def apply_params(url, params):
route_params = keyfilter(params_filter, params)
return (
reduce(lambda acc, kv: acc.replace(kv[0], kv[1]), route_params.items(),
url),
keyfilter(not_params_filter, params),
)
def update(token, **kwargs):
customer_id = get_customer_id(token)
args = keyfilter(lambda x: x in ["customer_name"], kwargs)
doc = frappe.get_doc("Customer", customer_id)
doc.update(args)
doc.save(ignore_permissions=True)
return keyfilter(lambda x: x in CUSTOMER_FIELDS, doc.as_dict())
def _create_address(customer, args):
fields = [
"address_line1", "address_line2", "city", "state", "country", "pincode"
]
_args = keyfilter(lambda x: x in fields, args)
doc = frappe.get_doc(
merge({
"doctype": "Address",
"address_type": "Billing"
}, _args))
doc.append("links", {"link_doctype": "Customer", "link_name": customer})
doc.insert(ignore_permissions=True)
return keyfilter(lambda x: x in ["name"] + fields, doc.as_dict())
def get_slideshow():
homepage = frappe.get_single("Homepage")
if homepage.hero_section_based_on != "Slideshow" or not homepage.slideshow:
return None
def get_route(item):
ref_doctype, ref_name = item.get("cm_ref_doctype"), item.get("cm_ref_docname")
if ref_doctype and ref_name:
route, show_in__website = frappe.get_cached_value(
ref_doctype, ref_name, ["route", "show_in_website"]
)
if route and show_in__website:
return transform_route({"route": route})
return None
return [
merge(
keyfilter(lambda y: y in ["image", "heading", "description"], x),
{"route": get_route(x), "kind": x.get("cm_ref_doctype")},
)
for x in frappe.get_all(
"Website Slideshow Item",
filters={"parent": homepage.slideshow},
fields=[
"image",
"heading",
"description",
"cm_ref_doctype",
"cm_ref_docname",
],
)
]
def get_groups(parsed, store, conf):
"""
Return groups based on argument provided
:param Namespace parsed: arguments parsed
:param store: Otter scaling group collection
:param dict conf: config
:return: Deferred fired with list of {"tenantId": .., "groupId": ..} dict
"""
log = mock_log()
if parsed.group:
groups = [g.split(":") for g in parsed.group]
return succeed([{"tenantId": tid, "groupId": gid} for tid, gid in groups])
elif parsed.all:
d = store.get_all_groups()
d.addCallback(lambda tgs: concat(tgs.values()))
elif parsed.tenant_id:
d = get_groups_of_tenants(log, store, parsed.tenant_id)
elif parsed.disabled_tenants:
non_conv_tenants = conf["non-convergence-tenants"]
d = store.get_all_groups()
d.addCallback(keyfilter(lambda k: k not in set(non_conv_tenants)))
d.addCallback(lambda tgs: concat(tgs.values()))
elif parsed.conf_conv_tenants:
d = get_groups_of_tenants(log, store, conf["convergence-tenants"])
else:
raise SystemExit("Unexpected group selection")
return d
def get_values(_type):
fields = list(map(lambda x: "{}_{}".format(_type, x), params))
_get = compose(
valmap(lambda x: x or 0),
keymap(lambda x: x.replace("{}_".format(_type), "")),
keyfilter(lambda x: x in fields),
)
return _get(data)
def get_clb_contents():
"""
Get Rackspace Cloud Load Balancer contents as list of `CLBNode`. CLB
health monitor information is also returned as a pmap of :obj:`CLB` objects
mapped on LB ID.
:return: Effect of (``list`` of :obj:`CLBNode`, `pmap` of :obj:`CLB`)
:rtype: :obj:`Effect`
"""
