def extend_entry(entry, dataset):
entry['dataset'] = dataset.name
entry['dataset.id'] = dataset.id
entry = flatten(entry)
entry['_id'] = dataset.name + '::' + unicode(entry['id'])
for k, v in entry.items():
# this is similar to json encoding, but not the same.
if isinstance(v, datetime.datetime) and not v.tzinfo:
entry[k] = datetime.datetime(v.year,
v.month,
v.day,
v.hour,
v.minute,
v.second,
tzinfo=tzutc())
elif '.' in k and isinstance(v, (list, tuple)):
entry[k] = " ".join([unicode(vi) for vi in v])
else:
entry[k] = safe_unicode(entry[k])
if k.endswith(".name"):
vk = k[:len(k) - len(".name")]
entry[vk] = v
if k.endswith(".label"):
entry[k + "_str"] = entry[k]
entry[k + "_facet"] = entry[k]
for item in PluginImplementations(ISolrSearch):
entry = item.update_index(entry)
return entry
def extend_entry(entry, dataset):
entry['dataset'] = dataset.name
entry['dataset.id'] = dataset.id
entry = flatten(entry)
entry['_id'] = dataset.name + '::' + unicode(entry['id'])
for k, v in entry.items():
if k.endswith(".taxonomy") or k.endswith('.color'):
continue
# this is similar to json encoding, but not the same.
if isinstance(v, datetime.datetime) and not v.tzinfo:
entry[k] = datetime.datetime(v.year,
v.month,
v.day,
v.hour,
v.minute,
v.second,
tzinfo=UTC())
elif '.' in k and isinstance(v, (list, tuple)):
entry[k] = " ".join([unicode(vi) for vi in v])
else:
entry[k] = _safe_unicode(entry[k])
if k.endswith(".name"):
vk = k[:len(k) - len(".name")]
entry[vk] = v
if k.endswith(".label"):
entry[k + "_facet"] = entry[k]
return entry
def generate_csv_row(entry, generate_headers=True):
row = {}
for k, v in flatten(entry).items():
if isinstance(v, (list, tuple, dict)):
continue
elif isinstance(v, datetime):
v = v.isoformat()
elif isinstance(v, float):
v = u'%.2f' % v
row[unicode(k).encode('utf8')] = unicode(v).encode('utf8')
fields = sorted(row.keys())
sio = StringIO()
writer = csv.DictWriter(sio, fields)
if generate_headers:
header = dict(zip(fields, fields))
writer.writerow(header)
writer.writerow(row)
return sio.getvalue()
def extend_entry(entry, dataset):
entry['dataset'] = dataset.name
entry['dataset.id'] = dataset.id
entry = flatten(entry)
entry['_id'] = dataset.name + '::' + unicode(entry['id'])
for k, v in entry.items():
# this is similar to json encoding, but not the same.
if isinstance(v, datetime.datetime) and not v.tzinfo:
entry[k] = datetime.datetime(v.year, v.month, v.day, v.hour,
v.minute, v.second, tzinfo=UTC())
elif '.' in k and isinstance(v, (list, tuple)):
entry[k] = " ".join([unicode(vi) for vi in v])
else:
entry[k] = _safe_unicode(entry[k])
if k.endswith(".name"):
vk = k[:len(k)-len(".name")]
entry[vk] = v
if k.endswith(".label"):
#entry[k + "_str"] = entry[k]
entry[k + "_facet"] = entry[k]
return entry
def generate_csv(entries):
generate_headers = True
for entry in entries:
row = {}
for k, v in flatten(entry).items():
if isinstance(v, (list, tuple, dict)):
continue
elif isinstance(v, datetime):
v = v.isoformat()
row[unicode(k).encode('utf8')] = unicode(v).encode('utf8')
fields = sorted(row.keys())
sio = StringIO()
writer = csv.DictWriter(sio, fields)
if generate_headers:
header = dict(zip(fields, fields))
writer.writerow(header)
generate_headers = False
writer.writerow(row)
yield sio.getvalue()
def generate_csv(entries):
generate_headers = True
for entry in entries:
row = {}
for k, v in flatten(entry).items():
if isinstance(v, (list, tuple, dict)):
continue
elif isinstance(v, datetime):
v = v.isoformat()
row[unicode(k).encode('utf8')] = unicode(v).encode('utf8')
fields = sorted(row.keys())
sio = StringIO()
writer = csv.DictWriter(sio, fields)
if generate_headers:
header = dict(zip(fields, fields))
writer.writerow(header)
generate_headers = False
writer.writerow(row)
yield sio.getvalue()
