def get_authorization_stream(context: Context) -> Observable:
return return_value(context).pipe(
op.flat_map(call_async(validate_redirect_uri)),
op.flat_map(call_async(validate_response_type)),
op.flat_map(call_async(validate_scope)),
op.flat_map(select_flow),
)
def rmux_client(sources):
response = sources.tcp_client.response.pipe(ops.share())
tcp_connect = rx.just(tcp_client.Connect(
host='127.0.0.1', port='8080'
))
create_observable = response.pipe(
ops.flat_map(lambda connection:
rx.just({'what': 'subscribe', 'id':42, 'name': '1234'}).pipe(
ops.map(lambda i: json.dumps(i)),
frame,
ops.map(lambda j: tcp_client.Write(id=connection.id, data=j.encode()))
))
)
console = response.pipe(
ops.flat_map(lambda connection: connection.observable.pipe(
ops.map(lambda i: i.data.decode('utf-8')),
unframe,
ops.map(lambda i: json.loads(i)),
ops.group_by(lambda i: i['id']),
ops.flat_map(lambda subscription: subscription.pipe(
ops.map(notification),
ops.dematerialize(),
))
)),
ops.map(lambda i: "item: {}\n".format(i))
)
tcp_sink = rx.merge(tcp_connect, create_observable)
return Sink(
tcp_client=tcp_client.Sink(request=tcp_sink),
stdout=stdout.Sink(data=console),
)
def test_walk_file_and_dir(self):
expected_files = [
os.path.join('dfoo', 'foo'),
os.path.join('dbar', 'bar'),
os.path.join('dbiz', 'biz'),
]
expected_dirs = ['dfoo', 'dbar', 'dbiz']
actual_files = []
create_file_tree(self.wordkir, expected_dirs, expected_files)
source = walk.make_driver().call(
walk.Sink(request=rx.just(
walk.Walk(top=self.wordkir, id='test', recursive=True))))
class TestObserver(Observer):
def on_next(self, i):
actual_files.append(i)
def on_completed(self):
return
def on_error(self, e):
raise Exception(e)
source.response.pipe(
ops.filter(lambda i: type(i) is walk.WalkResponse),
ops.flat_map(lambda i: i.content.directories),
ops.flat_map(lambda i: i.files),
).subscribe(TestObserver())
for f in expected_files:
self.assertIn(os.path.join(self.wordkir, f), actual_files)
def download_directory(file: dict,
destination: str,
matching: str = None,
delete_after_download: bool = False) -> Observable:
destination = os.path.abspath(destination)
def get_destination(f):
relative_path = f['path'][len(file['path']):]
next_destination = '{}{}{}'.format(
destination, '' if destination[-1] == '/' else '/', relative_path)
return next_destination
def initial_stats(files):
return {
'progress': 0,
'total_files': len(files),
'total_bytes': sum([int(f.get('size', 0)) for f in files]),
'downloaded_files': 0,
'downloaded_bytes': 0
}
def update_stats(stats, download):
downloaded_files = stats['downloaded_files'] + (
0 if download['progress'] < 1 else 1)
downloaded_bytes = stats['downloaded_bytes'] + download[
'downloaded_bytes']
progress = downloaded_bytes / stats['total_bytes']
return {
'progress': progress,
'total_files': stats['total_files'],
'total_bytes': stats['total_bytes'],
'downloaded_files': downloaded_files,
'downloaded_bytes': downloaded_bytes
}
def is_file_matching(f):
return not matching or fnmatch.fnmatch(f['path'], matching)
def delete_downloaded(downloaded):
if delete_after_download:
return delete_file(downloaded['file']).pipe(
map(lambda _: downloaded))
else:
return of(downloaded)
def filter_files(files):
return [f for f in files if not is_folder(f) and is_file_matching(f)]
if is_folder(file):
return list_folder_recursively(file).pipe(
map(lambda files: filter_files(files)),
flat_map(lambda files: of(True).pipe(
flat_map(lambda _: of(*files).pipe(
flat_map(lambda f: download_file(f, get_destination(f))),
flat_map(delete_downloaded))),