# If we get a CLBNotFoundError while fetching feeds, we should throw away
# all nodes related to that load balancer, because we don't want to act on
# data that we know is invalid/outdated (for example, if we can't fetch a
# feed because CLB was deleted, we don't want to say that we have a node in
# DRAINING with draining time of 0; we should just say that the node is
# gone).
def gone(r):
return catch(CLBNotFoundError, lambda exc: r)
lb_ids = [lb['id'] for lb in (yield _retry(get_clbs()))]
node_reqs = [_retry(get_clb_nodes(lb_id).on(error=gone([])))
for lb_id in lb_ids]
healthmon_reqs = [
_retry(get_clb_health_monitor(lb_id).on(error=gone(None)))
for lb_id in lb_ids]
all_nodes_hms = yield parallel(node_reqs + healthmon_reqs)
all_nodes, hms = all_nodes_hms[:len(lb_ids)], all_nodes_hms[len(lb_ids):]
lb_nodes = {
lb_id: [CLBNode.from_node_json(lb_id, node)
for node in nodes]
for lb_id, nodes in zip(lb_ids, all_nodes)}
clbs = {
str(lb_id): CLB(bool(health_mon))
for lb_id, health_mon in zip(lb_ids, hms) if health_mon is not None}
draining = [n for n in concat(lb_nodes.values())
if n.description.condition == CLBNodeCondition.DRAINING]
feeds = yield parallel(
[_retry(get_clb_node_feed(n.description.lb_id, n.node_id).on(
error=gone(None)))
for n in draining]
)
nodes_to_feeds = dict(zip(draining, feeds))
deleted_lbs = set([
node.description.lb_id
for (node, feed) in nodes_to_feeds.items() if feed is None])
def update_drained_at(node):
feed = nodes_to_feeds.get(node)
if node.description.lb_id in deleted_lbs:
return None
if feed is not None:
node.drained_at = extract_clb_drained_at(feed)
return node
nodes = map(update_drained_at, concat(lb_nodes.values()))
yield do_return((
list(filter(bool, nodes)),
pmap(keyfilter(lambda k: k not in deleted_lbs, clbs))))
def __init__(self, **kwargs):
self.attrs = pipe(
self.imports,
reversed,
map(vars),
merge,
keyfilter(compose(str.islower, first), ),
valfilter(callable),
)
self.attrs.update()
def get(token):
try:
customer_id = get_customer_id(token)
except:
return None
doc = frappe.get_doc("Customer", customer_id)
orders = frappe.db.exists("Sales Order", {"customer": customer_id})
return merge(
keyfilter(lambda x: x in CUSTOMER_FIELDS, doc.as_dict()),
{"can_register_messaging": bool(orders)},
)
def fit(self,
train_loader,
epochs,
val_loader=None,
send_weixin=False,
save_per_epochs=None,
callbacks=[]):
validate = val_loader is not None
# Weixin
if send_weixin:
self._enable_send_weixin()
# Create engine
engine = self._create_engine()
# Register events
engine.add_event_handler(Events.EPOCH_STARTED, self._log_epochs,
epochs)
if validate:
engine.add_event_handler(Events.EPOCH_COMPLETED, self._evaluate,
val_loader)
engine.add_event_handler(Events.EPOCH_COMPLETED, self._log_results,
validate)
# Set checkpoint
if save_per_epochs:
checkpoint_handler = ModelCheckpoint(self.save_path,
self.name,
save_per_epochs,
save_as_state_dict=True,
require_empty=False)
checkpoint_handler._iteration = self.epochs()
engine.add_event_handler(Events.EPOCH_COMPLETED,
checkpoint_handler, {"trainer": self})
for callback in callbacks:
engine.add_event_handler(Events.EPOCH_COMPLETED,
_callback_wrapper(callback), self)
# Run
engine.run(train_loader, epochs)
# Destroy
self._disable_send_weixin()
# Return history
hist = {
metric: hist[-epochs:]
for metric, hist in self.metric_history.items()
}
if not validate:
hist = keyfilter(lambda k: not k.startswith("val_"), hist)
return hist
def _prepare_kwargs(self, **kwargs):
"""Filter keywords with the function arguments. Call
any value that is callable, no arguments are applied
to these function.
