Arc Modifier Constants

# Return all arcs of type 'knows' regardless of modifier
graph.Neighborhood( "Alice", arc=("knows", D_OUT, M_ANY) ) )

# These are equivalent
graph.Connect( "Alice", "knows", "Bob" )  # M_STAT, value=1 implied
graph.Connect( "Alice", ("knows", M_STAT), "Bob" ) # value=1 implied

# This is illegal, will raise pyvgx.ArcError
graph.Connect( "Alice", ("knows", M_STAT, 123), "Bob" )

graph.Connect( "Alice", ("skillset", M_SIM, 0.8), "Bob" )
graph.Connect( "Alice", ("skillset", M_SIM, 0.3), "Charlie" )

# Some distances, relationship type should indicate unit
graph.Connect( "Boston", ("kilometers", M_DIST, 306.0), "New York" )
graph.Connect( "Earth", ("lightyears", M_DIST, 8.611), "Sirius" )
graph.Connect( "coffee", ("edit", M_DIST, 3), "kaffe" )

graph.Connect( "A", ("lsh", M_LSH, 0xFFFFFFFF), "B" )
graph.Connect( "A", ("lsh", M_LSH, 0x000FFFFF), "C" )
graph.Connect( "A", ("lsh", M_LSH, 0xFFFFF000), "D" )

graph.Neighborhood( "A", arc=("lsh", D_OUT, M_LSH, V_LTE, (0xFFFFFF33, 4)) )
# -> ['B']

graph.Neighborhood( "A", arc=("lsh", D_OUT, M_LSH, V_LTE, (0xFFFFFF33, 12)) )
# -> ['B', 'D']

graph.Connect( "A", ("boost", M_INT, -50), "B" )

graph.Connect( "A", ("related", M_UINT, 1000), "B" )

graph.Connect( "A", ("weight", M_FLT, 5.471), "B" )

graph.Connect( "Alice", ("called", M_CNT), "Bob" ) # -> 1
graph.Connect( "Alice", ("called", M_CNT), "Bob" ) # -> 2
graph.Connect( "StoreA", ("inventory", M_CNT, 100), "ItemX" ) # -> 100
graph.Connect( "StoreA", ("inventory", M_CNT, -1), "ItemX" ) # -> 99

graph.Connect( "QueryA", ("boost", M_ACC, 14.0), "ItemX" )  # -> 14.0
graph.Connect( "QueryA", ("boost", M_ACC, -3.5), "ItemX" )  # -> 10.5
graph.Connect( "QueryA", ("boost", M_ACC, 2.37), "ItemX" )  # -> 12.87

# Populate graph with different types of arcs
for n in range(4):
    via = "via_%d" % n
    graph.Connect( "A", "to", via)
    for m in range(4):
        leaf = "leaf_%d" % m
        graph.Connect( via, ("score",M_INT,n*m), leaf )
        graph.Connect( via, ("score",M_UINT,n), leaf )
        graph.Connect( via, ("score",M_DIST,n/float(m+1)), leaf )

# Sum up all integer values terminating at leaf nodes.
# Returns four values, one for each aggregated leaf node.
# Values for integer type arcs are summed, i.e. M_INT and M_UINT in this case.
graph.Neighborhood(
    A",
    "to",
    sortby   = S_VAL,
    result   = R_LIST,
    fields   = F_ID|F_VAL,
    collect  = False,
    neighbor = {
        'arc'     : ("*",D_OUT,M_ANY),
        'collect' : True
    },
    aggregate = {
        'mode':'sum',
        'arc':("*",D_ANY,M_INTAGGR)
    }
)

# Populate graph with different types of arcs
for n in range(4):
    via = "via_%d" % n
    graph.Connect( "A", "to", via)
    for m in range(4):
        leaf = "leaf_%d" % m
        graph.Connect( via, ("score",M_INT,n*m), leaf )
        graph.Connect( via, ("score",M_UINT,n), leaf )
        graph.Connect( via, ("score",M_DIST,n/float(m+1)), leaf )

# Sum up all float values terminating at leaf nodes.
# Returns four values, one for each aggregated leaf node.
# Values for float type arcs are summed, i.e. only M_DIST in this case.
graph.Neighborhood(
    "A",
    "to",
    sortby   = S_VAL,
    result   = R_LIST,
    fields   = F_ID|F_VAL,
    collect  = False,
    neighbor = {
        'arc'     : ("*",D_OUT,M_ANY),
        'collect' : True
    },
    aggregate = {
        'mode' : 'sum',
        'arc'  : ("*",D_ANY,M_FLTAGGR)
    }
 )

# creation time = now
graph.Connect( "Alice", ("called",M_TMC), "Bob" )  # -> now ts

graph.Connect( "Alice", ("called",M_CNT), "Bob" )  # -> 1
graph.Connect( "Alice", ("called",M_CNT), "Bob" )  # -> 2

# illegal, will raise pyvgx.ArcError
graph.Connect( "Alice", ("called",M_TMC), "Bob" )

graph.Connect( "Alice", ("called",M_CNT), "Bob" )  # -> 1
graph.Connect( "Alice", ("called",M_TMM), "Bob" )  # -> now ts
graph.Connect( "Alice", ("called",M_CNT), "Bob" )  # -> 2
graph.Connect( "Alice", ("called",M_TMM), "Bob" )  # -> now ts

# Create relationships that will automatically expire in two minutes

# Manual
now = int( time.time() )
ttl = 120
graph.Connect( "Alice", ("query", M_CNT, 5), "shoes" )
graph.Connect( "Alice", ("query", M_TMX, now + ttl), "shoes" )

# Automatic
graph.Connect( "Bob", ("query", M_CNT, 3), "pants" )
graph.Connect( "Bob", ("query", M_TMX, -120), "pants" )

# wait 2 minutes...
graph.Adjacent( "Alice", "query", "shoes" )  # -> False
graph.Adjacent( "Bob", "query", "pants" )  # -> False

# A -[link M_INT 123]-> B
# A -[link M_TMC 1749156031]-> B
# A -[link M_TMM 1749156031]-> B
graph.Connect( "A", ("link", M_INT|M_AUTOTM, 123), "B" )

graph.Neighborhood("A", neighbor="B", fields=F_AARC )
# ['( A )-[ to <M_TMC> 1749156031 ]->( C )',
#  '( A )-[ to <M_TMM> 1749156031 ]->( C )',
#  '( A )-[ to <M_INT> 200 ]->( C )']

# A -> B (regular arc)
# A -> C (without implicit reverse arc)
graph.Connect( "A", ("to", M_INT, 100), "B" )
graph.Connect( "A", ("to", M_INT|M_FWDONLY, 200), "C" )

# A connects to B and C
graph.Neighborhood( "A", arc=D_OUT, fields=F_AARC )
# -> ['( A )-[ to <M_INT> 100 ]->( B )',
#     '( A )-[ to <M_INT|M_FWDONLY> 200 ]->( C )']

# B has a normal reverse implicit arc to A
graph.Neighborhood( "B", arc=D_IN, fields=F_AARC )
# -> ['( B )<-[ to <M_INT> 100 ]-( A )']

# C has no implicit arc back to A
graph.Neighborhood( "C", arc=D_IN, fields=F_AARC )
# -> []

# C still records indegree
graph.Degree( "C", arc=D_IN )
# -> 1