Added django.contrib.humanize, a set of template tags for adding a 'human touch' to data. They're documented in add_ons.txt.

git-svn-id: http://code.djangoproject.com/svn/django/trunk@3076 bcc190cf-cafb-0310-a4f2-bffc1f526a37
This commit is contained in:
Adrian Holovaty 2006-06-04 00:58:39 +00:00
parent a5b7c29816
commit fb537e177d
5 changed files with 125 additions and 0 deletions

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from django import template
import re
register = template.Library()
def ordinal(value):
"""
Converts an integer to its ordinal as a string. 1 is '1st', 2 is '2nd',
3 is '3rd', etc. Works for any integer.
"""
try:
value = int(value)
except ValueError:
return value
t = ('th', 'st', 'nd', 'rd', 'th', 'th', 'th', 'th', 'th', 'th')
if value % 100 in (11, 12, 13): # special case
return '%dth' % value
return '%d%s' % (value, t[value % 10])
register.filter(ordinal)
def intcomma(value):
"""
Converts an integer to a string containing commas every three digits.
For example, 3000 becomes '3,000' and 45000 becomes '45,000'.
"""
orig = str(value)
new = re.sub("^(-?\d+)(\d{3})", '\g<1>,\g<2>', str(value))
if orig == new:
return new
else:
return intcomma(new)
register.filter(intcomma)
def intword(value):
"""
Converts a large integer to a friendly text representation. Works best for
numbers over 1 million. For example, 1000000 becomes '1.0 million', 1200000
becomes '1.2 million' and '1200000000' becomes '1.2 billion'.
"""
value = int(value)
if value < 1000000:
return value
if value < 1000000000:
return '%.1f million' % (value / 1000000.0)
if value < 1000000000000:
return '%.1f billion' % (value / 1000000000.0)
if value < 1000000000000000:
return '%.1f trillion' % (value / 1000000000000.0)
return value
register.filter(intword)

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@ -45,6 +45,57 @@ See the `csrf documentation`_.
.. _csrf documentation: http://www.djangoproject.com/documentation/csrf/ .. _csrf documentation: http://www.djangoproject.com/documentation/csrf/
humanize
========
A set of Django template filters useful for adding a "human touch" to data.
To activate these filters, add ``'django.contrib.english'`` to your
``INSTALLED_APPS`` setting. Once you've done that, use ``{% load english %}``
in a template, and you'll have access to these filters:
ordinal
-------
Converts an integer to its ordinal as a string.
Examples:
* ``1`` becomes ``'1st'``.
* ``2`` becomes ``'2nd'``.
* ``3`` becomes ``'3rd'``.
You can pass in either an integer or a string representation of an integer.
intcomma
--------
Converts an integer to a string containing commas every three digits.
Examples:
* ``4500`` becomes ``'4,500'``.
* ``45000`` becomes ``'45,000'``.
* ``450000`` becomes ``'450,000'``.
* ``4500000`` becomes ``'4,500,000'``.
You can pass in either an integer or a string representation of an integer.
intword
-------
Converts a large integer to a friendly text representation. Works best for
numbers over 1 million.
Examples:
* ``1000000`` becomes ``'1.0 million'``.
* ``1200000`` becomes ``'1.2 million'``.
* ``1200000000`` becomes ``'1.2 billion'``.
Values up to 1000000000000000 (one quadrillion) are supported.
You can pass in either an integer or a string representation of an integer.
flatpages flatpages
========= =========

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@ -1091,3 +1091,27 @@ Value Argument Outputs
``None`` ``"yeah,no"`` ``"no"`` (converts None to False ``None`` ``"yeah,no"`` ``"no"`` (converts None to False
if no mapping for None is given) if no mapping for None is given)
========== ====================== ================================== ========== ====================== ==================================
Other tags and filter libraries
===============================
Django comes with a couple of other template-tag libraries that you have to
enable explicitly in your ``INSTALLED_APPS`` setting and enable in your
template with the ``{% load %}`` tag.
django.contrib.humanize
-----------------------
A set of Django template filters useful for adding a "human touch" to data. See
the `humanize documentation`_.
.. _humanize documentation: http://www.djangoproject.com/documentation/add_ons/#humanize
django.contrib.markup
---------------------
A collection of template filters that implement these common markup languages:
* Textile
* Markdown
* ReST (ReStructured Text)