def test_basic(self):
function = f.basic
code = ['def {}(a, b):'.format(function.__name__), ' return b']
r = Rules(a=True, b=True, output=True)
r.add(b=True, output=True)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_identity_explicit(self):
"""
Identity will yield same result even though False and True inputs are explicit specified.
"""
code = ['def {}(a):'.format(f.identity.__name__), ' return a']
r = Rules(a=True, output=True)
r.add(a=False, output=False)
solution = r.solve(f.identity)
self.assertEqual(solution.implementation, code)
def test_code_generation_with_if(self):
"""
Test with outputs different from boolean.
"""
r = Rules(a=True, b=True, output=1)
solution = r.solve(f.non_boolean_and, self)
code = [
'def ' + f.non_boolean_and.__name__ + '(a, b):', '',
' if a and b:', ' return 1', '', ' return False'
]
self.assertEqual(solution.implementation, code)
def test_simple_constant_output(self):
"""
When the result output of the QM algorithm is an empty expression, that means that regardless
of the input the output is constant.
"""
function = f.simple_constant_output
code = ['def {}(a):'.format(function.__name__), ' return True']
r = Rules(a=True, output=True)
r.add(a=False, output=True)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_function_outputs(self):
"""
When output is a function.
"""
function = f.output_function_obj
out1 = f.fun8
code = [
'def ' + function.__name__ + '(a, b):', '', ' if not a and b:',
' return ' + c.print_object(out1), '', ' return False'
]
r = Rules(a=False, b=True, output=out1) # non-boolean output
solution = r.solve(function)
self.assertEqual(solution.implementation, code)
def test_basic_if(self):
"""test basic if statement"""
function = f.basic_if
ouput = 'le'
code = [
'def {}(a, b):'.format(function.__name__), '', ' if b:',
" return \"{}\"".format(ouput), '', ' return False'
]
r = Rules(a=True, b=True, output=ouput)
r.add(b=True, output=ouput)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_mix_output_boolean(self):
"""
When ifs and pure boolean expression mix.
"""
function = f.mix_output
out = 'a'
code = [
'def ' + function.__name__ + '(a, b):', '', ' if not a and b:',
' return ' + c.print_object(out), ' return a and b'
]
r = Rules(a=False, b=True, output=out) # non-boolean output
r.add(a=True, b=True) # boolean output
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_internal_code_arguments(self):
"""
Do logic with pieces of code that evaluate to boolean.
"""
function = f.with_internal_code_arg
code = [
'def ' + function.__name__ + '(a):', '',
' if isinstance(a, str):', ' return 2', '',
' return False'
]
r = Rules(any_non_input_name=s.Code(code_str='isinstance(a, str)'),
output=2)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_calling_another_function_no_args(self):
"""
Invoke function with NO arguments.
"""
function = f.another_call
out = f.no_args
code = [
'def {}(a, b):'.format(function.__name__), '',
' if not a and b:', ' return {}()'.format(out.__name__),
'', ' return False'
]
r = Rules(a=False, b=True, output=out,
output_args={}) # non-boolean output
solution = r.solve(function)
self.assertEqual(solution.implementation, code)
def test_calling_nested_functions(self):
"""
call nested functions.
"""
function = f.nested_call
out_obj = s.Output(f.f,
{'a': s.Output(f.g, {'a': s.Code(code_str='a')})})
code = [
'def ' + function.__name__ + '(a):', '', ' if not a:',
' return ' + f.f.__name__ + '(' + f.g.__name__ + '(a))', '',
' return False'
]
r = Rules(a=False, output=out_obj)
solution = r.solve(function)
self.assertEqual(solution.implementation, code)
def test_recursive_function(self):
"""
Will do recursion, extremely cool!!!
