def run(self, node, max=10):
val = ''
count, node = 0, self[node]
print_info('[RUN]: node: {}'.format(node), prefix='[Running]')
absorbing_states = False
while count < max and not absorbing_states:
# Once the node transitions from a probability edge,
# the optional generator function allows any arbitrary data to be
# generated. It can be deterministic or not
# -- whatever the user wants to do.
if 'generator' in node:
val += '{}'.format(node['generator']())
highest = 0
# Update the active node based on which probability of the outgoing
# edges for this node is the highest, then transition to that node.
for edge, probability in node['edges'].iteritems():
if probability == 1:
absorbing_states = True
break
if probability > highest:
highest = probability
node = self[edge]
self._step()
print('{}Current node: {}, highest probability: {}'.format(
count * ' ', edge, highest))
count += 1
print('Final value: {}'.format(val))
return val
def run(self, node, max=10):
val = ''
count, node = 0, self[node]
print_info('[RUN]: node: {}'.format(node), prefix='[Running]')
absorbing_states = False
while count < max and not absorbing_states:
# Once the node transitions from a probability edge,
# the optional generator function allows any arbitrary data to be
# generated. It can be deterministic or not
# -- whatever the user wants to do.
if 'generator' in node:
val += '{}'.format(node['generator']())
highest = 0
# Update the active node based on which probability of the outgoing
# edges for this node is the highest, then transition to that node.
for edge, probability in node['edges'].iteritems():
if probability == 1:
absorbing_states = True
break
if probability > highest:
highest = probability
node = self[edge]
self._step()
print('{}Current node: {}, highest probability: {}'.format(
count * ' ', edge, highest))
count += 1
print('Final value: {}'.format(val))
return val
def cleanup(cur, conn):
print_info('Cleaning up...')
# Always clean up DB for this demo.
try:
cur.execute("""DROP TABLE cache_table;""")
except psycopg2.ProgrammingError:
conn.commit()
# Clean up cache as well.
mclient.delete(CACHE_KEY)
def cleanup(cur, conn):
print_info('Cleaning up...')
# Always clean up DB for this demo.
try:
cur.execute("""DROP TABLE cache_table;""")
except psycopg2.ProgrammingError:
conn.commit()
# Clean up cache as well.
mclient.delete(CACHE_KEY)
def test(self, string):
try:
print_info('{}'.format(string), prefix='[TESTING]')
chars = list(str(string))
for char in chars:
self.step += 1
self.transition(char)
self.reset()
print_success(''.join(chars), prefix='[FOUND]')
return True
except InvalidTransition:
print_error(''.join(chars), prefix='[NOT-FOUND]')
return False
def on_open(ch, method, properties, body):
key = method.routing_key
message = '* Received! {}'.format(body)
if key == 'info':
print_info(message)
if key == 'warning':
print_warning(message)
if key == 'error':
print_error(message)
if key == 'success':
print_success(message)
if not start.USE_EXCHANGE:
# Specify ACK to prevent failures from disappearing.
ch.basic_ack(delivery_tag=method.delivery_tag)
def on_open(ch, method, properties, body):
key = method.routing_key
message = '* Received! {}'.format(body)
if key == 'info':
print_info(message)
if key == 'warning':
print_warning(message)
if key == 'error':
print_error(message)
if key == 'success':
print_success(message)
if not start.USE_EXCHANGE:
# Specify ACK to prevent failures from disappearing.
ch.basic_ack(delivery_tag=method.delivery_tag)
def _divvy_ram(self, ram):
"""This is an arbitrary, somewhat meaningless method, to simulate
the notion of free blocks of ram that must be allocated and
referenced via pointer. A given program may require X ram, but
the location of available ram may be disparate, so various blocks have
to be stored as a free linked list, or similar data structure.
