Not iterable object in python - python

I am trying to write a function that returns the variables contained in a class of type Rule. I need to iterate through it and get all variables and store them in a set.
class Rule:
# head is a function
# body is a *list* of functions
def __init__(self, head, body):
self.head = head
self.body = body
def __str__(self):
return str(self.head) + ' :- ' + str(self.body)
def __eq__(self, other):
if not isinstance(other, Rule):
return NotImplemented
return self.head == other.head and self.body == other.body
def __hash__(self):
return hash(self.head) + hash(self.body)
class RuleBody:
def __init__(self, terms):
assert isinstance(terms, list)
self.terms = terms
def separator(self):
return ','
def __str__(self):
return '(' + (self.separator() + ' ').join(
list(map(str, self.terms))) + ')'
def __eq__(self, other):
if not isinstance(other, RuleBody):
return NotImplemented
return self.terms == other.terms
def __hash__(self):
return hash(self.terms)
My function is the following:
def variables_of_clause (self, c : Rule) -> set :
returnSet = set()
l = getattr(c, 'body')
for o in l:
returnSet.add(o)
Testing function
# The variables in a Prolog rule p (X, Y, a) :- q (a, b, a) is [X; Y]
def test_variables_of_clause (self):
c = Rule (Function ("p", [Variable("X"), Variable("Y"), Atom("a")]),
RuleBody ([Function ("q", [Atom("a"), Atom("b"), Atom("a")])]))
#assert
(self.variables_of_clause(c) == set([Variable("X"), Variable("Y")]))
I keep getting an error that says: TypeError: 'RuleBody' is not iterable.

RuleBody.terms is a list, not RuleBody, you can iterate over RuleBody.terms instead, however, you can make your RuleBody class iterable (by basically making it return RuleBody.terms's elements), using the __iter__ method:
class RuleBody:
... # everything
...
def __iter__(self):
return iter(self.terms)

Related

Generalized __eq__() method in Python

I'd like to create a generalized __eq__() method for the following Class. Basically I'd like to be able to add another property (nick) without having to change __eq__()
I imagine I can do this somehow by iterating over dir() but I wonder if there is a way to create a comprehension that just delivers the properties.
class Person:
def __init__(self, first, last):
self.first=first
self.last=last
#property
def first(self):
assert(self._first != None)
return self._first
#first.setter
def first(self,fn):
assert(isinstance(fn,str))
self._first=fn
#property
def last(self):
assert(self._last != None)
return self._last
#last.setter
def last(self,ln):
assert(isinstance(ln,str))
self._last=ln
#property
def full(self):
return f'{self.first} {self.last}'
def __eq__(self, other):
return self.first==other.first and self.last==other.last
p = Person('Raymond', 'Salemi')
p2= Person('Ray', 'Salemi')
You could use __dict__ to check if everything is the same, which scales for all attributes:
If the objects are not matching types, I simply return False.
class Person:
def __init__(self, first, last, nick):
self.first = first
self.last = last
self.nick = nick
def __eq__(self, other):
return self.__dict__ == other.__dict__ if type(self) == type(other) else False
>>> p = Person('Ray', 'Salemi', 'Ray')
>>> p2= Person('Ray', 'Salemi', 'Ray')
>>> p3 = Person('Jared', 'Salemi', 'Jarbear')
>>> p == p2
True
>>> p3 == p2
False
>>> p == 1
False
You can get all the properties of a Class with a construct like this:
from itertools import chain
#classmethod
def _properties(cls):
type_dict = dict(chain.from_iterable(typ.__dict__.items() for typ in reversed(cls.mro())))
return {k for k, v in type_dict.items() if 'property' in str(v)}
The __eq__ would become something like this:
def __eq__(self, other):
properties = self._properties() & other._properties()
if other._properties() > properties and self._properties() > properties:
# types are not comparable
return False
try:
return all(getattr(self, prop) == getattr(other, prop) for prop in properties)
except AttributeError:
return False
The reason to work with the reversed(cls.mro()) is so something like this also works:
class Worker(Person):
#property
def wage(self):
return 0
p4 = Worker('Raymond', 'Salemi')
print(p4 == p3)
True
you can try to do this, it will also work if you want eq inside dict and set
def __eq__(self, other):
"""Overrides the default implementation"""
if isinstance(self, other.__class__):
return self.__hash__() == other.__hash__()
return NotImplemented
def __hash__(self):
"""Overrides the default implementation,
and set which fieds to use for hash generation
"""
__make_hash = [
self.first
]
return hash(tuple(sorted(list(filter(None, __make_hash)))))

How can I change the string object inside a string object?

