A collection holds items that all have a single common numerical component, whose value differs between each item.

Each collection comprises three main attributes:

  • head - The common leading part of each item.
  • tail - The common trailing part of each item.
  • padding - The width of the index (to be padded to with zeros).

Given items such as:

  • file.0001.jpg
  • file.0002.jpg

The head would be file., the tail .jpg and the padding 4.


If the numerical component is unpadded then the padding would be 0 and a variable index width supported.

A collection can be manually created using the Collection class:

>>> import clique
>>> collection = clique.Collection(head='file.', tail='.jpg', padding=4)

Adding & Removing Items

Items can then be added to the collection:

>>> collection.add('file.0001.jpg')

If an item does not match the collection’s expression a CollectionError is raised:

>>> collection.add('file.0001.dpx')
CollectionError: Item does not match collection expression.

Whether an item matches the collection expression can be tested ahead of time if desired using match():

>>> print collection.match('file.0002.jpg')
<_sre.SRE_Match object at 0x0000000003710D78>
>>> print collection.match('file.0002.dpx')

To remove an item:

>>> collection.remove('file.0001.jpg')

If the item is not present, a CollectionError is raised:

>>> collection.remove('file.0001.jpg')
CollectionError: Item not present in collection.

Accessing Items

To access items in the collection, iterate over it:

>>> collection.add('file.0001.jpg')
>>> collection.add('file.0002.jpg')
>>> for item in collection:
...     print item


A collection may be sparse and so is not directly indexable. If you need to access an item by index, convert the collection to a list:

>>> print list(collection)[-1]

Manipulating Indexes

Internally, Clique does not store the items directly, but rather just the properties to recreate the items (head, tail, padding). In addition it holds a sorted set of indexes present in the collection.

This set of indexes can be manipulated directly to perform the equivalent of adding and removing items (perhaps in bulk).

>>> print collection.indexes
[1, 2]
>>> collection.indexes.update([2, 3, 4])
>>> for item in collection:
...     print item


It is not possible to assign a new index set directly:

>>> collection.indexes = set([1, 2, 3])
AttributeError: Cannot set attribute defined as unsettable.

Instead, first clear and update the set as required:

>>> collection.indexes.clear()
>>> collection.indexes.update(set([1, 2, 3])


It is useful to express a collection as a string that represents the collection expression and ranges in a standard way. Clique supports basic formatting of a collection through its format() method:

>>> collection = clique.Collection('file.', '.jpg', 4, indexes=set([1, 2]))
>>> print collection.format()
file.%04d.jpg [1-2]

The format() method can be passed an alternative pattern if required:

>>> print collection.format('{head}[index]{tail}')

The passed pattern should match the formatting rules of Python’s standard string formatter and will have the following keyword variables available to it:

  • :term:`head` - Common leading part of the collection.
  • :term:`tail` - Common trailing part of the collection.
  • :term:`padding` - Padding value in %0d format.
  • range - Total range in the form start-end
  • ranges - Comma separated ranges of indexes.
  • holes - Comma separated ranges of missing indexes.


Clique makes it easy to get further information about the structure of a collection and act on that structure.

To check if a collection contains items that make up a contiguous sequence use is_contiguous():

>>> collection = clique.Collection('file.', '.jpg', 4)
>>> collection.indexes.update([1, 2, 3, 4, 5])
>>> print collection
file.%04d.jpg [1-5]
>>> print collection.is_contiguous()
>>> collection.indexes.discard(3)
>>> print collection
file.%04d.jpg [1-2, 4-5]
>>> print collection.is_contiguous()

To access the missing indexes in a non-contiguous collection use the holes() method (which returns a new Collection):

>>> missing = collection.holes()
>>> print missing.indexes

To separate a non-contiguous collection into a number of contiguous collections use the separate() method:

>>> subcollections = collection.separate()
>>> for subcollection in subcollections:
...     print subcollection
file.%04d.jpg [1-2]
file.%04d.jpg [4-5]

And to merge compatible collections into another use the merge() method:

>>> collection_a = clique.Collection('file.', '.jpg', 4, set([1, 2]))
>>> collection_b = clique.Collection('file.', '.jpg', 4, set([4, 5]))
>>> print collection_a.indexes
[1, 2]
>>> collection_a.merge(collection_b)
>>> print collection_a.indexes
[1, 2, 4, 5]


The collection being merged into is modified in-place, whilst the collection being merged is left unaltered.

A collection can be tested for compatibility using the is_compatible() method:

>>> collection_a = clique.Collection('file.', '.jpg', 4, set([1, 2]))
>>> collection_b = clique.Collection('file.', '.jpg', 4, set([4, 5]))
>>> collection_c = clique.Collection('file.', '.dpx', 4, set([4, 5]))

>>> print collection_a.is_compatible(collection_b)
>>> print collection_a.is_compatible(collection_c)