"""
function = f.recursive
not_a = 'not a'
args = {'a': s.Code(code_str=not_a)}
out = s.Output(function, args)
code = [
'def {}(a):'.format(function.__name__), '',
' if {}:'.format(not_a), ' return 0', '',
' return {0}({1})'.format(function.__name__, not_a)
]
r = Rules(a=False, output=0, default=out)
solution = r.solve(function)
self.assertEqual(solution.implementation, code)
def test_boolean_and_quasi_boolean_mix_true_values(self):
"""
Tests whether changing inputs for True and 1 outputs affect the final result.
BY DEFAULT IF 1 AND TRUE are present will choose 1 as output.
Test with both a boolean and quasi-boolean output.
In python True == 1. Therefore output=1 is the same as output=True.
"""
code = [
'def mix_true_values(a, b):', '',
' if a and not b or not a and b:', ' return 1', '',
' return False'
]
r = Rules(a=True, b=False, output=1) # non-boolean output
r.add(a=False, b=True, output=True) # boolean condition
solution = r.solve(f.mix_true_values, self)
self.assertEqual(solution.implementation, code)
def test_function_solve_with_no_unittest(self):
"""
Same as test_basic_if() test but with no unittest provided.
"""
function = f.basic_if
ouput = 'le'
code = [
'def {}(a, b):'.format(function.__name__), '', ' if b:',
" return \"{}\"".format(ouput), '', ' return False'
]
r = Rules(a=True, b=True, output=ouput)
r.add(b=True, output=ouput)
solution = r.solve(function)
self.assertEqual(solution.implementation, code)
def test_non_collision(self):
"""
Testing bigger stuff. Multiple ifs with multiple boolean variables
"""
r = Rules(a=True, b=True, c=True, output=0) # leave d out
r.add(a=False, b=True, d=True, output=1) # leave c out
r.add(a=True, c=False, d=True, output=2) # leave b out
r.add(b=True, c=False, d=False, output=3) # leave a out
r.solve(f.non_collision, self)
def test_calling_another_function_with_args(self):
"""
Invoke function with arguments.
"""
function = f.another_call2
args = {'a': s.Code(code_str='a'), 'b': s.Code(code_str='b')}
out_f = f.another_call
code = [
'def {}(a, b):'.format(function.__name__), '',
' if not a and b:',
' return {}(a, b)'.format(out_f.__name__), '',
' return False'
]
r = Rules(a=False, b=True, output=out_f,
output_args=args) # non-boolean output
solution = r.solve(function)
self.assertEqual(solution.implementation, code)
def test_recursive_iteration(self):
"""
Will do recursive iteration, extremely cool!!!
"""
function = f.recursive_iteration
array_len_0 = 'len(array) == 0'
array_1 = 'array[1:]'
args = {'array': s.Code(code_str=array_1)}
out = s.Output(function, args)
code = [
'def {}(array):'.format(function.__name__), '',
' if {}:'.format(array_len_0), ' return 0', '',
' return {0}({1})'.format(function.__name__, array_1)
]
r = Rules(r1=s.Code(code_str=array_len_0), output=0, default=out)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def multiple_value_test(self, out1, out2, function):
"""
Testing multiple output types.
:param out1: anything
:param out2: anything
:param function: object
"""
code = [
'def ' + function.__name__ + '(a, b):', '', ' if not a and b:',
' return ' + c.print_object(out1), '',
' if a and not b:', ' return ' + c.print_object(out2),
'', ' return False'
]
r = Rules(a=False, b=True, output=out1) # non-boolean output
r.add(a=True, b=False, output=out2) # non-boolean condition
solution = r.solve(function)
self.assertEqual(solution.implementation, code)
def test_rules_input_order_is_respected(self):
"""
First input has to be first on the final boolean expression.
So programmers can use short circuiting to their advantage ;). Very useful when validating data.
Changing input order will change expression order.