"""
return valmap(
self._call_lazy_function,
merge(
keyfilter(partial(operator.contains, self.arguments), self.keywords),
kwargs,
)
)
def get_settings():
ahong_settings = frappe.get_single("Ahong eCommerce Settings")
website_settings = get_website_settings()
return merge(
keyfilter(lambda x: x in ["copyright", "footer_address"], website_settings),
{
"privacy": bool(ahong_settings.privacy),
"terms": bool(ahong_settings.terms),
"show_about_us": bool(ahong_settings.show_about_us),
"hide_build_info": bool(ahong_settings.hide_build_info),
},
)
def create(token, **kwargs):
decoded_token = get_decoded_token(token)
session_user = frappe.session.user
settings = frappe.get_single("Leiteng Website Settings")
if not settings.user:
frappe.throw(frappe._("Site setup not complete"))
frappe.set_user(settings.user)
uid = decoded_token["uid"]
customer_id = frappe.db.exists("Customer", {"le_firebase_uid": uid})
if customer_id:
frappe.throw(frappe._("Customer already created"))
args = keyfilter(
lambda x: x
in [
"customer_name",
"mobile_no",
"email",
"address_line1",
"address_line2",
"city",
"state",
"country",
"pincode",
],
kwargs,
)
doc = frappe.get_doc(
merge(
{
"doctype": "Customer",
"le_firebase_uid": uid,
"customer_type": "Individual",
"customer_group": frappe.db.get_single_value(
"Selling Settings", "customer_group"
),
"territory": frappe.db.get_single_value(
"Selling Settings", "territory"
),
},
args,
)
).insert()
auth.set_custom_user_claims(uid, {"customer": True}, app=app)
frappe.set_user(session_user)
return pick(["name", "customer_name"], doc.as_dict())
def _(dictionary):
try:
parameters = pipeline(
dictionary,
[
keyfilter(lambda k: k != '__type'),
valmap(json_deserialize_types),
],
)
Class = get_member_by_path(dictionary['__type'])
instance = make_instance(Class)
for key, value in parameters.items():
setattr(instance, key, json_deserialize_types(value))
return instance
except KeyError:
return valmap(json_deserialize_types, dictionary)
def json_serialize_types(value):
try:
value.__dict__
except AttributeError:
return value
return {
'__type': type(value).__module__ + "." + type(value).__name__,
**pipeline(
value.__dict__,
[
keyfilter(lambda l: not l.startswith("_")),
json_serialize_types,
],
),
}
def set_items_from_reference(self):
ref_doc = frappe.get_doc(self.print_dt, self.print_dn)
self.items = []
for ref_item in ref_doc.items:
self.append(
"items",
merge(
keyfilter(
lambda x: x in
["item_code", "item_name", "qty", "batch_no"],
ref_item.as_dict(),
),
get_item_details(
ref_item.item_code,
ref_item.batch_no,
price_list=self.price_list,
),
),
)
def attach(self, trainer):
if not self.enabled:
return
if self.metrics is None:
metrics = trainer.test_metrics
elif isinstance(self.metrics, Sequence):
assert not isinstance(
self.metrics,
str), "Metrics can't be str, maybe wrap it in a list."
for m in self.metrics:
assert m in trainer.test_metrics, "%s is not in test_metrics" % m
metrics = keyfilter(lambda k: k in self.metrics,
trainer.test_metrics)
elif isinstance(self.metrics, Dict):
metrics = self.metrics
else:
raise ValueError("Invalid metrics, got %s" % self.metrics)
self.evaluator = create_supervised_evaluator(trainer.model, metrics,
trainer.device)
self.trainer = trainer
def get_all_scaling_group_servers(changes_since=None,
server_predicate=identity):
"""
Return tenant's servers that belong to any scaling group as
{group_id: [server1, server2]} ``dict``. No specific ordering is guaranteed
:param datetime changes_since: Get server since this time. Must be UTC
:param server_predicate: function of server -> bool that determines whether
the server should be included in the result.
:return: dict mapping group IDs to lists of Nova servers.
"""
def has_group_id(s):
return 'metadata' in s and isinstance(s['metadata'], dict)
def group_id(s):
return group_id_from_metadata(s['metadata'])
servers_apply = compose(keyfilter(lambda k: k is not None),
groupby(group_id), filter(server_predicate),
filter(has_group_id))
return get_all_server_details(changes_since).on(servers_apply)
def __init__(
self,
data=None,
index=None,
columns=None,
estimator=None,
parent=None,
feature_level=None,
copy=False,
extensions=[
'harness.python.ext.base.JinjaExtension',
'harness.python.ext.SciKit.SciKitExtension',
'harness.python.ext.Bokeh.BokehModelsExtension',
'harness.python.ext.Bokeh.BokehPlottingExtension',
'harness.python.ext.Bokeh.BokehChartsExtension'
],
):
kwargs = dict(
estimator=estimator,
parent=parent,
feature_level=feature_level,
extensions=extensions,
)
self.set_params(**kwargs)
for ext in self.extensions:
if not ext in self.env.extensions:
self.env.add_extension(ext)
ext = self.env.extensions[ext]
if (not (ext.mixin is None)
and not (ext.mixin in self.__class__.__bases__)):
self.__class__.__bases__ += (ext.mixin, )
kwargs = pipe(locals(),
keyfilter(partial(operator.contains, self._blacklist)),
valfilter(complement(lambda x: x is None)))
super().__init__(**kwargs)
def get_all_scaling_group_servers(changes_since=None,
server_predicate=identity):
"""
Return tenant's servers that belong to any scaling group as
{group_id: [server1, server2]} ``dict``. No specific ordering is guaranteed
:param datetime changes_since: Get server since this time. Must be UTC
:param server_predicate: function of server -> bool that determines whether
the server should be included in the result.