scan(update_stats, initial_stats(files)))))
else:
return download_file(file, destination)
def audio_encoder(sources):
# Parse configuration
parser = create_arg_parser()
read_request, read_response = sources.argv.argv.pipe(
ops.skip(1),
argparse.parse(parser),
ops.filter(lambda i: i.key == 'config'),
ops.map(lambda i: file.Read(id='config', path=i.value)),
file.read(sources.file.response),
)
config = read_response.pipe(
ops.filter(lambda i: i.id == "config"),
ops.flat_map(lambda i: i.data),
parse_config,
)
# Transcode request handling
encode_init = config.pipe(
ops.map(
lambda i: encoder.Initialize(storage_path=i.encode.storage_path)))
encode_request = sources.httpd.route.pipe(
ops.filter(lambda i: i.id == 'flac_transcode'),
ops.flat_map(lambda i: i.request),
ops.map(lambda i: encoder.EncodeMp3(
id=i.context, data=i.data, key=i.match_info['key'])),
)
encoder_request = rx.merge(encode_init, encode_request)
# http server
http_init = config.pipe(
ops.flat_map(lambda i: rx.from_([
httpd.Initialize(request_max_size=0),
httpd.AddRoute(
methods=['POST'],
path='/api/transcode/v1/flac/{key:[a-zA-Z0-9-\._]*}',
id='flac_transcode',
),
httpd.StartServer(host=i.server.http.host, port=i.server.http.port
),
])))
http_response = sources.encoder.response.pipe(
ops.map(lambda i: httpd.Response(
data='ok'.encode('utf-8'),
context=i.id,
)))
http = rx.merge(http_init, http_response)
# merge sink requests
file_requests = read_request
return Sink(
encoder=encoder.Sink(request=encoder_request),
file=file.Sink(request=file_requests),
httpd=httpd.Sink(control=http),
)
def select_flow(context: Context) -> Observable:
response_type = next(iter(context.oauth2_request.response_type))
if response_type == 'code':
return return_value(context).pipe(
op.flat_map(call_async(authorization_code_grant)))
if response_type == 'token':
return return_value(context).pipe(
op.flat_map(call_async(implicit_grant)))
raise InvalidRequest('Invalid response_type parameter')
def __init__(self, protocol):
# See comment in players.py.
self._aio_scheduler = QtScheduler(QtCore)
messages = protocol.register("game_info")
self.new = messages.pipe(
ops.flat_map(self._split_game_info),
ops.observe_on(self._aio_scheduler),
ops.flat_map(self._process_game),
ops.observe_on(ImmediateScheduler()),
ops.filter(lambda x: x is not None),
)
def _export_geometries():
def aggregate_progress(progresses, count):
p = _sum_dicts(progresses.values(), excluded_keys=['geometry'])
exported = round(100 * p['exported'] / count)
downloaded = round(100 * p['downloaded'] / count)
downloaded_bytes = format_bytes(p['downloaded_bytes'])
processed = round(100 * p['processed'] / count)
return progress(
default_message='Exported {}%, Downloaded {}% ({}), Processed {}%'.format(
exported, downloaded, downloaded_bytes, processed
),
message_key='tasks.retrieve.time_series_to_sepal.progress',
exported=exported,
downloaded=downloaded,
downloaded_bytes=downloaded_bytes,
processed=processed
)
features_collection = _to_features_collection(region)
def export_geometry(geometry, i, geometry_count):
geometry_description = str(i + 1).zfill(len(str(geometry_count)))
return defer(
lambda _: _export_geometry(
geometry,
geometry_description=geometry_description
)
)
return concat(
progress(
default_message='Tiling AOI...',
message_key='tasks.retrieve.time_series_to_sepal.tiling'
),
_extract_feature_indexes(features_collection).pipe(
flat_map(
lambda feature_indexes: _to_geometries(features_collection, feature_indexes).pipe(
flat_map(
lambda geometries: concat(
*[
export_geometry(geometry, i, len(feature_indexes))
