def components():
graph = lk.createVertices(size=1000).createRandomEdges(
degree=2, seed=pp('${date.hashCode()}'))
component_metrics = graph.findConnectedComponents().sql(
pp('''
select
"$date" as date_id,
max(size) as max_size,
min(size) as min_size,
count(*) as num_components
from `connected_components.vertices`'''))
return dict(metrics=component_metrics)
def components(sec_collector, table):
graph = table.useTableAsGraph(src='src', dst='dst')
component_metrics = graph.findConnectedComponents().sql(
pp('''
select
"$date" as date_id,
max(size) as max_size,
min(size) as min_size,
count(*) as num_components
from `connected_components.vertices`'''))
exp = component_metrics.exportToParquet(path=pp(output_folder +
'/${date}'))
exp.register(sec_collector)
return dict(metrics=component_metrics)
def parametric_ws(self):
from lynx.kite import pp, text
lk = lynx.kite.LynxKite()
state = lk.createExampleGraph().sql(
pp('select name from `vertices` where age = $ap')).output(name='table')
ws = lynx.kite.Workspace([state], name='ws params', ws_parameters=[text('ap', '18.2')])
return ws
def test_parametric_parameters(self):
from lynx.kite import pp
lk = lynx.kite.LynxKite()
graph = lk.createExampleGraph().deriveGraphAttribute(
output='pi', expr=pp('${2+1.14}')).get_graph()
scalars = {s.title: lk.get_graph_attribute(s.id) for s in graph.graphAttributes}
self.assertEqual(scalars['pi'].string, '3.14')
def save(table):
table_with_timestamp = table.sql(
pp('''
select
"$date" as date_id,
cast(supporters as integer) as supporters,
cast(amount as integer) as amount
from input'''))
return dict(hourly=table_with_timestamp)
def components(table):
graph = table.useTableAsGraph(src='src', dst='dst')
component_metrics = graph.findConnectedComponents().sql(
pp('''
select
"$date" as date_id,
max(size) as max_size,
min(size) as min_size,
count(*) as num_components
from `connected_components.vertices`'''))
return dict(metrics=component_metrics)
def save_graph_to_snapshot(sec, graph):
graph.sql('select * from vertices').saveToSnapshot(path=pp('$snapshot_path')).register(sec)
def save_and_return_graph(sec, graph):
graph.sql('select * from vertices').saveToSnapshot(path=pp('$snapshot_path')).register(sec)
return dict(graph=graph)
def csv_exporter(sec, table):
table.exportToCSV(path=pp('$export_path')).register(sec)
def filter_table(table):
query = pp(
'select name, income from input where ${field} > ${limit}')
out = table.sql(query)
return dict(table=out)
def add_ws():
return (lk.createVertices(size='5').deriveGraphAttribute(
output='total', expr=pp('${a.toInt+b.toInt+c.toInt}')))
def f(t):
return t.sql1(sql=pp('select age from vertices where name == "$name"'))
def g(x):
return f(x, p=pp('$p'))
def f(x):
return x.sql1(sql=pp('select $p from vertices'))
def g(t):
return f(t, query=pp('select $column from vertices limit 1'))