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Compress lists of integers to range objects

Project description

Project Status: Active — The project has reached a stable, usable state and is being actively developed. CI Status https://codecov.io/gh/jwodder/derange/branch/master/graph/badge.svg https://img.shields.io/pypi/pyversions/derange.svg MIT License

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Do you have a list of integers? Do you want to know what ranges of consecutive values the list covers? Do you need to solve a gaps and islands problem outside of SQL? Maybe you have a list of dates and need to find the longest streak of consecutive days on which something happened. No? Why not? Well, either way, the derange module is here for you, ready to solve all these problems and a couple more.

Installation

derange requires Python 3.6 or higher. Just use pip for Python 3 (You have pip, right?) to install:

python3 -m pip install derange

Examples

Condense commit years obtained from git log or the like into range objects:

>>> import derange
>>> derange.derange([2015, 2015, 2015, 2014, 2014, 2011, 2010, 2010, 2009, 2009])
[range(2009, 2012), range(2014, 2016)]

If the input is already sorted, you can condense it slightly faster with derange_sorted():

>>> derange.derange_sorted([2009, 2009, 2010, 2010, 2011, 2014, 2014, 2015, 2015, 2015])
[range(2009, 2012), range(2014, 2016)]

Organize non-integer values into closed intervals (represented as pairs of endpoints) with deinterval():

>>> import datetime
>>> # deinterval() requires a callable for determining when two values are "adjacent":
>>> def within_24_hours(a,b):
...     return abs(a-b) <= datetime.timedelta(hours=24)
...
>>> timestamps = [
...     datetime.datetime(2017, 11, 2, 12, 0),
...     datetime.datetime(2017, 11, 3, 11, 0),
...     datetime.datetime(2017, 11, 4, 10, 0),
...     datetime.datetime(2017, 11, 5,  9, 0),
...     datetime.datetime(2017, 11, 6,  9, 0),
...     datetime.datetime(2017, 11, 7, 10, 0),
... ]
>>> derange.deinterval(within_24_hours, timestamps)
[(datetime.datetime(2017, 11, 2, 12, 0), datetime.datetime(2017, 11, 6, 9, 0)), (datetime.datetime(2017, 11, 7, 10, 0), datetime.datetime(2017, 11, 7, 10, 0))]

… which also has a deinterval_sorted() variant:

>>> derange.deinterval_sorted(within_24_hours, timestamps)
[(datetime.datetime(2017, 11, 2, 12, 0), datetime.datetime(2017, 11, 6, 9, 0)), (datetime.datetime(2017, 11, 7, 10, 0), datetime.datetime(2017, 11, 7, 10, 0))]
>>> derange.deinterval_sorted(within_24_hours, reversed(timestamps))
Traceback (most recent call last):
    ...
ValueError: sequence not in ascending order

API

derange.derange(iterable: Iterable[int]) -> List[range]

Convert a sequence of integers to a minimal list of range objects that together contain all of the input elements.

Output is in strictly ascending order. Input need not be in order (but see also derange_sorted()). Duplicate input values are ignored.

derange.derange_sorted(iterable: Iterable[int]) -> List[range]

Convert a non-decreasing sequence of integers to a minimal list of range objects that together contain all of the input elements. This is faster than derange() but only accepts sorted input.

derange.deinterval(
    adjacent: Callable[[T,T], bool],
    iterable: Iterable[T],
) -> List[Tuple[T,T]]

Convert a sequence of totally-ordered values to a minimal list of closed intervals (represented as pairs of endpoints) that together contain all of the input elements. This is a generalization of derange() for arbitrary types.

Two input values will be placed in the same interval iff they are directly adjacent or there exists a chain of adjacent input values connecting them, where adjacency is defined by the given adjacent callable.

adjacent will be called with two elements of iterable at a time to test whether they should be placed in the same interval. The binary relation implied by adjacent must be reflexive and symmetric, and for all x < y < z, if adjacent(x, z) is true, then both adjacent(x, y) and adjacent(y, z) must also be true.

Output is in strictly ascending order. Input need not be in order (but see also deinterval_sorted()). Duplicate input values are ignored.

Note that, unlike with range objects, intervals returned from deinterval() contain their upper bounds.

derange.deinterval_sorted(
    adjacent: Callable[[T,T], bool],
    iterable: Iterable[T],
) -> List[Tuple[T,T]]

Convert a non-decreasing sequence of totally-ordered values to a minimal list of closed intervals that together contain all of the input elements. This is faster than deinterval() but only accepts sorted input.

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