I'm trying to create a mutable string object by just subclassing str (Unlike the answer to this other question).
Here's my code so far:
class mstr(str):
def __new__(self, s):
self.s = list(s)
return str.__new__(self, s)
def __getitem__(self, index):
return self.s[index]
def __setitem__(self, index, value):
self.s[index] = value
def __eq__(self, other):
return ''.join(self.s) == other
def __ne__(self, other):
return ''.join(self.s) != other
def __lt__(self, other):
return len(self.s) < len(other)
def __gt__(self, other):
return len(self.s) > len(other)
def __le__(self, other):
return len(self.s) <= len(other)
def __ge__(self, other):
return len(self.s) >= len(other)
def __add__(self, other):
return ''.join(self.s) + other
def __mul__(self, other):
return ''.join(self.s) * other
def __hash__(self):
return hash(''.join(self.s))
def __str__(self):
return ''.join(self.s)
def main():
s = mstr("Hello ")
s[5] = " World!"
print(s)
if __name__ == '__main__':
main()
By just outputting this example, it's easy to be fooled by the __ str __ return value:
Hello World!
It's also easy to be fooled by the return value of __ add __ :
print(s + " Bloody madness!")
Output:
Hello World! Bloody madness!
But the immutable truth is revealed once we pass the mstr itself by the other argument of __ add __, as an example:
print(s + s)
Output:
Hello World!Hello
Removing all the extra methods:
class mstr(str):
def __new__(self, s):
self.s = list(s)
return str.__new__(self, s)
def __setitem__(self, index, value):
self.s[index] = value
self = ''.join(self.s) # Foolish attepmt.
Output of print(s) is just "Hello ".
So, how can I change the string object inside the string object? I mean, WHERE is the string actual and physical content stored in str or object or whatever? Wherever that is, I want to assign there.
It's in here:
typedef struct {
PyObject_VAR_HEAD
long ob_shash;
int ob_sstate;
char ob_sval[1]; // This part. (Not actually one char.)
/* ... */
} PyStringObject;
Unless you want to screw with the memory directly with ctypes or something, you can't get at it. If you do screw with it, weird things will break, because the assumption that that data is immutable isn't waived for string subclasses.

What is the "metaclass" way to do this?

I want to write a program that accepts as input a number p and produces as output a type-constructor for a number that obeys integer arithmetic modulo p.
So far I have
def IntegersModP(p):
N = type('IntegersMod%d' % p, (), {})
def __init__(self, x): self.val = x % p
def __add__(a, b): return N(a.val + b.val)
... (more functions) ...
attrs = {'__init__': __init__, '__add__': __add__, ... }
for name, f in attrs.items():
setattr(N, name, f)
return N
This works fine, but I'd like to know what the Pythonic way to do this is, which I understand would use metaclasses.
Like this:
def IntegerModP(p): # class factory function
class IntegerModP(object):
def __init__(self, x):
self.val = x % p
def __add__(a, b):
return IntegerModP(a.val + b.val)
def __str__(self):
return str(self.val)
def __repr__(self):
return '{}({})'.format(self.__class__.__name__, self.val)
IntegerModP.__name__ = 'IntegerMod%s' % p # rename created class
return IntegerModP
IntegerMod4 = IntegerModP(4)
i = IntegerMod4(3)
j = IntegerMod4(2)
print i + j # 1
print repr(i + j) # IntegerMod4(1)
Metaclasses are for when your class needs to behave differently from a normal class or when you want to alter the behavior of the class statement. Neither of those apply here, so there's really no need to use a metaclass. In fact, you could just have one ModularInteger class with instances that record their value and modulus, but assuming you don't want to do that, it's still easy to do this with an ordinary class statement:
def integers_mod_p(p):
class IntegerModP(object):
def __init__(self, n):
self.n = n % IntegerModP.p
def typecheck(self, other):
try:
if self.p != other.p:
raise TypeError
except AttributeError:
raise TypeError
def __add__(self, other):
self.typecheck(other)
return IntegerModP(self.n + other.n)
def __sub__(self, other):
...
IntegerModP.p = p
IntegerModP.__name__ = 'IntegerMod{}'.format(p)
return IntegerModP

