Adds to Melange a tags framework based on taggable-mixin.
The taggable-mixin allowed only tag per Datastore model. This is extended
framework allows any arbitrary number of tags per Datastore model. Also,
now one can define different models for different Tag types which are all
inherited from the base Tag model provided by taggable-mixin.
The GHOPTask model makes use of 2 tags per model, one for difficulty and the
other for task_type, both using the tags framework.
Reviewed by: Paweł Sołyga
"""
Utility functions for generating "lorem ipsum" Latin text.
"""
import random
COMMON_P = 'Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.'
WORDS = ('exercitationem', 'perferendis', 'perspiciatis', 'laborum', 'eveniet',
'sunt', 'iure', 'nam', 'nobis', 'eum', 'cum', 'officiis', 'excepturi',
'odio', 'consectetur', 'quasi', 'aut', 'quisquam', 'vel', 'eligendi',
'itaque', 'non', 'odit', 'tempore', 'quaerat', 'dignissimos',
'facilis', 'neque', 'nihil', 'expedita', 'vitae', 'vero', 'ipsum',
'nisi', 'animi', 'cumque', 'pariatur', 'velit', 'modi', 'natus',
'iusto', 'eaque', 'sequi', 'illo', 'sed', 'ex', 'et', 'voluptatibus',
'tempora', 'veritatis', 'ratione', 'assumenda', 'incidunt', 'nostrum',
'placeat', 'aliquid', 'fuga', 'provident', 'praesentium', 'rem',
'necessitatibus', 'suscipit', 'adipisci', 'quidem', 'possimus',
'voluptas', 'debitis', 'sint', 'accusantium', 'unde', 'sapiente',
'voluptate', 'qui', 'aspernatur', 'laudantium', 'soluta', 'amet',
'quo', 'aliquam', 'saepe', 'culpa', 'libero', 'ipsa', 'dicta',
'reiciendis', 'nesciunt', 'doloribus', 'autem', 'impedit', 'minima',
'maiores', 'repudiandae', 'ipsam', 'obcaecati', 'ullam', 'enim',
'totam', 'delectus', 'ducimus', 'quis', 'voluptates', 'dolores',
'molestiae', 'harum', 'dolorem', 'quia', 'voluptatem', 'molestias',
'magni', 'distinctio', 'omnis', 'illum', 'dolorum', 'voluptatum', 'ea',
'quas', 'quam', 'corporis', 'quae', 'blanditiis', 'atque', 'deserunt',
'laboriosam', 'earum', 'consequuntur', 'hic', 'cupiditate',
'quibusdam', 'accusamus', 'ut', 'rerum', 'error', 'minus', 'eius',
'ab', 'ad', 'nemo', 'fugit', 'officia', 'at', 'in', 'id', 'quos',
'reprehenderit', 'numquam', 'iste', 'fugiat', 'sit', 'inventore',
'beatae', 'repellendus', 'magnam', 'recusandae', 'quod', 'explicabo',
'doloremque', 'aperiam', 'consequatur', 'asperiores', 'commodi',
'optio', 'dolor', 'labore', 'temporibus', 'repellat', 'veniam',
'architecto', 'est', 'esse', 'mollitia', 'nulla', 'a', 'similique',
'eos', 'alias', 'dolore', 'tenetur', 'deleniti', 'porro', 'facere',
'maxime', 'corrupti')
COMMON_WORDS = ('lorem', 'ipsum', 'dolor', 'sit', 'amet', 'consectetur',
'adipisicing', 'elit', 'sed', 'do', 'eiusmod', 'tempor', 'incididunt',
'ut', 'labore', 'et', 'dolore', 'magna', 'aliqua')
def sentence():
"""
Returns a randomly generated sentence of lorem ipsum text.
The first word is capitalized, and the sentence ends in either a period or
question mark. Commas are added at random.
"""
# Determine the number of comma-separated sections and number of words in
# each section for this sentence.
sections = [u' '.join(random.sample(WORDS, random.randint(3, 12))) for i in range(random.randint(1, 5))]
s = u', '.join(sections)
# Convert to sentence case and add end punctuation.
return u'%s%s%s' % (s[0].upper(), s[1:], random.choice('?.'))
def paragraph():
"""
Returns a randomly generated paragraph of lorem ipsum text.
The paragraph consists of between 1 and 4 sentences, inclusive.
"""
return u' '.join([sentence() for i in range(random.randint(1, 4))])
def paragraphs(count, common=True):
"""
Returns a list of paragraphs as returned by paragraph().
If `common` is True, then the first paragraph will be the standard
'lorem ipsum' paragraph. Otherwise, the first paragraph will be random
Latin text. Either way, subsequent paragraphs will be random Latin text.
"""
paras = []
for i in range(count):
if common and i == 0:
paras.append(COMMON_P)
else:
paras.append(paragraph())
return paras
def words(count, common=True):
"""
Returns a string of `count` lorem ipsum words separated by a single space.
If `common` is True, then the first 19 words will be the standard
'lorem ipsum' words. Otherwise, all words will be selected randomly.
"""
if common:
word_list = list(COMMON_WORDS)
else:
word_list = []
c = len(word_list)
if count > c:
count -= c
while count > 0:
c = min(count, len(WORDS))
count -= c
word_list += random.sample(WORDS, c)
else:
word_list = word_list[:count]
return u' '.join(word_list)