:return: dict mapping group IDs to lists of Nova servers.
"""
def has_group_id(s):
return 'metadata' in s and isinstance(s['metadata'], dict)
def group_id(s):
return group_id_from_metadata(s['metadata'])
servers_apply = compose(keyfilter(lambda k: k is not None),
groupby(group_id),
filter(server_predicate),
filter(has_group_id))
return get_all_server_details(changes_since).on(servers_apply)
def fit2(self, train_loader, epochs=1, save=None, callbacks=()):
engine = create_supervised_trainer(self.model, self.criterion,
self.optimizer, self.metrics,
self.device)
engine.add_event_handler(Events.ITERATION_STARTED,
self._lr_scheduler_step)
self._timer.attach(engine, start=Events.EPOCH_STARTED)
engine.add_event_handler(Events.EPOCH_STARTED, self._log_epochs,
epochs)
engine.add_event_handler(Events.EPOCH_COMPLETED, self._increment_epoch)
engine.add_event_handler(Events.EPOCH_COMPLETED, self._log_results)
# Set checkpoint
if save:
checkpoint_handler = save.parse(self)
engine.add_event_handler(Events.EPOCH_COMPLETED,
checkpoint_handler, {"trainer": self})
for callback in callbacks:
engine.add_event_handler(Events.EPOCH_COMPLETED, wrap(callback),
self)
# Run
engine.run(train_loader, epochs)
# Return history
hist = {
metric: hist[-epochs:]
for metric, hist in self.metric_history.items()
}
hist = keyfilter(lambda k: not k.startswith("val_"), hist)
return hist
def get_notes(token, so_name):
decoded_token = get_decoded_token(token)
customer_id = frappe.db.exists(
"Customer", {"le_firebase_uid": decoded_token["uid"]}
)
if not customer_id:
frappe.throw(frappe._("Customer does not exist on backend"))
if customer_id != frappe.db.get_value("Sales Order", so_name, "customer"):
frappe.throw(frappe._("Not allowed to view this document"))
get_dn_fields = compose(
keyfilter(
lambda x: x
in [
"name",
"partner",
"partner_name",
"scheduled_datetime",
"posting_datetime",
"total",
"total_taxes_and_charges",
"grand_total",
"rounding_adjustment",
"rounded_total",
"status",
]
),
first,
)
get_item_fields = compose(
list,
map(
keyfilter(
lambda x: x
in [
"name",
"item_code",
"item_name",
"item_group",
"rate",
"amount",
"so_detail",
]
)
),
map(lambda x: merge(x, {"name": x.get("child_name")})),
)
get_deliveries = compose(
lambda x: x.values(),
valmap(lambda x: merge(get_dn_fields(x), {"items": get_item_fields(x)})),
groupby("name"),
lambda x: frappe.db.sql(
"""
SELECT
dn.name,
dn.sales_partner AS partner,
sp.partner_name,
dn.le_scheduled_datetime AS scheduled_datetime,
TIMESTAMP(dn.posting_date, dn.posting_time) AS posting_datetime,
dn.total,
dn.total_taxes_and_charges,
dn.grand_total,
dn.rounding_adjustment,
dn.rounded_total,
dn.workflow_state AS status,
dni.name AS child_name,
dni.item_code,
dni.item_name,
dni.item_group,
dni.qty,
dni.rate,
dni.amount,
dni.so_detail
FROM `tabDelivery Note Item` AS dni
LEFT JOIN `tabDelivery Note` AS dn ON dn.name = dni.parent
LEFT JOIN `tabSales Partner` AS sp ON sp.name = dn.sales_partner
WHERE
dn.status < 2 AND
dn.workflow_state IN ('Pending', 'Completed') AND
dni.against_sales_order = %(against_sales_order)s
""",
values={"against_sales_order": x},
as_dict=1,
),
)
return get_deliveries(so_name)
def create(token, **kwargs):
decoded_token = get_decoded_token(token)
session_user = frappe.session.user
webapp_user = frappe.get_cached_value("Ahong eCommerce Settings", None,
"webapp_user")
if not webapp_user:
frappe.throw(frappe._("Site setup not complete"))