Since we've already covered linked lists, association lists, etc...,
there isn't much value outside learning the context of this data
structure, which tends to be in memory management."""
subdivisions = rr(2, 20) # Arbitrary number
flist = []
while subdivisions > 0:
diff = rr(0, ram)
# Store ram as [current block of memory, location]
flist.append([diff, str(self.last_block).zfill(4)])
ram = ram - diff
self.last_block += 1
subdivisions -= 1
if DEBUG:
print_info('Ram: {} / diff: {}'.format(ram, diff))
return flist
def _divvy_ram(self, ram):
"""This is an arbitrary, somewhat meaningless method, to simulate
the notion of free blocks of ram that must be allocated and
referenced via pointer. A given program may require X ram, but
the location of available ram may be disparate, so various blocks have
to be stored as a free linked list, or similar data structure.
Since we've already covered linked lists, association lists, etc...,
there isn't much value outside learning the context of this data
structure, which tends to be in memory management."""
subdivisions = rr(2, 20) # Arbitrary number
flist = []
while subdivisions > 0:
diff = rr(0, ram)
# Store ram as [current block of memory, location]
flist.append([diff, str(self.last_block).zfill(4)])
ram = ram - diff
self.last_block += 1
subdivisions -= 1
if DEBUG:
print_info('Ram: {} / diff: {}'.format(ram, diff))
return flist
[+]
/ \
[2] [2]
etc... `foo = 3 * 9`
(ROOT)
/ \
[=] [*]
/ / \
[foo] [3] [9]
"""
if DEBUG:
with Section('Abstract Syntax Tree (AST)'):
print_h2('Reading functions and then building ast and executing.')
src1 = inspect.getsource(foo)
src2 = inspect.getsource(bar)
tree = ast.parse(src1 + '\nfoo()\n' + src2 + '\nbar()')
print_info(tree)
exec(compile(tree, filename='<ast>', mode='exec'))
drawing = ast.parse(inspect.getsource(ast_drawing), filename='<ast>')
print_info('Printing AST docstring, a drawing of an AST (such meta)')
for node in ast.walk(drawing):
try:
print(ast.get_docstring(node))
except TypeError:
continue
map(classes_map.enroll_all, classes_map.schedules())
print_h3('All fields')
print(classes_map)
print_h3('\nClasses for Ella Tabor')
print('Classes: {}'.format(classes_map.get_classes('Ms. Ella Tabor')))
del classes_map['Ms. Ella Tabor']
# Too young to be taking classes right now anyway.
assert classes_map['Ms. Ella Tabor'] is None
print(classes_map)
assert 'Ms. Ella Tabor' not in classes_map
print_h3('Bi-directional', desc='A map ADT that maps to key OR value.')
bdmap = BidirectionalMap(
{1: 'Foo', 2: 'Bar', 'Foo': 'Bar', 'Bar': 'Foo'})
print(bdmap)
try:
bdmap['Bar'] = 'Foo'
bdmap['Foo'] = 'Bar'
except ValueError:
print_info('Test raising error for duplicate values Foo and Bar')
print(bdmap)
assert 'Bar' in bdmap
assert 'Foo' in bdmap
print_h3('\nClasses for Ella Tabor')
print('Classes: {}'.format(classes_map.get_classes('Ms. Ella Tabor')))
del classes_map['Ms. Ella Tabor']
# Too young to be taking classes right now anyway.
assert classes_map['Ms. Ella Tabor'] is None
print(classes_map)
assert 'Ms. Ella Tabor' not in classes_map
print_h3('Bi-directional', desc='A map ADT that maps to key OR value.')
bdmap = BidirectionalMap({
1: 'Foo',
2: 'Bar',
'Foo': 'Bar',
'Bar': 'Foo'
})
print(bdmap)
try:
bdmap['Bar'] = 'Foo'
bdmap['Foo'] = 'Bar'
except ValueError:
print_info('Test raising error for duplicate values Foo and Bar')
print(bdmap)
assert 'Bar' in bdmap
assert 'Foo' in bdmap