"""
code = ['def ordered_expression(a, b):', ' return a or b']
r = Rules(a=True, output=True) # boolean output
r.add(b=True, output=True) # boolean condition
solution = r.solve(f.ordered_expression, self)
self.assertEqual(solution.implementation, code)
code = ['def ordered_expression(a, b):', ' return a or b']
r = Rules(b=True, output=True) # boolean output
r.add(a=True, output=True) # boolean condition
solution = r.solve(f.ordered_expression, self)
self.assertEqual(solution.implementation, code)
def test_factoring_with_code_var(self):
"""This is a hard test from test_code_generator.py, but additionally here it is added Code instances :)"""
function = f.factor_code_with_code
output_code = 'i * 2'
code1_str = 'i == 9'
code2_str = 'i == 7'
code = [
'def ' + function.__name__ + '(i):', '',
' if ' + code1_str + ' or ' + code2_str + ':',
' return ' + output_code, '', ' return False'
]
i = Code()
r = Rules(i == 9, output=i * 2)
r.add(i == 7, output=i * 2)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_boolean_and_quasi_boolean_mix_false_values(self):
"""
Will make an if for the 0 case, while it will ignore the False case.
"""
code = [
'def mix_false_values(a, b):', '',
' if a and not b or not a and b:', ' return 0', '',
' return False'
]
r = Rules(a=False, b=True, output=0) # non-boolean output
r.add(a=True, b=False, output=False) # boolean condition
solution = r.solve(f.mix_false_values, self)
self.assertEqual(solution.implementation, code)
r = Rules(a=True, b=False, output=False) # non-boolean output
r.add(a=False, b=True, output=0) # boolean condition
solution = r.solve(f.mix_false_values, self)
self.assertEqual(solution.implementation, code)
def test_factor_code_output(self):
"""
Tests that code output can be factored.
"""
function = f.factor_ordered_pieces_of_code
output_code = '2*2'
code1_str = 'isinstance(array[0], int)'
code2_str = 'isinstance(array[1], int)'
code = [
'def ' + function.__name__ + '(array):', '',
' if ' + code1_str + ' or ' + code2_str + ':',
' return ' + output_code, '', ' return False'
]
r = Rules(r1=s.Code(code_str=code1_str),
output=s.Code(code_str=output_code))
r.add(s.Code(code_str=code2_str), output=s.Code(code_str=output_code))
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_factor_ordered_pieces_with_redundancy(self):
"""Tests that string output is factored, when inputs are given in more than one addition."""
function = f.factor_ordered_pieces_with_redundancy
right_str = 'factoring!!!'
code0_str = 'isinstance(array[0], int)'
code1_str = 'isinstance(array[1], int)'
code = [
'def {}(array):'.format(function.__name__), '',
' if {}:'.format(code1_str),
" return \"{}\"".format(right_str), '', ' return False'
]
r = Rules(r1=s.Code(code_str=code0_str),
r2=s.Code(code_str=code1_str),
output=right_str)
r.add(s.Code(code_str=code1_str), output=right_str)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_collision(self):
"""
Even though the rules are absurd and are a contradiction. The non deterministic model should choose and solve
the problem at random between the identity ('return a') and its negation ('return not a').
"""
r = Rules(a=True, output=True) # first condition
r.add(a=True, output=False) # contradictory condition.
r.solve(f.collision, self)
def test_factor_ordered_with_code(self):
"""This is a hard test from test_code_generator.py, but additionally here it is added Code vars :)"""
function = f.factor_ordered_with_code
right_str = 'i * j'
code1_str = 'i != 0'
code2_str = 'i < 1'
code3_str = 'i > j'
code = [
'def ' + function.__name__ + '(i, j):', '',
' if {0} and {1} or {2}:'.format(code1_str, code2_str,
code3_str),
' return ' + right_str, '', ' return False'
]
i = Code()
j = Code()
r = Rules(i != 0, i < 1, output=i * j)
r.add(i > j, output=i * j)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_right_code_input_order(self):
"""
For programmer convenience and to be able to use short circuiting.
Code pieces on expressions will follow the same order as the input order.
