def insert_all(max_records):
people = [random_person() for n in range(max_records)]
prnt('Records to create:', people)
for person in people:
# Don't need this prop for our example schema.
del person['address']
db_session.add(Person(**person))
def insert_all(max_records):
people = [random_person() for n in range(max_records)]
prnt('Records to create:', people)
for person in people:
# Don't need this prop for our example schema.
del person['address']
db_session.add(Person(**person))
print(f)
print(neg * f)
# Bind all once
print_h2('Applicative functors, partial applications and compositions')
bound1 = add2 * pm.List(*range(2)) & pm.List(*range(2))
# Bind all a second time
bound2 = add_ten_to * pm.List(*range(2)) & bound1
ppr(bound2)
ppr(num_and_ranges(10))
assert negafy(*range(10)) == neg * monoid_range(10)
# Combining Functors * 4
names = pm.List(*[random_person()['name'] for _ in range(4)])
f1 = foofix * names
f2 = foofix * f1
f3 = foofix * f2
f4 = foofix * f3
print(f1)
print(f2)
print(f3)
print(f4)
assert f4[0].startswith('FOO_FOO_FOO_FOO_')
print_h2('Monads')
f = monoid_range(4) >> monoid_range(4)
ppr(neg * f)
print(pm.Just(9) >> pm.Just(10))
def _random_person():
person = random_person()
return {'name': person['name']}
# topics = ['foo', 'bar', 'quux', 'foo.bar', 'foo.bar.*']
topics = ['main-topic']
consumer = KafkaConsumer('main-topic',
group_id='my_group',
bootstrap_servers=['localhost:9092'])
if DEBUG:
# http://kafka-python.readthedocs.org/en/latest/usage.html to use kafka
# See .sh scripts at:
# http://kafka.apache.org/08/documentation.html#quickstart
# instance and send/receive messages.
with Section('Kafka - via kafka-py'):
# PRODUCER - typically living somewhere else beside the consumer,
# running in parallel.
for topic in topics:
for i in range(10):
producer.send_messages(topic, '{}'.format(random_person()))
# Also works with command line message sending:
# Typing into the console after running the below command will cause the
# arguments to be sent to the queue, and processed.
# They will also be visible here when read by the consumer in python.
# bin/kafka-console-producer.sh --broker-list \
# localhost:9092 --topic main-topic
# CONSUMER
for message in consumer:
print("{}:{}:{}: key={} value={}".format(
message.topic, message.partition,
message.offset, message.key,
message.value))
topics = ['main-topic']
consumer = KafkaConsumer('main-topic',
group_id='my_group',
bootstrap_servers=['localhost:9092'])
if DEBUG:
# http://kafka-python.readthedocs.org/en/latest/usage.html to use kafka
# See .sh scripts at:
# http://kafka.apache.org/08/documentation.html#quickstart
# instance and send/receive messages.
with Section('Kafka - via kafka-py'):
# PRODUCER - typically living somewhere else beside the consumer,
# running in parallel.
for topic in topics:
for i in range(10):
producer.send_messages(topic, '{}'.format(random_person()))
# Also works with command line message sending:
# Typing into the console after running the below command will cause the
# arguments to be sent to the queue, and processed.
# They will also be visible here when read by the consumer in python.
# bin/kafka-console-producer.sh --broker-list \
# localhost:9092 --topic main-topic
# CONSUMER
for message in consumer:
print("{}:{}:{}: key={} value={}".format(message.topic,
message.partition,
message.offset,
message.key,
message.value))
print(f)
print(neg * f)
# Bind all once
print_h2('Applicative functors, partial applications and compositions')
bound1 = add2 * pm.List(*range(2)) & pm.List(*range(2))
# Bind all a second time
bound2 = add_ten_to * pm.List(*range(2)) & bound1
ppr(bound2)
ppr(num_and_ranges(10))
assert negafy(*range(10)) == neg * monoid_range(10)
# Combining Functors * 4
names = pm.List(*[random_person()['name'] for _ in range(4)])
f1 = foofix * names
f2 = foofix * f1
f3 = foofix * f2
f4 = foofix * f3
print(f1)
print(f2)
print(f3)
print(f4)
assert f4[0].startswith('FOO_FOO_FOO_FOO_')
print_h2('Monads')
f = monoid_range(4) >> monoid_range(4)
ppr(neg * f)
print(pm.Just(9) >> pm.Just(10))
