macro-kit
macro-kit is a package for efficient macro recording and metaprogramming in Python using abstract syntax tree (AST).
The design of AST in this package is strongly inspired by Julia metaprogramming. Similar methods are also implemented in builtin ast module but macro-kit is more focused on the macro generation and customization.
Installation
- use pip
pip install macro-kit
- from source
pip install git+https://github.com/hanjinliu/macro-kit
Examples
- Define a macro-recordable function
from macrokit import Macro, Expr, Symbol
macro = Macro()
@macro.record
def str_add(a, b):
return str(a) + str(b)
val0 = str_add(1, 2)
val1 = str_add(val0, "xyz")
macro
[Out]
var0x24fdc2d1530 = str_add(1, 2)
var0x24fdc211df0 = str_add(var0x24fdc2d1530, 'xyz')
# substitute identifiers of variables
# var0x24fdc2d1530 -> x
macro.format([(val0, "x")])
[Out]
x = str_add(1, 2)
var0x24fdc211df0 = str_add(x, 'xyz')
# substitute to _dict["key"], or _dict.__getitem__("key")
expr = Expr(head="getitem", args=[Symbol("_dict"), "key"])
macro.format([(val0, expr)])
[Out]
_dict['key'] = str_add(1, 2)
var0x24fdc211df0 = str_add(_dict['key'], 'xyz')
- Record class
macro = Macro()
@macro.record
class C:
def __init__(self, val: int):
self.value = val
@property
def value(self):
return self._value
@value.setter
def value(self, new_value: int):
if not isinstance(new_value, int):
raise TypeError("new_value must be an integer.")
self._value = new_value
def show(self):
print(self._value)
c = C(1)
c.value = 5
c.value = -10
c.show()
[Out]
-10
macro.format([(c, "ins")])
[Out]
ins = C(1)
ins.value = -10 # setattr (and setitem) will not be recorded in duplicate
var0x7ffed09d2cd8 = ins.show()
macro.eval({"C": C})
[Out]
-10
- Record module
import numpy as np
macro = Macro()
np = macro.record(np) # macro-recordable numpy
arr = np.random.random(30)
mean = np.mean(arr)
macro
[Out]
var0x2a0a2864090 = numpy.random.random(30)
var0x2a0a40daef0 = numpy.mean(var0x2a0a2864090)
from dask import array as da
dask_macro = macro.format([(np, "da")])
dask_macro
[Out]
var0x2a0a2864090 = da.random.random(30)
var0x2a0a40daef0 = da.mean(var0x2a0a2864090)
output = {}
dask_macro.eval({"da": da}, output)
output
[Out]
{:da:
,
:var0x2a0a2864090: dask.array
,
:var0x2a0a40daef0: dask.array
}
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