  • deep_first (bool) – if True, deep first will be returned, else it will be breadth first

  • leaves_only (bool) – if True, only leaf nodes (having no children) will be returned

Return type:

Iterator[T]

satella.coding.sequences.zip_shifted(*args)

Construct an iterator, just like zip but first by cycling it’s elements by it’s shift factor. Elements will be shifted by a certain factor, this means that they will appear earlier.

Example:

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

This will work on arbitrary iterators and iterables.

Shift can be negative, in which case the last elements will appear sooner, eg.

>>> zip_shifted(([1, 2, 3, 4], -1), ([1, 2, 3, 4], 0)) == [(4, 1), (1, 2), (2, 3), (3, 4)]

Same memory considerations as shift() apply.

The resulting iterator will be as long as the shortest sequence.

Deprecated since version 2.14.22: Use zip(shift(…)) instead

Parameters:

args (Union[Iterator[T], Iterable[T], Tuple[Union[Iterator[T], Iterable[T]], int]]) – a tuple with the iterator/iterable and amount of shift. If a non-tuple is given, it is assumed that the shift is zero.

Return type:

Iterator[Tuple[T, …]]