## Python data structures to lisp

| categories: | tags: | View Comments

I have an idea in mind that would use the output of python scripts in lisp functions. Xah Lee posted an idea for writing emacs commands in scripting languages . In this post I want to explore an extension of the idea, where a Python script will return output that can be read in Lisp, e.g. we can convert a Python list to a lisp list, or a dictionary to an a-list or p-list. I can already see that simple data structures will be "simple", and arbitrary data structures will offer a lot of challenges, e.g. nested lists or dictionaries…

If I could add some custom functions to the basic builtin types in Python, then I could use another approach to format python objects as lisp data types. This isn't recommended by Pythonistas, but I guess they don't want to use lisp as much as I do ;) I found this approach to modifying builtins:

We use that almost verbatim here to get what I want. This is a super low level way to add functions to the builtins. I add some simple formatting to floats, ints and strings. I add a more complex recursive formatting function to lists, tuples and dictionaries. A dictionary can be represented as an alist or plist. Both examples are shown, but I leave the alist version commented out. Finally, we add a lispify function to numpy arrays.

import ctypes as c

_fields_ = [('HEAD', c.c_ubyte * (object.__basicsize__ -
c.sizeof(c.c_void_p))),
('ob_type', c.c_void_p)]

_get_dict = c.pythonapi._PyObject_GetDictPtr
_get_dict.restype = c.POINTER(c.py_object)
_get_dict.argtypes = [c.py_object]

def get_dict(object):
return _get_dict(object).contents.value

get_dict(str)['lisp'] = lambda s:'"{}"'.format(str(s))
get_dict(float)['lisp'] = lambda f:'{}'.format(str(f))
get_dict(int)['lisp'] = lambda f:'{}'.format(str(f))

import collections
import numpy as np

def lispify(L):
"Convert a Python object L to a lisp representation."
if (isinstance(L, str)
or isinstance(L, float)
or isinstance(L, int)):
return L.lisp()
elif (isinstance(L, list)
or isinstance(L, tuple)
or isinstance(L, np.ndarray)):
s = []
for element in L:
s += [element.lisp()]
return '(' + ' '.join(s) + ')'
elif isinstance(L, dict):
s = []
for key in L:
# alist format
# s += ["({0} . {1})".format(key, L[key].lisp())]
# plist
s += [":{0} {1}".format(key, L[key].lisp())]
return '(' + ' '.join(s) + ')'

get_dict(list)['lisp'] = lispify
get_dict(tuple)['lisp'] = lispify
get_dict(dict)['lisp'] = lispify
get_dict(np.ndarray)['lisp'] = lispify


Let us test these out.

from pylisp import *
a = 4.5
print int(a).lisp()
print a.lisp()
print "test".lisp()

print [1, 2, 3].lisp()
print (1, 2, 3).lisp()

print [[1, 3], (5, 6)].lisp()

print {"a": 5}.lisp()
print [[1, 3], (5, 6), {"a": 5, "b": "test"}].lisp()

A = np.array([1, 3, 4])
print A.lisp()
print ({"tree": [5, 6]}, ["a", 4, "list"], 5, 2.0 / 3.0).lisp()

4
4.5
"test"
(1 2 3)
(1 2 3)
((1 3) (5 6))
(:a 5)
((1 3) (5 6) (:a 5 :b "test"))
(1 3 4)
((:tree (5 6)) ("a" 4 "list") 5 0.666666666667)


Now, is that better than a single lisp function with a lot of conditionals to handle each type? I am not sure. This seems to work pretty well.

Here is how I imagine using this idea. We would have some emacs-lisp variables and use them to dynamically generate a python script. We run the python script, capturing the output, and read it back in as a lisp data structure. Here is a simple kind of example that generates a dictionary.

(let* ((elisp-var 6)
(result)
(script (format "
from pylisp import *
print {x: [2*y for y in range(x)] for x in range(1, %s)}.lisp()
" elisp-var)))

;; start a python process
(run-python)
script)))
(plist-get result :5))

(0 2 4 6 8)


That seems to work pretty well. One alternative idea to this is Pymacs , which I have written about before . This project isn't currently under active development, and I ran into some difficulties with it before.

Here we can solve the problem I previously posed and get the result back as an elisp float, and then reuse the result

(let* ((myvar 3)
(script (format "from pylisp import *
from scipy.optimize import fsolve
def objective(x):
return x - 5

ans, = fsolve(objective, %s)
print ans.lisp()" myvar)))
(run-python)
script)))
(- 5 result))

0.0


Bottom line: we can write python code in lisp functions that are dynamically updated, execute them, and get lisp data structures back for simple data types. I think that could be useful in some applications, where it is easier to do parsing/analysis in Python, but you want to do something else that is easier in Lisp.