for i, geometry in enumerate(geometries)
]
)
),
scan(lambda acc, p: {**acc, p['geometry']: p}, {}),
flat_map(lambda progresses: aggregate_progress(
progresses,
count=len(feature_indexes) * len(year_ranges)
))
)
)
)
)
def getTestrunDependencies(testrun):
return rx.of(testrun).pipe(
ops.flat_map(
lambda testrun: getTestrunProperties(testrun)
),
ops.flat_map(
lambda testrun: getTestcaseOwners(testrun)
),
ops.flat_map(
lambda testrun: getTestrunMatrix(testrun)
),
)
def monitor():
def is_running(state):
return state in [Task.State.UNSUBMITTED, Task.State.READY, Task.State.RUNNING]
return interval(_MONITORING_FREQUENCY).pipe(
flat_map(lambda _: execute(
action=load_status,
description='monitor task ' + str(task))
),
flat_map(extract_state),
distinct_until_changed(),
take_while(is_running, inclusive=True)
)
def get_authorization_stream(request: OIDCRequest) -> Observable:
response_params: Dict[str, Any] = {}
# yapf: disable
return just(request).pipe(
op.flat_map(call_async(validate_redirect_uri)),
op.flat_map(call_async(validate_response_type)),
op.flat_map(call_async(validate_scope)),
op.flat_map(select_flows),
op.merge_all(),
op.do_action(lambda x: response_params.update(asdict(x))),
op.last(),
op.map(lambda x: AuthorizationResponse(**response_params)))
def main():
origin = rx.subjects.Subject()
origin.pipe(
ops.flat_map(rx.from_),
ops.map(lambda x: bytes([x])),
ops.filter(RemoveComments().next_character),
ops.flat_map(Tokenize().next_character),
ops.filter(bool),
ops.flat_map(Parse().next_token),
).subscribe_(on_next=pprint.pprint, on_error=print)
read_into("parse.lisp", origin)
def main():
loop = asyncio.get_event_loop()
io_scheduler = AsyncIOThreadSafeScheduler(loop=loop)
scheduler = ThreadPoolScheduler(multiprocessing.cpu_count())
semaphore = Subject()
semaphore_stream = semaphore.pipe(
ops.flat_map(lambda _: rx.of(True).pipe(
ops.delay(ARGS.block_time, scheduler=scheduler),
ops.start_with(False))), ops.start_with(True))
video_stream_observable = rx.using(
lambda: VideoStreamDisposable(),
lambda d: rx.from_iterable(video_stream_iterable(d.cap)))
gated_video_stream = video_stream_observable.pipe(
ops.subscribe_on(scheduler),
ops.sample(1 / ARGS.fps), # sample frames based on fps
ops.combine_latest(semaphore_stream),
ops.filter(lambda tup: tup[1]), # proceed only if semaphore allows
ops.map(lambda tup: tup[0]) # take only frame
)
disposable = gated_video_stream.pipe(
ops.filter(has_face), # filter frames without faces
ops.map(lambda frame: Image.fromarray(
cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))), # map frame to PIL image
ops.map(lambda img: img.resize(
(640, 360))), # resize image (inference will be faster)
ops.observe_on(io_scheduler),
ops.map(lambda img: ImageFacesPair(img, analyse_frame(img))
), # analyse frame for faces
ops.filter(lambda img_faces_pair: any([
face.top_prediction.confidence > ARGS.threshold
for face in img_faces_pair.faces
])), # proceed only if there is a known face in the frame
ops.throttle_first(1),
ops.flat_map(unlock_request), # unlock the door
ops.do_action(
on_next=lambda _: semaphore.on_next(True)
) # trigger semaphore which will block stream for "block-seconds" seconds (doors are unlocked for that long after unlock request)
).subscribe(on_error=lambda e: logger.exception(e))
try:
loop.run_forever()
except Exception as e:
logger.exception(e)
logger.info("Smart lock face recognition engine shutdown")
disposable.dispose()
def create():
def mapper(x_yy):
x, yy = x_yy
return yy.pipe(ops.map(lambda y: '{}{}'.format(x.value, y.value)))