"""
function = f.right_expression_order
right_str = 'right order!!!'
code1_str = 'len(array) > 1'
code2_str = 'array[0]'
code3_str = 'isinstance(array[0], int)'
code = [
'def ' + function.__name__ + '(array):', '', ' if ' +
code1_str + ' and ' + code2_str + ' and ' + code3_str + ':',
' return ' + "\"" + right_str + "\"", '', ' return False'
]
r = Rules(r1=s.Code(code_str=code1_str),
r2=s.Code(code_str=code2_str),
r3=s.Code(code_str=code3_str),
output=right_str)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_factor_ordered_pieces_of_code(self):
"""
Tests that string output is factored, when inputs are given in more than one addition.
"""
function = f.factor_ordered_pieces_of_code
right_str = 'factoring!!!'
code1_str = 'isinstance(array[0], int)'
code2_str = 'isinstance(array[1], int)'
code3_str = 'isinstance(array[2], int)'
code = [
'def ' + function.__name__ + '(array):', '', ' if ' +
code1_str + ' and ' + code2_str + ' or ' + code3_str + ':',
' return ' + "\"" + right_str + "\"", '', ' return False'
]
r = Rules(r1=s.Code(code_str=code1_str),
r2=s.Code(code_str=code2_str),
output=right_str)
r.add(s.Code(code_str=code3_str), output=right_str)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_inner_inputs_with_different_outputs(self):
"""
Inner inputs are not function arguments but are for example pieces of code, that act as inputs to the tables.
Inside function 'return_solution', on module solver.py:
On each table iteration the all_inputs variable has to be calculated inside the main function of solver.py
This is because if not this test fails.
"""
function = f.many_outputs
input1 = 'isinstance(a, int)'
input2 = 'isinstance(a, str)'
r = Rules(r1=Code(code_str=input1), output=1)
r.add(r1=Code(code_str='isinstance(a, str)'), output=2)
solution = r.solve(function, self)
print(solution.implementation)
# is taking the correct inputs
self.assertEqual(solution.implementation[2],
' if {}:'.format(input1))
self.assertEqual(solution.implementation[5],
' if {}:'.format(input2))
def test_default_keyword(self):
"""
default keyword changes the last return from False to determined value.
"""
function = f.with_default_value
out = 3
default = 5
code = [
'def ' + function.__name__ + '(a, b):', '', ' if not a and b:',
' return ' + str(out), '', ' return ' + str(default)
]
r = Rules(a=False, b=True, output=out, default=default)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
r = Rules(a=False, b=True, output=out)
r.add(default=default)
solution = r.solve(function, self)
self.assertEqual(solution.implementation, code)
def test_identity_representation(self):
"""There are 4 equivalent representations of the identity function:
1. Boring:
>>> Rules(a=True, output=True)
2. Implicit True:
>>> Rules(a=True)
3. Using Code() magic:
>>> a = Code()
>>> Rules(a, output=True)
4. Using both Code() magic and implicit True output:
>>> a = Code()
>>> Rules(a)
lets test all representations!!!
"""
a = Code()
solution = ['def {}(a):'.format(f.identity.__name__), ' return a']
r = Rules(a=True, output=True)
s = r.solve(f.identity)
self.assertEqual(s.implementation, solution)
r = Rules(a=True)
s = r.solve(f.identity)
self.assertEqual(s.implementation, solution)
r = Rules(a, output=True)
s = r.solve(f.identity)
self.assertEqual(s.implementation, solution)
# TODO: pass this test:
"""
def from_table_to_ones(table):
"""
Gets the ones as a list of strings from a truth table like set, containing tuples.
:param table: truth table
:return: list containing bits.
"""
ones = []
for row in table:
# case 1: when the output is explicit.
if Rules.is_explicit(row):
if row[1]: # only do it for true outputs.# TODO change for non booleans.
ones.append(''.join(list(map(h.from_bool_to_bit,
list(row[0])))))
else: # case 2: The output is an implicit True, inputs are in the row.
ones.append(''.join(list(map(h.from_bool_to_bit, list(row)))))
return ones