uid = decoded_token["uid"]
customer_id = frappe.db.exists("Customer", {"cm_firebase_uid": uid})
if customer_id:
frappe.throw(frappe._("Customer already created"))
args = keyfilter(
lambda x: x in [
"customer_name",
"mobile_no",
"email_id",
"address_line1",
"address_line2",
"city",
"state",
"country",
"pincode",
],
kwargs,
)
def insert_or_update():
existing = frappe.db.exists("Customer",
{"cm_mobile_no": args.get("mobile_no")})
if existing:
doc = frappe.get_doc("Customer", existing)
doc.update({
"customer_name": args.get("customer_name"),
"cm_firebase_uid": uid
})
if args.get("address_line1") and args.get("city"):
address = _create_address(existing, args)
doc.update({"customer_primary_address": address.get("name")})
print([args.get("email_id"), doc.customer_primary_contact])
if args.get("email_id") and doc.customer_primary_contact:
contact = frappe.get_doc("Contact",
doc.customer_primary_contact)
contact.add_email(args.get("email_id"), autosave=True)
doc.save(ignore_permissions=True)
return doc
frappe.set_user(webapp_user)
doc = frappe.get_doc(
merge(
{
"doctype":
"Customer",
"cm_firebase_uid":
uid,
"cm_mobile_no":
args.get("mobile_no"),
"customer_type":
"Individual",
"customer_group":
frappe.db.get_single_value("Selling Settings",
"customer_group"),
"territory":
frappe.db.get_single_value("Selling Settings",
"territory"),
},
args,
)).insert(ignore_permissions=True)
frappe.set_user(session_user)
return doc
doc = insert_or_update()
auth.set_custom_user_claims(uid, {"customer": True}, app=app)
return keyfilter(lambda x: x in CUSTOMER_FIELDS, doc.as_dict())
'remote_cloudtrail_bucket': bool,
}
}
}, required=True, extra=ALLOW_EXTRA)
OUTPUT_SCHEMA = Schema({
'output': ACCOUNT_LINK_PROVISIONED,
}, required=True, extra=ALLOW_EXTRA)
request_type = get_in(['event', 'RequestType'])
properties = get_in(['event', 'ResourceProperties'])
stacks = get_in(['event', 'ResourceProperties', 'Stacks'])
reactor_callback_url = get_in(['event', 'ResourceProperties', 'ReactorCallbackUrl'])
supported_metadata = {'Region', 'ExternalId', 'AccountId', 'AccountName', 'ReactorId', 'ReactorCallbackUrl'}
callback_metadata = keyfilter(lambda x: x in supported_metadata)
default_metadata = {
'version': '1',
'message_source': 'cfn',
}
#####################
#
# Coeffects, i.e. from the outside world
#
#####################
def coeffects(world):
return pipe(world,
coeffects_cfn)
def sanitize(d):
if d:
filtered = keyfilter(lambda k: k not in ["etag", "elapsed"], d)
return filtered
return d
def coeffects_s3(world):
response = s3.list_buckets()
return keyfilter(lambda x: x in {'Buckets'}, response)
def extract_dur_disp_tab(doc: Disp_dur) -> Disp_dur:
return z.keyfilter(lambda x: x in {'dispatchCount', 'duration'}, doc)
def pick(whitelist, d):
return keyfilter(lambda k: k in whitelist, d)
def fit(self,
train_loader,
epochs=1,
val_loader=None,
save=None,
iterations=None,
callbacks=()):
engine = create_supervised_trainer(self.model, self.criterion,
self.optimizer, self.metrics,
self.device)
self._attach_timer(engine)
engine.add_event_handler(Events.ITERATION_STARTED,
self._lr_scheduler_step)
engine.add_event_handler(Events.EPOCH_STARTED, self._log_epochs,
epochs)
if val_loader is not None:
if isinstance(val_loader, tuple):
val_loader, eval_per_epochs = val_loader
else:
eval_per_epochs = 1
evaluator = create_supervised_evaluator(self.model,
self.test_metrics,
self.device)
