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#!/usr/bin/env python
# -*- coding: utf-8 -*-
import csv
import datetime
import hashlib
import sys
from django.core.management.base import BaseCommand
from ishtar_common.models import Document
BLOCKSIZE = 65536
def get_hexdigest(filename):
m = hashlib.sha256()
with open(filename, 'rb') as afile:
buf = afile.read(BLOCKSIZE)
while len(buf) > 0:
m.update(buf)
buf = afile.read(BLOCKSIZE)
return m.hexdigest()
class Command(BaseCommand):
help = 'Re-associate similar images in the database'
def add_arguments(self, parser):
parser.add_argument(
'--merge-title', type=str, default='', dest='merged-title',
help='If specified when title differs the given title will be '
'used.')
parser.add_argument(
'--output-path', type=str, default='', dest='output-path',
help='Output path for results CSV files. Default to current path.')
parser.add_argument(
'--ignore-reference', dest='ignore-reference', action='store_true',
help='Ignore the reference on diff between models.')
parser.add_argument(
'--delete-missing', dest='delete-missing', action='store_true',
default=False, help='Delete document with missing images.')
parser.add_argument(
'--quiet', dest='quiet', action='store_true',
help='Quiet output.')
def handle(self, *args, **options):
quiet = options['quiet']
ignore_ref = options['ignore-reference']
delete_missing = options['delete-missing']
merged_title = options['merged-title']
output_path = options['output-path']
q = Document.objects.filter(image__isnull=False).exclude(
image='')
hashes = {}
missing_images = []
count = q.count()
out = sys.stdout
if not quiet:
out.write("* {} images\n".format(count))
for idx, doc in enumerate(q.all()):
if not quiet:
out.write("\r* hashes calculation: {} %".format(
int(float(idx + 1) / count * 100)))
out.flush()
path = doc.image.path
try:
hexdigest = get_hexdigest(path)
except IOError:
missing_images.append(doc.pk)
continue
if hexdigest not in hashes:
hashes[hexdigest] = []
hashes[hexdigest].append(doc.pk)
nb_missing_images = len(missing_images)
if not quiet:
out.write("\n* {} missing images\n".format(nb_missing_images))
if missing_images and delete_missing:
for nb, idx in enumerate(missing_images):
if not quiet:
out.write(
"\r* delete document with missing images: {} %".format(
int(float(nb + 1) / nb_missing_images * 100)))
out.flush()
doc = Document.objects.get(pk=idx)
doc.delete()
if not quiet:
out.write("\n")
attributes = [
'title', 'associated_file', 'internal_reference', 'source_type',
'support_type', 'format_type', 'scale',
'authors_raw', 'associated_url', 'receipt_date', 'creation_date',
'receipt_date_in_documentation', 'item_number', 'description',
'comment', 'additional_information', 'duplicate'
]
if not ignore_ref:
attributes.append('reference')
m2ms = ['authors', 'licenses']
nb_conflicted_items = 0
nb_merged_items = 0
distinct_image = 0
conflicts = []
merged = []
count = len(hashes)
for idx, hash in enumerate(hashes):
if not quiet:
out.write("\r* merge similar images: {} %".format(
int(float(idx + 1) / count * 100)))
out.flush()
if len(hashes[hash]) < 2:
distinct_image += 1
continue
items = [Document.objects.get(pk=pk) for pk in hashes[hash]]
ref_item = items[0]
other_items = items[1:]
for item in other_items:
ref_item = Document.objects.get(pk=ref_item.pk)
conflicted_values = []
for attr in attributes:
ref_value = getattr(ref_item, attr)
other_value = getattr(item, attr)
if ref_value:
if not other_value:
continue
if other_value != ref_value:
if attr == 'title' and merged_title:
setattr(ref_item, 'title', merged_title)
else:
conflicted_values.append(
(attr, ref_value, other_value)
)
else:
if not other_value:
continue
setattr(ref_item, attr, other_value)
base_csv = [
ref_item.pk,
ref_item.reference.encode('utf-8') if
ref_item.reference else "",
ref_item.cache_related_label.encode('utf-8') if
ref_item.cache_related_label else "",
ref_item.image.name.encode('utf-8'),
item.pk,
item.reference.encode('utf-8') if
item.reference else "",
item.cache_related_label.encode('utf-8') if
item.cache_related_label else "",
item.image.name.encode('utf-8'),
]
if conflicted_values:
nb_conflicted_items += 1
for attr, ref_value, other_value in conflicted_values:
conflicts.append(base_csv + [
attr, unicode(ref_value).encode('utf-8'),
unicode(other_value).encode('utf-8')
])
continue
merged.append(base_csv)
for m2m in m2ms:
for m2 in getattr(item, m2m).all():
if m2 not in getattr(ref_item, m2m).all():
getattr(ref_item, m2m).add(m2)
for rel_attr in Document.RELATED_MODELS:
ref_rel_items = [
r.pk for r in getattr(ref_item, rel_attr).all()]
for rel_item in getattr(item, rel_attr).all():
if rel_item.pk not in ref_rel_items:
getattr(ref_item, rel_attr).add(rel_item)
ref_item.skip_history_when_saving = True
ref_item.save()
item.delete()
nb_merged_items += 1
if not quiet:
out.write(u"\n")
n = datetime.datetime.now().isoformat().split('.')[0].replace(':', '-')
if conflicts:
filename = output_path + u"{}-conflict.csv".format(n)
with open(filename, 'w') as csvfile:
writer = csv.writer(csvfile)
writer.writerow(
["Document 1 - pk", "Document 1 - Ref",
"Document 1 - related", "Document 1 - image path",
"Document 2 - pk", "Document 2 - Ref",
"Document 2 - related", "Document 2 - image path",
"Attribute", "Document 1 - value", "Document 2 - value"
]
)
for conflict in conflicts:
writer.writerow(conflict)
if not quiet:
out.write(u"* {} conflicted items ({})\n".format(
nb_conflicted_items, filename))
if merged:
filename = output_path + u"{}-merged.csv".format(n)
with open(filename, 'w') as csvfile:
writer = csv.writer(csvfile)
writer.writerow(
["Document 1 - pk", "Document 1 - Ref",
"Document 1 - related", "Document 1 - image path",
"Document 2 - pk", "Document 2 - Ref",
"Document 2 - related", "Document 2 - image path",
]
)
for merge in merged:
writer.writerow(merge)
if not quiet:
out.write(u"* {} merged items ({})\n".format(nb_merged_items,
filename))
if not quiet:
out.write("* {} distinct images\n".format(distinct_image))
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