return xs.pipe(
ops.group_join(
ys,
lambda x: rx.timer(x.interval),
lambda y: rx.timer(y.interval).pipe(
ops.flat_map(rx.throw(ex) if y.value == "tin" else rx.empty())),
),
ops.flat_map(mapper),
)
def _set_band_names():
band_names_stream = of(band_names) if band_names else get_band_names(
credentials, image)
return concat(
progress(
default_message='Setting band names...',
message_key='tasks.retrieve.image_to_sepal.setting_band_names'
),
band_names_stream.pipe(
flat_map(lambda names: set_band_names(
band_names=names,
files=
[destination_path + '/*.tif', destination_path + '/*.vrt'])
), flat_map(lambda _: empty())))
def configure_timed_read(self):
interval = self.config.getfloat("fp50", "interval")
if interval > 0:
logger.info("Configuring timed read")
# enabled
rx.interval(interval, scheduler=NewThreadScheduler()).pipe(
operators.flat_map(lambda x: self.control.get_power()),
operators.map(lambda x: self.upload_power(x)),
operators.delay(self.config.getfloat("fp50", "query_delay")),
operators.flat_map(
lambda x: self.control.get_internal_temperature()),
operators.map(lambda x: self.upload_internal_temperature(x)),
operators.catch(error_handler)).subscribe()
def list_folder_recursively(folder: dict) -> Observable:
def recurse(file):
if is_folder(file):
return concat(
of([file]),
list_folder_recursively(file),
)
else:
return of([file])
return list_folder(folder).pipe(
flat_map(lambda files: from_list(files)),
flat_map(recurse),
reduce(lambda acc, files: acc + files, []),
)
def get_products(shop: Dict[str, str], search_term: str,
options) -> Observable:
domain = re.findall("\.(.+)\.com", shop['url'])[0]
print(f"Lauching {domain}")
browser = launch_browser(f"{shop['url']}{search_term}", options, shop)
base_obs = rx.of(browser).pipe(
ops.do_action(
lambda el: print(f"Getting products prices from {domain}")),
ops.flat_map(lambda browser: rx.from_(
browser.find_elements_by_xpath(shop["xpath"]["parent"]))),
ops.filter(lambda el: el.is_displayed()),
ops.map(lambda el: (
get_property(el, shop["xpath"]["product_name"]),
get_property(el, shop["xpath"]["price"]),
)),
ops.filter(lambda el: el[0] and el[1]),
ops.map(lambda el: {
"name": el[0],
"price": el[1]
}),
ops.map(lambda product: transform_price(product, shop["priceRegexp"])),
ops.finally_action(lambda: browser.close()),
)
return base_obs
def __init__(self,
concurrency_per_group,
delay_seconds=0,
description=None):
self._queue = Subject()
self._description = description
self.request_scheduler = ThreadPoolScheduler(concurrency_per_group)
producer_scheduler = ThreadPoolScheduler(concurrency_per_group)
def on_next(result):
output = result['output']
output.on_next({
'value': result.get('value'),
'completed': result.get('completed')
})
self._subscription = self._queue.pipe(
observe_on(producer_scheduler), group_by(lambda r: r['group']),
flat_map(lambda concurrency_group: concurrency_group.pipe(
map(lambda r: r['work']),
delay(delay_seconds),
merge(max_concurrent=concurrency_per_group),
merge_all(),
)), take_until_disposed()).subscribe(
on_next=on_next,
on_error=lambda error: logging.exception(
'Error in {} request stream'.format(self)),
scheduler=producer_scheduler)
def start(self):
logging.debug("in MyObservable.start")
rx.interval(1.0).pipe(
ops.subscribe_on(self.scheduler),
ops.flat_map(lambda i: self.fetch_subjects())).subscribe(
on_next=lambda v: self.subject.on_next(v),
on_error=lambda e: print_error("Error in interval loop", e))
def __init__(
self, influxdb_client,
write_options: WriteOptions = WriteOptions()) -> None:
self._influxdb_client = influxdb_client
self._write_service = WriteService(influxdb_client.api_client)
self._write_options = write_options
if self._write_options.write_type is WriteType.batching:
# Define Subject that listen incoming data and produces writes into InfluxDB
self._subject = Subject()
# Define a scheduler that is used for processing incoming data - default singleton
observable = self._subject.pipe(
ops.observe_on(self._write_options.write_scheduler))
self._disposable = observable \
.pipe( # Split incoming data to windows by batch_size or flush_interval
ops.window_with_time_or_count(count=write_options.batch_size,
timespan=timedelta(milliseconds=write_options.flush_interval)),
# Map incoming batch window in groups defined by 'organization', 'bucket' and 'precision'
ops.flat_map(lambda v: _window_to_group(v)),
# Write data into InfluxDB (possibility to retry if its fail)
ops.map(mapper=lambda batch: self._retryable(data=batch, delay=self._jitter_delay())), #
ops.merge_all()) \
.subscribe(self._on_next, self._on_error, self._on_complete)
else:
self._subject = None
self._disposable = None
def demo_flatmap2():
'''tuple unpacking'''
a = rx.of(1, 2, 3, 4)
a.pipe(ops.flat_map(lambda x: range(0, x))
#ops.flat_map(range)
).subscribe(print)
def word_counter(file_name):
# count words using `group_by()`
# tuple the word with the count
return words_from_file(file_name).pipe(
ops.group_by(lambda word: word),
ops.flat_map(lambda grp: grp.pipe(ops.count(),
ops.map(lambda ct: (grp.key, ct)))))
def run():
parser = argparse.ArgumentParser(
prog='entityfactssheetsharvester',
description=
'Retrieves EntityFacts sheets from a given CSV with GND identifiers and returns them as line-delimited JSON records.',
epilog=
'example: entityfactssheetsharvester < [INPUT CSV FILE WITH GND IDENTIFIERS] > [PATH TO THE OUTPUT LINE-DELIMITED JSON RECORDS FILE]',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
args = parser.parse_args()
if hasattr(args, 'help') and args.help:
parser.print_usage(sys.stderr)
exit(-1)
source = create(push_input)
all_in_one = source.pipe(
op.map(lambda line: get_gnd_identifier(line)),
op.map(lambda gnd_identifier: retrieve_entityfacts_sheet_obs(
gnd_identifier)),
op.map(lambda ef_sheet_tuple_obs: format_entityfacts_sheet_obs(
ef_sheet_tuple_obs)),
op.map(lambda flat_ef_sheet_json_tuple_obs:
write_entityfacts_sheet_obs(flat_ef_sheet_json_tuple_obs)),
op.flat_map(lambda x: x))
all_in_one.subscribe(on_next=lambda gnd_identifier: eprint(
"PROCESSED GND identifier '{0}': {1}".format(gnd_identifier,
current_thread().name)),
on_error=lambda e: eprint(e),
on_completed=lambda: eprint("PROCESS done!"),
scheduler=THREAD_POOL_SCHEDULER)
def create():
def mapper(x_yy):
x, yy = x_yy
return yy.pipe(
ops.map(lambda y: '{}{}'.format(x.value, y.value)))
return xs.pipe(
ops.group_join(
ys,
lambda x: rx.timer(x.interval),
lambda y: rx.timer(y.interval).pipe(
ops.flat_map(
rx.throw(ex) if y.value == "tin" else rx.empty())),
),
ops.flat_map(mapper),
)
def cartesian_product():
"""
this method take stream of list (--[a,b]--[1,2]-->)
convert each list to a stream (--a--b--> --1--2-->)
convert output to a stream contain one list of streams (--[--a--b--> , --1--2-->]-->)
convert output to a cartesian product stream (--[a,1]--[a,2]--[b,1]--[b,2]-->)
"""
def cartesian(sources):
"""
this method take list of streams (--[--a--b--> , --1--2-->]-->)
convert output to a cartesian product stream (--[a,1]--[a,2]--[b,1]--[b,2]-->)
"""
if len(sources) == 0:
return empty()
result = sources[0].pipe(ops.map(lambda s: [s]))
