Subset of set designed to conveniently hold sets of integers. It creates them from, and displays them as, integer spans (e.g. 1-3,14,29,92-97). When iterating, pop()-ing an item, or converting to a list, intspan behaves as if it were an ordered collection.
The main draw is that this provides a convenient way to specify ranges--for example, ranges of rows to be processed in a spreadsheet.
from intspan import intspan s = intspan('1-3,14,29,92-97') s.discard('2,13,92') print s
for n in intspan('1-3,5'): print n # Python 2
1 2 3 5
intspan piggybacks Python's set, so it stores every integer individually. Unlike Perl's Set::IntSpan it is not optimized for long contiguous runs. For sets of several hundred or thousand members, you will probably never notice the difference.
On the other hand, if you're doing lots of processing of large sets (e.g. with 100,000 or more elements), or doing lots of set operations on them (e.g. union, intersection), a data structure based on lists of ranges, run length encoding, or Judy arrays would probably perform / scale better.
There are several modules you might want to consider as alternatives or supplements. AFAIK, none of them provide the convenient integer span specification that intspan does, but they have other virtues:
- intspan methods and operations such as add() discard(), and >= take integer span strings, lists, and sets as arguments, changing facilities that used to take only one item into onces that take multiples, inlcuding arguments that are technically string specifications rather than proper intspan objects.
- String representation based on Jeff Mercado's concise answer to this StackOverflow question. Thank you, Jeff!
- Automated multi-version testing managed with the wonderful pytest and tox. Successfully packaged for, and tested against, all late-model verions of Python: 2.6, 2.7, 3.2, and 3.3, as well as PyPy 1.9 (based on 2.7.2).
- The author, Jonathan Eunice or @jeunice on Twitter welcomes your comments and suggestions.
To install the latest version:
pip install -U intspan
To easy_install under a specific Python version (3.3 in this example):
python3.3 -m easy_install --upgrade intspan
(You may need to prefix these with "sudo " to authorize installation.)