Implements
forward-oriented programming
in Python. This shares configuration arguments across multiple components
and determines their values after the main business logic.
Dependencies: makefun
Developer: Emmanouil (Manios) Krasanakis
Contant: maniospas@hotmail.com
Features
Quickstart
Enable lazy execution and automatically annotate arguments with defaults as aspects:
from pyfop import lazy, autoaspects
@lazy
@autoaspects
def affine(x, scale=1, offset=0):
return x*scale + offsetProduce results with python code:
GM = (affine(2)*affine(8))**0.5Set aspect values of previous code:
print(GM(scale=3)) # 12Advanced features
Internal call of lazy methods while exposing their aspects.
@lazy
@autoaspects
def gm(x, y, affine=affine): # pass the method as an argument
return (affine(x)*affine(y))**0.5
GM = gm(2, 8)
print(GM(scale=3)) # 12Print list of aspects.
print(GM.get_input_context(scale=3))
# context:
# - scale:
# value: 3,
# priority: Priority.HIGH
# shares: 1
# - offset:
# value: 1,
# priority: Priority.INCREASED
# shares: 4Aspects are shared between everything contributing to the result.
@lazy
@autoaspects
def square(x, scale=1):
return scale*x*x
print(affine(2)(scale=2)) # 4
print((affine(2)+square(1))(scale=2)) # 5Priority-based selection between defaults.
@lazy
def logpp(x, offset=Aspect(1, Priority.INCREASED)):
import math
return math.log(x+offset)/math.log(2)
result = affine(2)+log(3)
print(result(scale=2)) # 5+2=7Toggle caching.
@lazy # automatically performs caching
def inc(x):
print("running")
return x+1
print(inc(2)())
# running
# 3
print(inc(2)())
# 3
print(inc(3)())
# running
# 4@lazy_no_cache # disables caching
def inc(x):
print("running")
return x+1
print(inc(2)())
# running
# 3
print(inc(2)())
# running
# 3
print(inc(3)())
# running
# 4
