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
}
2 Dec 5, 2021
5 Nov 8, 2021
39 Jan 5, 2023
3 Jul 15, 2021
12 Sep 1, 2022
7 Sep 8, 2022
1.7k Jan 4, 2023
36 Dec 14, 2022
147 Dec 29, 2022
2 Feb 11, 2022
8 Feb 23, 2022
4 Aug 31, 2022
3 Nov 28, 2021
8 Nov 27, 2022
0 Feb 24, 2022
1 Nov 30, 2021
6 Aug 26, 2022
1 Oct 11, 2022
12 Dec 15, 2022
4.3k Jan 05, 2023
6 Dec 08, 2022
1 Oct 17, 2021
6 Aug 06, 2021
4 Sep 24, 2021
3 Jul 05, 2022
158 Dec 22, 2022
18 Dec 17, 2022
1 Nov 03, 2022
2 Nov 02, 2022