Allowing User to Input Variables (Python)

I am working on a project using PuLP and I am trying to create a terminal prompt to allow users to input their data and then my Python program will change the input to code readable by PuLP. To do this I must allow users to input:
2*a + 3*b <= c
and my code will eval() this code as well as creating variables a, b and c such
a = LpVariable("a",None,None,LpContinuous)
b = LpVariable("b",None,None,LpContinuous)
c = LpVariable("c",None,None,LpContinuous)
any ideas? I've tried using exec() but it does not seem to like this much.
at the moment I'm getting the input via:
print "Please enter your constraints 1 at a time and enter '#' when done:"
control = True
while (control):
entry = raw_input('-->')
entryS = ""
entryS += entry
so the string 2*a+3*B <= c is stored as entryS
Using eval() might not be such a good idea, but if you insist (Python 3):
call = lambda f: lambda *args: f(*args)
flip = lambda f: lambda *args: f(*reversed(args))
class Expression:
def __repr__(self):
return '{}({})'.format(type(self).__name__, self)
class BinaryExpression(Expression):
def __init__(self, left, right):
self.left = promote(left)
self.right = promote(right)
def __str__(self):
return '({} {} {})'.format(self.op, self.left, self.right)
class Variable(Expression):
def __init__(self, name):
self.name = name
def __str__(self):
return self.name
class Number(Expression):
def __init__(self, value):
self.value = int(value)
def __str__(self):
return str(self.value)
class Multiplication(BinaryExpression):
op = '*'
class Addition(BinaryExpression):
op = '+'
class Smaller(BinaryExpression):
op = '<'
class Greater(BinaryExpression):
op = '>'
class SmallerOrEqual(BinaryExpression):
op = '<='
class GreaterOrEqual(BinaryExpression):
op = '>='
Expression.__mul__ = call(Multiplication)
Expression.__rmul__ = flip(Multiplication)
Expression.__add__ = call(Addition)
Expression.__radd__ = flip(Addition)
Expression.__lt__ = call(Smaller)
Expression.__gt__ = call(Greater)
Expression.__le__ = call(SmallerOrEqual)
Expression.__ge__ = call(GreaterOrEqual)
def promote(item):
if isinstance(item, str):
return Variable(item)
elif isinstance(item, int):
return Number(item)
else:
return item
class LpVariable:
def __init__(self, name, x, y, z):
self.name = name
self.x = x
self.y = y
self.z = z
def __str__(self):
return 'LpVariable({}, {}, {}, {})'.format(
self.name,
self.x,
self.y,
self.z,
)
__repr__ = __str__
LpContinuous = 'LpContinuous'
class ExpressionVisitor:
def visit(self, node):
return getattr(self, 'visit_' + type(node).__name__)(node)
class LpTransformer(ExpressionVisitor):
def visit_Variable(self, node):
return LpVariable(node.name, None, None, LpContinuous)
def visit_Number(self, node):
return node.value
def visit_Multiplication(self, node):
return [node.op, self.visit(node.left), self.visit(node.right)]
def visit_Addition(self, node):
return [node.op, self.visit(node.left), self.visit(node.right)]
def visit_Smaller(self, node):
return [node.op, self.visit(node.left), self.visit(node.right)]
def visit_Greater(self, node):
return [node.op, self.visit(node.left), self.visit(node.right)]
def visit_SmallerOrEqual(self, node):
return [node.op, self.visit(node.left), self.visit(node.right)]
def visit_GreaterOrEqual(self, node):
return [node.op, self.visit(node.left), self.visit(node.right)]
class Evaluator(ExpressionVisitor):
def __init__(self, **env):
self.env = env
def visit_Variable(self, node):
return self.env[node.name]
def visit_Number(self, node):
return node.value
def visit_Multiplication(self, node):
return self.visit(node.left) * self.visit(node.right)
def visit_Addition(self, node):
return self.visit(node.left) + self.visit(node.right)
def visit_Smaller(self, node):
return self.visit(node.left) < self.visit(node.right)
def visit_Greater(self, node):
return self.visit(node.left) > self.visit(node.right)
def visit_SmallerOrEqual(self, node):
return self.visit(node.left) <= self.visit(node.right)
def visit_GreaterOrEqual(self, node):
return self.visit(node.left) >= self.visit(node.right)
class Namespace(dict):
def __missing__(self, key):
value = self[key] = Variable(key)
return value
def main():
constraints = '2*a + 3*b <= c'
namespace = Namespace()
tree = eval(constraints, {}, namespace)
print('AST in prefix notation:', tree)
print()
print('Namespace:', namespace)
print()
print('LP-Transformed tree:')
import pprint
pprint.pprint(LpTransformer().visit(tree))
print()
print('Evaluated with a=3, b=5, c=10:')
pprint.pprint(Evaluator(a=3, b=5, c=10).visit(tree))
print()
print('Evaluated with a=3, b=5, c=100:')
pprint.pprint(Evaluator(a=3, b=5, c=100).visit(tree))
if __name__ == '__main__':
main()
Result:
AST in prefix notation: (<= (+ (* 2 a) (* 3 b)) c)
Namespace: {'a': Variable(a), 'c': Variable(c), 'b': Variable(b)}
LP-Transformed tree:
['<=',
['+',
['*', 2, LpVariable(a, None, None, LpContinuous)],
['*', 3, LpVariable(b, None, None, LpContinuous)]],
LpVariable(c, None, None, LpContinuous)]
Evaluated with a=3, b=5, c=10:
False
Evaluated with a=3, b=5, c=100:
True
The LpVariable class is obviously a mockup. Also, the LpTransformer class should produce something that's usable by pulp. Just change the visit_* methods accordingly.
Numbers are all ints, which you might not want. You should probably add floats and/or convert all numbers to decimal.Decimal.
Instead of using eval() I'd probably write a real parser, maybe with pyparsing, or, my favorite for stuff like that, Parcon.
Put
entryS = ""
before the while loop.

