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84 lines
2.5 KiB
84 lines
2.5 KiB
from django.shortcuts import _get_queryset
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from django.utils import timezone
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from pprint import pprint, pformat
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import natsort
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import pydash as _; _.map = _.map_; _.filter = _.filter_
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import random
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def take(coll, n):
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chunk = coll[0:n]
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del coll[0:n]
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return chunk
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def take_random(coll, n):
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if n == 0:
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return []
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chunk = _.sample(coll, n)
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for item in chunk:
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coll.remove(item)
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return chunk
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def take_one_random(coll):
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if len(coll) == 0:
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return None
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return coll.pop(_.random(0, len(coll)-1))
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def random_phone():
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return '+7' + str(_.sample((917, 964, 965, 987, 912, 935))) + str(_.random(1000000, 9999999))
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def random_date():
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return timezone.datetime(_.random(2012, 2018), _.random(1, 12), _.random(1, 28))
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def random_amount():
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return random.random() * random.choice((100, 1000, 10000))
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def get_or_none(klass, *args, **kwargs):
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queryset = _get_queryset(klass)
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try:
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return queryset.get(*args, **kwargs)
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except queryset.model.DoesNotExist:
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return None
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def get_attr_or_none(klass, *args, attr=None, **kwargs):
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object = get_or_none(klass, *args, **kwargs)
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if object and attr and isinstance(attr, str):
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return getattr(object, attr, None)
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def model_fields(model, width=200):
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fields = natsort.natsorted(model._meta.get_fields(), key=lambda f: f.name)
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pprint([(
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f.name,
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'Relation? %s' % f.is_relation,
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'Null? %s' % f.null,
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'Blank? %s' % f.blank if not f.is_relation else '(relation)',
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) for f in fields], width=width)
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def lorem(sentences=5):
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words = _.split((
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'a ac adipiscing amet ante arcu at auctor augue bibendum commodo condimentum consectetur consequat convallis curabitur'
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'cursus diam dictum dignissim dolor donec duis efficitur eget eleifend elit enim erat et eu ex facilisis faucibus feugiat'
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'finibus gravida iaculis id imperdiet in integer ipsum lacinia lacus laoreet lectus leo libero ligula lobortis lorem'
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'luctus maecenas mauris metus mi mollis morbi nam nec neque nisi non nulla nullam nunc odio orci ornare pellentesque'
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'pharetra phasellus porta porttitor posuere pretium proin pulvinar purus quam quis rhoncus rutrum sapien sed sem semper'
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'sit sollicitudin tempor tempus tincidunt tortor turpis ullamcorper ultricies ut varius vehicula vel velit vestibulum'
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'vitae viverra volutpat vulputate'
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), ' ')
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return _.join(_.times(lambda i_: _.capitalize(_.join(_.sample(words, _.random(5, 30)), ' ')), sentences), '. ')
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