engine.add_event_handler(Events.EPOCH_COMPLETED, _evaluate,
evaluator, val_loader, eval_per_epochs)
engine.add_event_handler(Events.EPOCH_COMPLETED, self._increment_epoch)
engine.add_event_handler(Events.EPOCH_COMPLETED, self._log_results)
if val_loader is not None:
engine.add_event_handler(Events.EPOCH_COMPLETED,
self._log_val_results, evaluator,
eval_per_epochs)
# Set checkpoint
if save:
checkpoint_handler = save.parse(self)
engine.add_event_handler(Events.EPOCH_COMPLETED,
checkpoint_handler, {"trainer": self})
for callback in callbacks:
engine.add_event_handler(Events.EPOCH_COMPLETED, wrap(callback),
self)
if iterations:
engine.add_event_handler(Events.ITERATION_COMPLETED,
_terminate_on_iterations, iterations)
epochs = 1000
# Run
engine.run(train_loader, epochs)
# Return history
hist = {
metric: hist[-epochs:]
for metric, hist in self.metric_history.items()
}
if val_loader is None:
hist = keyfilter(lambda k: not k.startswith("val_"), hist)
return hist
def coeffects_organizations(world):
response = orgs.describe_organization()
return keyfilter(lambda x: x in {'Organization'}, response)
def coeffects_cur(world):
response = cur.describe_report_definitions()
return keyfilter(lambda x: x in {'ReportDefinitions'}, response)
def coeffects_cloudtrail(world):
response = ct.describe_trails()
return keyfilter(lambda x: x in {'trailList'}, response)
def get_clb_contents():
"""
Get Rackspace Cloud Load Balancer contents as list of `CLBNode`. CLB
health monitor information is also returned as a pmap of :obj:`CLB` objects
mapped on LB ID.
:return: Effect of (``list`` of :obj:`CLBNode`, `pmap` of :obj:`CLB`)
:rtype: :obj:`Effect`
"""
# If we get a CLBNotFoundError while fetching feeds, we should throw away
# all nodes related to that load balancer, because we don't want to act on
# data that we know is invalid/outdated (for example, if we can't fetch a
# feed because CLB was deleted, we don't want to say that we have a node in
# DRAINING with draining time of 0; we should just say that the node is
# gone).
def gone(r):
return catch(CLBNotFoundError, lambda exc: r)
lb_ids = [lb['id'] for lb in (yield _retry(get_clbs()))]
node_reqs = [
_retry(get_clb_nodes(lb_id).on(error=gone([]))) for lb_id in lb_ids
]
healthmon_reqs = [
_retry(get_clb_health_monitor(lb_id).on(error=gone(None)))
for lb_id in lb_ids
]
all_nodes_hms = yield parallel(node_reqs + healthmon_reqs)
all_nodes, hms = all_nodes_hms[:len(lb_ids)], all_nodes_hms[len(lb_ids):]
lb_nodes = {
lb_id: [CLBNode.from_node_json(lb_id, node) for node in nodes]
for lb_id, nodes in zip(lb_ids, all_nodes)
}
clbs = {
str(lb_id): CLB(bool(health_mon))
for lb_id, health_mon in zip(lb_ids, hms) if health_mon is not None
}
draining = [
n for n in concat(lb_nodes.values())
if n.description.condition == CLBNodeCondition.DRAINING
]
feeds = yield parallel([
_retry(
get_clb_node_feed(n.description.lb_id,
n.node_id).on(error=gone(None)))
for n in draining
])
nodes_to_feeds = dict(zip(draining, feeds))
deleted_lbs = set([
node.description.lb_id for (node, feed) in nodes_to_feeds.items()
if feed is None
])
def update_drained_at(node):
feed = nodes_to_feeds.get(node)
if node.description.lb_id in deleted_lbs:
return None
if feed is not None:
node.drained_at = extract_clb_drained_at(feed)
return node
nodes = map(update_drained_at, concat(lb_nodes.values()))
yield do_return((list(filter(bool, nodes)),
pmap(keyfilter(lambda k: k not in deleted_lbs, clbs))))