How to create a class instance without calling initializer?

Is there any way to avoid calling __init__ on a class while initializing it, such as from a class method?
I am trying to create a case and punctuation insensitive string class in Python used for efficient comparison purposes but am having trouble creating a new instance without calling __init__.
>>> class String:
def __init__(self, string):
self.__string = tuple(string.split())
self.__simple = tuple(self.__simple())
def __simple(self):
letter = lambda s: ''.join(filter(lambda s: 'a' <= s <= 'z', s))
return filter(bool, map(letter, map(str.lower, self.__string)))
def __eq__(self, other):
assert isinstance(other, String)
return self.__simple == other.__simple
def __getitem__(self, key):
assert isinstance(key, slice)
string = String()
string.__string = self.__string[key]
string.__simple = self.__simple[key]
return string
def __iter__(self):
return iter(self.__string)
>>> String('Hello, world!')[1:]
Traceback (most recent call last):
File "<pyshell#2>", line 1, in <module>
String('Hello, world!')[1:]
File "<pyshell#1>", line 17, in __getitem__
string = String()
TypeError: __init__() takes exactly 2 positional arguments (1 given)
>>>
What should I replace string = String(); string.__string = self.__string[key]; string.__simple = self.__simple[key] with to initialize the new object with the slices?
EDIT:
As inspired by the answer written below, the initializer has been edited to quickly check for no arguments.
def __init__(self, string=None):
if string is None:
self.__string = self.__simple = ()
else:
self.__string = tuple(string.split())
self.__simple = tuple(self.__simple())
When feasible, letting __init__ get called (and make the call innocuous by suitable arguments) is preferable. However, should that require too much of a contortion, you do have an alternative, as long as you avoid the disastrous choice of using old-style classes (there is no good reason to use old-style classes in new code, and several good reasons not to)...:
class String(object):
...
bare_s = String.__new__(String)
This idiom is generally used in classmethods which are meant to work as "alternative constructors", so you'll usually see it used in ways such as...:
#classmethod
def makeit(cls):
self = cls.__new__(cls)
# etc etc, then
return self
(this way the classmethod will properly be inherited and generate subclass instances when called on a subclass rather than on the base class).
A trick the standard pickle and copy modules use is to create an empty class, instantiate the object using that, and then assign that instance's __class__ to the "real" class. e.g.
>>> class MyClass(object):
... init = False
... def __init__(self):
... print 'init called!'
... self.init = True
... def hello(self):
... print 'hello world!'
...
>>> class Empty(object):
... pass
...
>>> a = MyClass()
init called!
>>> a.hello()
hello world!
>>> print a.init
True
>>> b = Empty()
>>> b.__class__ = MyClass
>>> b.hello()
hello world!
>>> print b.init
False
But note, this approach is very rarely necessary. Bypassing the __init__ can have some unexpected side effects, especially if you're not familiar with the original class, so make sure you know what you're doing.
