8bc4b6a95e
Code now resides in common.serialization in the form of two new functions: yaml_load and yaml_dump. Signed-off-by: Roberto Rosario <roberto.rosario@mayan-edms.com>
116 lines
3.9 KiB
Python
116 lines
3.9 KiB
Python
from __future__ import unicode_literals
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import logging
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from django.contrib.contenttypes.models import ContentType
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from django.db import models, transaction
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from mayan.apps.common.serialization import yaml_dump, yaml_load
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from .transformations import BaseTransformation
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logger = logging.getLogger(__name__)
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class TransformationManager(models.Manager):
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def add_to_object(self, obj, transformation, arguments=None):
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content_type = ContentType.objects.get_for_model(model=obj)
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self.create(
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content_type=content_type, object_id=obj.pk,
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name=transformation.name, arguments=yaml_dump(
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data=arguments
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)
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)
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def copy(self, source, targets):
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"""
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Copy transformation from source to all targets
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"""
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content_type = ContentType.objects.get_for_model(model=source)
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# Get transformations
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transformations = self.filter(
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content_type=content_type, object_id=source.pk
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).values('name', 'arguments', 'order')
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logger.debug('source transformations: %s', transformations)
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# Get all targets from target QS
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targets_dict = map(
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lambda entry: {
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'content_type': entry[0], 'object_id': entry[1]
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}, zip(
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ContentType.objects.get_for_models(models=targets).values(),
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targets.values_list('pk', flat=True)
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)
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)
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logger.debug('targets: %s', targets_dict)
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# Combine the two
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results = []
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for instance in targets_dict:
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for transformation in transformations:
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result = instance.copy()
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result.update(transformation)
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results.append(dict(result))
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logger.debug('results: %s', results)
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# Bulk create for a single DB query
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with transaction.atomic():
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self.bulk_create(
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map(lambda entry: self.model(**entry), results),
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)
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def get_for_object(self, obj, as_classes=False):
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"""
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as_classes == True returns the transformation classes from .classes
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ready to be feed to the converter class
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"""
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content_type = ContentType.objects.get_for_model(model=obj)
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transformations = self.filter(
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content_type=content_type, object_id=obj.pk
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)
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if as_classes:
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result = []
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for transformation in transformations:
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try:
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transformation_class = BaseTransformation.get(
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transformation.name
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)
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except KeyError:
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# Non existant transformation, but we don't raise an error
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logger.error(
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'Non existant transformation: %s for %s',
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transformation.name, obj
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)
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else:
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try:
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# Some transformations don't require arguments
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# return an empty dictionary as ** doesn't allow None
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if transformation.arguments:
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kwargs = yaml_load(
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stream=transformation.arguments,
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)
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else:
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kwargs = {}
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result.append(
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transformation_class(
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**kwargs
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)
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)
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except Exception as exception:
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logger.error(
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'Error while parsing transformation "%s", '
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'arguments "%s", for object "%s"; %s',
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transformation, transformation.arguments, obj,
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exception
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)
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return result
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else:
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return transformations
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