# collections

Starlark module for working with collections library.

This module implements specialized container datatypes providing alternatives to Python's general purpose built-in containers, dict, list, set, and tuple.

Similar to [collections in Python](https://docs.python.org/3/library/collections.html).

## collections.after\_each(separator, iterable)

Inserts separator after each item in iterable.

**Parameters:**

* **separator** - the value to insert after each item in iterable.
* **iterable** - the list into which to intersperse the separator.

*Returns:* a new list with separator after each item in iterable.

## collections.before\_each(separator, iterable)

Inserts separator before each item in iterable.

**Parameters:**

* **separator** - the value to insert before each item in iterable.
* **iterable** - the list into which to intersperse the separator.

*Returns:* a new list with separator before each item in iterable.

## collections.namedtuple(typename, field\_names, rename=False, defaults=None, module=None)

*Returns:* a new subclass of tuple with named fields.

Examples:

```python
Point = namedtuple('Point', ['x', 'y'])
Point.__doc__                # docstring for the new class
'Point(x, y)'
p = Point(11, y=22)          # instantiate with positional args or keywords
p[0] + p[1]                  # indexable like a plain tuple
33
x, y = p                     # unpack like a regular tuple
x, y
(11, 22)
p.x + p.y                    # fields also accessible by name
33
d = p._asdict()              # convert to a dictionary
d['x']
11
Point(**d)                   # convert from a dictionary
Point(x=11, y=22)
p._replace(x=100)            # _replace() is like str.replace() but targets named fields
Point(x=100, y=22)
```

## collections.uniq(iterable)

*Returns:* a list of unique elements in iterable. Requires all the elements to be hashable.

**Parameters:**

**iterable** – an iterable to filter.

*Returns:* a new list with all unique elements from iterable.


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