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namedlist 0.3

Similar to namedtuple, but instances are mutable.

Latest Version: 1.4

Overview

namedlist provides a factory function, named namedlist.namedlist. It is similar to collections.namedtuple, with the following differences:

  • namedlist instances are mutable.
  • namedlist supports per-field default values.
  • namedlist supports an optional default value, to be used by all fields do not have an explicit default value.

Typical usage

You can use namedlist like a mutable namedtuple:

>>> from namedlist import namedlist

>>> Point = namedlist('Point', 'x y')
>>> p = Point(1, 3)
>>> p.x = 2
>>> assert p.x == 2
>>> assert p.y == 3

Or, you can specify a default value for all fields:

>>> Point = namedlist('Point', 'x y', default=3)
>>> p = Point(y=2)
>>> assert p.x == 3
>>> assert p.y == 2

Or, you can specify per-field default values:

>>> Point = namedlist('Point', [('x', 0), ('y', 100)])
>>> p = Point()
>>> assert p.x == 0
>>> assert p.y == 100

You can also specify the per-field defaults with a mapping, instead of an interable. Note that this is only useful with an ordered mapping, such as an OrderedDict:

>>> from collections import OrderedDict
>>> Point = namedlist('Point', OrderedDict((('y', 0),
...                                         ('x', 100))))
>>> p = Point()
>>> p
Point(y=0, x=100)

The default value will only be used if it is provided and a per-field default is not used:

>>> Point = namedlist('Point', ['x', ('y', 100)], default=10)
>>> p = Point()
>>> assert p.x == 10
>>> assert p.y == 100

If you use a mapping, the value NO_DEFAULT is convenient to specify that a field uses the default value:

>>> from namedlist import NO_DEFAULT
>>> Point = namedlist('Point', OrderedDict((('y', NO_DEFAULT),
...                                         ('x', 100))),
...                            default=5)
>>> p = Point()
>>> assert p.x == 100
>>> assert p.y == 5

Creating types

Specifying Fields

Fields can be specified as in namedtuple: as either a string specifing the field names, or as a iterable of field names. These two uses are equivalent:

>>> Point = namedlist('Point', 'x y')
>>> Point = namedlist('Point', ['x', 'y'])

If using a string, commas are first converted to spaces. So these are equivalent:

>>> Point = namedlist('Point', 'x y')
>>> Point = namedlist('Point', 'x,y')

Specifying Defaults

Per-field defaults can be specified by supplying a 2-tuple (name, default_value) instead of just a string for the field name. This is only supported when you specify a list of field names:

>>> Point = namedlist('Point', [('x', 0), ('y', 0)])
>>> p = Point(3)
>>> assert p.x == 3
>>> assert p.y == 0

In addition to, or instead of, these per-field defaults, you can also specify a default value which is used when no per-field default value is specified:

>>> Point = namedlist('Point', 'x y z', default=0)
>>> p = Point(y=3)
>>> assert p.x == 0
>>> assert p.y == 3
>>> assert p.z == 0

>>> Point = namedlist('Point', [('x', 0), 'y', ('z', 0)], default=4)
>>> p = Point(z=2)
>>> assert p.x == 0
>>> assert p.y == 4
>>> assert p.z == 2

In addition to supplying the field names as an iterable of 2-tuples, you can also specify a mapping. The keys will be the field names, and the values will be the per-field default values. This is most useful with an OrderedDict, as the order of the fields will then be deterministic. The module variable NO_DEFAULT can be specified if you want a field to use the per-type default value instead of specifying it with a field:

>>> Point = namedlist('Point', OrderedDict((('x', 0),
...                                         ('y', NO_DEFAULT),
...                                         ('z', 0),
...                                         )),
...                            default=4)
>>> p = Point(z=2)
>>> assert p.x == 0
>>> assert p.y == 4
>>> assert p.z == 2

Writing to values

The objects retured by the factory function are fully writable, unlike the tuple-derived classes returned by namedtuple:

>>> Point = namedlist('Point', 'x y')
>>> p = Point(1, 2)
>>> p.y = 4
>>> assert p.x == 1
>>> assert p.y == 4

Specifying __slots__

By default, the returned class sets __slots__, which is initialized to the field names. While this decreases memory usage by eliminating the instance dict, it also means that you cannot create new instance members.

To change this behavior, specify use_slots=False when creating the namedlist:

>>> Point = namedlist('Point', 'x y', use_slots=False)
>>> p = Point(0, 1)
>>> p.z = 2
>>> assert p.x == 0
>>> assert p.y == 1
>>> assert p.z == 2

Additional class members

namedlist classes contain these members:

  • _asdict(): Returns a dict which maps field names to their corresponding values.
  • _fields: Tuple of strings listing the field names. Useful for introspection.

Renaming invalid field names

This functionality is identical to namedtuple. If you specify rename=True, then any invalid field names are changed to _0, _1, etc. Reasons for a field name to be invalid are:

  • Zero length strings.
  • Containing characters other than alphanumerics and underscores.
  • A conflict with a Python reserved identifier.
  • Beginning with a digit.
  • Beginning with an underscore.
  • Using the same field name more than once.

For example:

>>> Point = namedlist('Point', 'x x for', rename=True)
>>> assert Point._fields == ('x', '_1', '_2')

Mutable default values

Be aware of creating mutable default values. Due to the way Python handles default values, each instance of a namedlist will share the default. This is especially problematic with default values that are lists. For example:

>>> A = namedlist('A', [('x', [])])
>>> a = A()
>>> a.x.append(4)
>>> b = A()
>>> assert b.x == [4]

This is probably not the desired behavior, so see the next section.

Specifying a factory function for default values

You can supply a zero-argument callable for a default, by wrapping it in a FACTORY call. The only change in this example is to change the default from [] to FACTORY(list). But note that b.x is a new list object, not shared with a.x:

>>> from namedlist import FACTORY
>>> A = namedlist('A', [('x', FACTORY(list))])
>>> a = A()
>>> a.x.append(4)
>>> b = A()
>>> assert b.x == []

Every time a new instance is created, your callable (in this case, list), will be called to produce a new instance for the default value.

Iterating over instances

Because instances are iterable (like lists), iteration works the same way. Values are returned in definition order:

>>> Point = namedlist('Point', 'x y z t')
>>> p = Point(1.0, 42.0, 3.14, 2.71828)
>>> for value in p:
...    print(value)
1.0
42.0
3.14
2.71828

Creating and using instances

Because the type returned by namedlist is a normal Python class, you create instances as you would with any Python class.

Change log

0.3 2014-01-29 Eric V. Smith

  • Removed documentation left over from recordtype.
  • Make instances unhashable (issue #2).
  • For python3, use str.isidentifier (issue #1).
  • Reorganize code for name checking. No functional changes.
  • Make instances iterable (issue #3).
  • Add collections.Sequence ABC (issue #4).
  • Have "python setup.py test" also run doctests (issue #5).

0.2 2014-01-28 Eric V. Smith

  • Added MANIFEST.in.
  • Hopefully fixed a problem with .rst formatting in CHANGES.txt.

0.1 2014-01-28 Eric V. Smith

  • Initial release.
  • Based off my recordtype project, but uses ast generation instead of building up a string and exec-ing it. This has a number of advantages:
    • Supporting both python2 and python3 is easier. exec has the anti-feature of having different syntax in the two languages.
    • Adding additional features is easier, because I can write in real Python instead of having to write the string version, and deal with all of the escaping and syntax errors.
  • Added FACTORY, to allow namedlist to work even with mutable defaults.
 
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