lazy-graph 0.3.9

lazy graph framework

lazy-graph

The lazy-graph is a Python package that enables lazy evaluation and provides additional features for updating upstream values and copying the entire lazy graph.

Install

Please copy or link this folder directly. Alternatively, you can use pip to install the lazy-graph distribution with the command pip install lazy_graph.

Documents

Simple example

from lazy import Root, Node


def add(a, b):
    print(f"calculating {a} + {b}")
    return a + b


print("create nodes")
a = Root(1)
b = Root(2)
c = Node(add, a, b)
print("get the value")
print(f"c is {c()}")

create nodes
get the value
calculating 1 + 2
c is 3

The value of node c is calculated when it is needed.

Update upstream

print("create nodes")
a = Root(1)
b = Root(2)
c = Node(add, a, b)
print("get the value")
print(f"c is {c()}")
print("get the value again")
print(f"c is {c()}")
print("update upstream")
a.reset(4)
print("get the new value")
print(f"c is {c()}")

create nodes
get the value
calculating 1 + 2
c is 3
get the value again
c is 3
update upstream
get the new value
calculating 4 + 2
c is 6

The value of node c will only be recalculated if its upstream is updated, and retrieving its value multiple times will not result in duplicate calculations.

Normal argument or keyword argument are also available

def add4(a, b, c, d):
    print(f"calculating {a} + {b} + {c} + {d}")
    return a + b + c + d


print("create nodes")
a = Root(1)
c = Root(3)
z = Node(add4, a, 2, c=c, d=4)
print("get the value")
print(f"c is {z()}")

create nodes
get the value
calculating 1 + 2 + 3 + 4
c is 10

Both position arguments and keyword arguments are supported, and they can also be mixed with normal arguments.

Copy the lazy graph

from lazy import Copy

print("create nodes")
a = Root(1)
b = Root(2)
c = Node(add, a, b)
print("get the value")
print(f"c is {c()}")

print("copy lazy graph")
copy = Copy()
new_a = copy(a)
new_b = copy(b)
new_c = copy(c)

print("get the new value")
print(f"new c is {new_c()}")

print("reset value")
a.reset(4)
new_a.reset(8)
print("get the old value and new value")
print(f"c is {c()}, new c is {new_c()}")

create nodes
get the value
calculating 1 + 2
c is 3
copy lazy graph
get the new value
new c is 3
reset value
get the old value and new value
calculating 4 + 2
calculating 8 + 2
c is 6, new c is 10

Copy the same relation between node a, b, and c to a new lazy graph. The new graph shares the initial value from the original nodes but does not have any other effects on each other.

Please note that you can copy a part of the lazy graph. For example, copy b and c here while sharing the same a. This means that updating a will result in both c and new_c being updated, while b or new_b will only affect either c or new_c.

copy = Copy()
new_b = copy(b)
new_c = copy(c)

print(f"a is {a()}")
print(f"b is {b()}, new b is {new_b()}")
print(f"c is {c()}, new c is {new_c()}")
b.reset(8)
print(f"c is {c()}, new c is {new_c()}")
new_b.reset(10)
print(f"c is {c()}, new c is {new_c()}")
a.reset(6)
print(f"c is {c()}, new c is {new_c()}")

a is 4
b is 2, new b is 2
c is 6, new c is 6
calculating 4 + 8
c is 12, new c is 6
calculating 4 + 10
c is 12, new c is 14
calculating 6 + 8
calculating 6 + 10
c is 14, new c is 16

If you copy the same node using the same copy object twice, you will get the same copied node.

new_c = copy(c)
new_c_2 = copy(c)
print(id(new_c) == id(new_c_2))

True

When copying a lazy graph, it is always necessary to copy the upstream nodes before the downstream nodes are copied, so that this package can maintain the dependencies.

Check whether a node has been calculated

a = Root(1)
b = Root(2)
c = Node(add, a, b)
print(bool(c))
print("c is", c())
print(bool(c))

False
calculating 1 + 2
c is 3
True