def import_locations(config, file_name='locations.csv', overwrite=False, dry_run=False,
quiet=False):
"""Import locations from CSV file provided by client."""
from arctasks.django import setup; setup(config) # noqa
from ecoroofs.locations.importer import Importer
location_importer = Importer(file_name, overwrite=overwrite, dry_run=dry_run, quiet=quiet)
location_importer.run()
def copy_records(ctx, recreate_db=False):
"""Copy database records from old site.
This is messy because only certain records are copied from the old
site while others are loaded from fixtures.
"""
setup()
from django.db import connections
from django.contrib.auth import get_user_model
from elasticmodels import suspended_updates
settings = get_settings()
settings.DATABASES['old'] = {
'ENGINE': 'django.contrib.gis.db.backends.postgis',
'HOST': 'pgsql.rc.pdx.edu',
'NAME': 'invhotline',
'USER': '******',
'PASSWORD': getpass(
'Old database password (get from '
'/vol/www/invasivespecieshotline/invasivespecieshotline/config/database.yml): '
),
}
User = get_user_model()
if recreate_db:
createdb(ctx, drop=True)
migrate(ctx)
loaddata(ctx)
with suspended_updates():
_copy_records(settings)
default = connections['default']
print('Updating sequences...', end='')
tables = (
'category', 'comment', 'county', 'image', 'invite', 'notification', 'report', 'species',
'user', 'user_notification_query',
)
statement = """
SELECT setval(
pg_get_serial_sequence('{table}', '{table}_id'),
coalesce(max({table}_id), 0) + 1,
false
)
FROM "{table}";
"""
statements = ' '.join(statement.format(table=table) for table in tables)
default.cursor().execute(statements)
print('Done')
print('Updating expert contact name...', end='')
expert = User.objects.filter(first_name='EXPERT', last_name='CONTACT')
expert.update(first_name='', last_name='')
print('Done')
def import_neighborhoods(config, path='rlis/nbo_hood', from_srid=None,
overwrite=True, dry_run=False, quiet=False):
"""Import neighborhoods from RLIS shapefile.
We overwrite by default because doing so should be safe.
The neighborhoods shapefile can be downloaded from Metro's RLIS
Discovery site::
http://rlisdiscovery.oregonmetro.gov/?action=viewDetail&layerID=237
This task expects the shapefile directory to be at ``rlis/nbo_hood``
by default, but it can be located anywhere if you pass the
corresponding ``--path`` option.
"""
from arctasks.django import setup; setup(config) # noqa
from ecoroofs.neighborhoods.importer import Importer
location_importer = Importer(
path, from_srid=from_srid, overwrite=overwrite, dry_run=dry_run, quiet=quiet)
location_importer.run()
def remove_duplicate_users(ctx):
setup()
from django.apps import apps
from django.contrib.auth import get_user_model
from arcutils.db import will_be_deleted_with
Comment = apps.get_model('comments', 'Comment')
Image = apps.get_model('images', 'Image')
Notification = apps.get_model('notifications', 'Notification')
UserNotificationQuery = apps.get_model('notifications', 'UserNotificationQuery')
Invite = apps.get_model('reports', 'Invite')
Report = apps.get_model('reports', 'Report')
user_model = get_user_model()
dupes = user_model.objects.raw(
'SELECT * from "user" u1 '
'WHERE ('
' SELECT count(*) FROM "user" u2 WHERE lower(u2.email) = lower(u1.email )'
') > 1 '
'ORDER BY lower(email)'
)
dupes = [d for d in dupes]
print_info('Found {n} duplicates'.format(n=len(dupes)))
# Delete any dupes we can.
# Active and staff users are never deleted.
# Public users with no associated records will be deleted.
for user in dupes:
email = user.email
objects = list(will_be_deleted_with(user))
num_objects = len(objects)
f = locals()
if user.is_active:
print('Skipping active user: {email}.'.format_map(f))
elif user.is_staff:
print('Skipping inactive staff user: {email}.'.format_map(f))
elif num_objects == 0:
print_warning('Deleting {email} will *not* cascade.'.format_map(f))
if confirm(ctx, 'Delete {email}?'.format_map(f), yes_values=('yes',)):
print('Okay, deleting {email}...'.format_map(f), end='')
user.delete()
dupes.remove(user)
print('Deleted')
else:
print(
'Deleting {email} would cascade to {num_objects} objects. Skipping.'.format_map(f))
# Group the remaining duplicates by email address
grouped_dupes = defaultdict(list)
for user in dupes:
email = user.email.lower()
grouped_dupes[email].append(user)
grouped_dupes = {email: users for (email, users) in grouped_dupes.items() if len(users) > 1}
# For each group, find the "best" user (staff > active > inactive).
# The other users' associated records will be associated with this
# "winner".
for email, users in grouped_dupes.items():
winner = None
for user in users:
if user.is_staff:
winner = user
break
if winner is None:
for user in users:
if user.is_active:
winner = user
break
if winner is None:
for user in users:
if user.full_name:
winner = user
if winner is None:
winner = users[0]
losers = [user for user in users if user != winner]
print('Winner:', winner.full_name, '<{0.email}>'.format(winner))
for loser in losers:
print('Loser:', loser.full_name, '<{0.email}>'.format(loser))
print('Re-associating loser objects...', end='')
Comment.objects.filter(created_by=loser).update(created_by=winner)
Image.objects.filter(created_by=loser).update(created_by=winner)
Invite.objects.filter(user=loser).update(user=winner)
Invite.objects.filter(created_by=loser).update(created_by=winner)
Notification.objects.filter(user=loser).update(user=winner)
Report.objects.filter(claimed_by=loser).update(claimed_by=winner)
Report.objects.filter(created_by=loser).update(created_by=winner)
UserNotificationQuery.objects.filter(user=loser).update(user=winner)
print('Done')