Using a metaclass provides a nice solution in this example. The metaclass has limited use but works fine.
>>> class MetaInit(type):
def __call__(cls, *args, **kwargs):
if args or kwargs:
return super().__call__(*args, **kwargs)
return cls.__new__(cls)
>>> class String(metaclass=MetaInit):
def __init__(self, string):
self.__string = tuple(string.split())
self.__simple = tuple(self.__simple())
def __simple(self):
letter = lambda s: ''.join(filter(lambda s: 'a' <= s <= 'z', s))
return filter(bool, map(letter, map(str.lower, self.__string)))
def __eq__(self, other):
assert isinstance(other, String)
return self.__simple == other.__simple
def __getitem__(self, key):
assert isinstance(key, slice)
string = String()
string.__string = self.__string[key]
string.__simple = self.__simple[key]
return string
def __iter__(self):
return iter(self.__string)
>>> String('Hello, world!')[1:]
<__main__.String object at 0x02E78830>
>>> _._String__string, _._String__simple
(('world!',), ('world',))
>>>
Addendum:
After six years, my opinion favors Alex Martelli's answer more than my own approach. With meta-classes still on the mind, the following answer shows how the problem can be solved both with and without them:
#! /usr/bin/env python3
METHOD = 'metaclass'
class NoInitMeta(type):
def new(cls):
return cls.__new__(cls)
class String(metaclass=NoInitMeta if METHOD == 'metaclass' else type):
def __init__(self, value):
self.__value = tuple(value.split())
self.__alpha = tuple(filter(None, (
''.join(c for c in word.casefold() if 'a' <= c <= 'z') for word in
self.__value)))
def __str__(self):
return ' '.join(self.__value)
def __eq__(self, other):
if not isinstance(other, type(self)):
return NotImplemented
return self.__alpha == other.__alpha
if METHOD == 'metaclass':
def __getitem__(self, key):
if not isinstance(key, slice):
raise NotImplementedError
instance = type(self).new()
instance.__value = self.__value[key]
instance.__alpha = self.__alpha[key]
return instance
elif METHOD == 'classmethod':
def __getitem__(self, key):
if not isinstance(key, slice):
raise NotImplementedError
instance = self.new()
instance.__value = self.__value[key]
instance.__alpha = self.__alpha[key]
return instance
#classmethod
def new(cls):
return cls.__new__(cls)
elif METHOD == 'inline':
def __getitem__(self, key):
if not isinstance(key, slice):
raise NotImplementedError
cls = type(self)
instance = cls.__new__(cls)
instance.__value = self.__value[key]
instance.__alpha = self.__alpha[key]
return instance
else:
raise ValueError('METHOD did not have an appropriate value')
def __iter__(self):
return iter(self.__value)
def main():
x = String('Hello, world!')
y = x[1:]
print(y)
if __name__ == '__main__':
main()
Pass another argument to the constructor, like so:
def __init__(self, string, simple = None):
if simple is None:
self.__string = tuple(string.split())
self.__simple = tuple(self.__simple())
else:
self.__string = string
self.__simple = simple
You can then call it like this:
def __getitem__(self, key):
assert isinstance(key, slice)
return String(self.__string[key], self.__simple[key])
Also, I'm not sure it's allowed to name both the field and the method __simple. If only for readability, you should change that.

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