ops.group_by(key_selector)
)
groups.subscribe(subscribe_group_observable)
# Sample: A way to grab items and emit latest values at certain points
print('-- Sample')
# 10 ms 마다 인터벌 발생 (시간의 단위는 초이다.)
rx.interval(0.01).pipe(
# 1초 동안 동작
ops.take_until(rx.timer(1)),
# 100ms 마다 이벤트 출력 (현재 받은 최신값)
ops.sample(0.1)
).subscribe(print)
time.sleep(2)
# Max
print('-- Max')
rx.from_([1, 2, 3, 4, 12, 3, 3, -10]).pipe(
ops.max(lambda x, y: x - y)
).subscribe(print)
rx.throw() rx.interval() rx.from_() rx.interval() rx.just() rx.range() rx.repeat_value() rx.start() rx.timer() """Mathematical""" op.average() op.concat() op.count() op.max() op.min() op.reduce() op.sum() """Transformation""" op.buffer() op.group_by() op.map() op.scan() # ... """Filtering""" op.debounce() op.distinct() op.filter()
op.map(lambda v: v[1]),
op.average()
).subscribe(reporter)
print('=' * 25)
stocks2 = (('GOOG', 8.95), ('APPL', 7.65), ('APPL', 12.45), ('MSFT', 5.66), ('GOOG', 7.56), ('IBM', 12.76))
source1 = rx.from_list(stocks)
source2 = rx.from_list(stocks2)
# Find the max
rx.merge(source1, source2).pipe(
op.map(lambda v: v[1]),
op.max()
).subscribe(reporter)
print('-' * 25)
# Find the min
rx.merge(source1, source2).pipe(
op.map(lambda v: v[1]),
op.min()
).subscribe(reporter)
print('-' * 25)
# Only publish unique values
rx.merge(source1, source2).pipe(
op.distinct()
"""this operator will given an observable with max value from the source observable.
:parameter
comparer_function: optional param. this function is used on source observables to compare values.
:return
it returns an observable with max value from the source observable.
"""
from rx import of, operators as op
o = of(12, 24, 50, 33, 72, 80, 520, 1001)
o.pipe(
# op.max(), # Max value is 1001
# op.max(lambda t1, t2: t1 - t2), # Max value is 1001
op.max(lambda t1, t2: t2 - t1) # Max value is 12
# java compare o1, o2와 같다.
).subscribe(lambda r: print("Max value is {}".format(r)))
import rx
import rx.operators as ops
numbers = rx.from_([1, 2, 3, 4])
numbers.pipe(ops.max()).subscribe(
on_next=lambda i: print("on_next {}".format(i)),
on_error=lambda e: print("on_error: {}".format(e)),
on_completed=lambda: print("on_completed"))
files = ['test.csv', 'test2.csv']
source = rx.from_([rx.from_(read_csv(filename))
for filename in files]).pipe(ops.merge_all(),
ops.map(row_to_dict))
published = source.pipe(ops.publish())
def print_row(row):
print(
'File: {filename} has {lines} lines and its size is {size} kb'.format(
**row))
def print_group(group):
return group.subscribe(print_row)
# 두 곳에서 subscribe 한다. #1
maximum = published.pipe(ops.max(lambda a, b: a['lines'] - b['lines']))
maximum.subscribe(lambda row: print(
'-- File with the most number of lines is "{filename}" with {lines} lines'.
format(**row)))
# 2
published.pipe(ops.group_by(lambda row: row['size'])).subscribe(print_group)
# 이걸 해야 시작
published.connect()
def create():
return xs.pipe(ops.max(reverse_comparer))
def create():
return xs.pipe(ops.max())