def two_streams_product(stream2, stream1):
product = stream1.pipe(
ops.flat_map(
lambda s1: stream2.pipe(ops.map(lambda s2: s1 + [s2]))))
return product
for i in range(1, len(sources)):
result = two_streams_product(sources[i], result)
return result
return pipe(ops.map(lambda _list: from_list(_list)), ops.to_list(),
ops.flat_map(lambda i: cartesian(i)))
def getCategoryAndDependencies(selectedJobId):
return rx.of(selectedJobId).pipe(
ops.flat_map(
lambda selectedJobId: getCategory(selectedJobId)
),
ops.flat_map(
lambda category: getTestruns(category)
),
ops.flat_map(
lambda testruns: rx.from_(testruns)
),
ops.map(
lambda testrun: getTestrunDependencies(testrun)
),
ops.merge(max_concurrent=1),
)
def factory():
def projection(x):
invoked[0] += 1
if invoked[0] == 3:
raise Exception(ex)
return x
return xs.pipe(ops.flat_map(projection))
def logs(self, number_of_lines: int) -> Observable[str]:
return rx.from_callable(lambda: self._client.post_json({'uri': self._uri, 'numberOfLines': number_of_lines},
url_postfix="/skill/logs"), self._scheduler) \
.pipe(
ops.map(lambda r: json.loads(r.content)),
ops.flat_map(lambda r: rx.from_iterable(r['logLines']))
)
def demo_flatmap3():
'''tuple unpacking'''
a = rx.of([1, 2], [3, 4])
a.pipe(ops.flat_map(lambda x: x)
#ops.flat_map(range)
).subscribe(print)
def execute_task(task):
def start():
task.start()
return task.status()['id']
def load_status():
return task.status()
def extract_state(status):
state = status['state']
if state == 'FAILED':
return throw(ee.EEException(status.get('error_message')))
else:
return of(state)
def monitor():
def is_running(state):
return state in [Task.State.UNSUBMITTED, Task.State.READY, Task.State.RUNNING]
return interval(_MONITORING_FREQUENCY).pipe(
flat_map(lambda _: execute(
action=load_status,
description='monitor task ' + str(task))
),
flat_map(extract_state),
distinct_until_changed(),
take_while(is_running, inclusive=True)
)
return execute(start, description='start task ' + str(task)).pipe(
flat_map(lambda _: monitor())
)
def create():
pfh = self.test_obs.pipe(pairwise_buffer, ops.map(lambda x: x[0]))
w = pfh.pipe(
ops.window(
self.test_obs.pipe(pairwise_buffer,
ops.filter(lambda x: x[0] != x[1]))))
return w.pipe(ops.flat_map(lambda x: x.pipe(ops.to_list())))
def _buffer_with_time(timespan: typing.RelativeTime, timeshift: typing.RelativeTime = None,
scheduler: typing.Scheduler = None) -> Callable[[Observable], Observable]:
if not timeshift:
timeshift = timespan
return pipe(
ops.window_with_time(timespan, timeshift, scheduler),
ops.flat_map(lambda x: x.pipe(ops.to_iterable()))
)
def create():
def mapper(x_yy):
x, yy = x_yy
return yy.pipe(ops.map(lambda y: '{}{}'.format(x.value, y.value)))
return xs.pipe(
ops.group_join(
ys,
lambda x: new_timer(xsd, x.interval, scheduler),
lambda y: new_timer(ysd, y.interval, scheduler),
),
ops.flat_map(mapper),
)
def create():
def mapper(xy):
x, y = xy
return "{}{}".format(x.value, y.value)
return xs.pipe(
ops.join(
ys,
lambda x: rx.timer(x.interval),
lambda y: rx.timer(y.interval).pipe(ops.flat_map(rx.throw(ex) if y.value == "tin" else rx.empty())),
),
ops.map(mapper),
)
def create():
def mapper(x_yy):
x, yy = x_yy
return yy.pipe(ops.map(lambda y: '{}{}'.format(x.value, y.value)))
return xs.pipe(
ops.group_join(
ys,
lambda x: rx.timer(x.interval).pipe(ops.filter(lambda _: False)),
lambda y: rx.timer(y.interval).pipe(ops.filter(lambda _: False)),
),
ops.flat_map(mapper),
)
def buffer_with_count(source: Observable) -> Observable:
nonlocal skip
if skip is None:
skip = count
def mapper(value):
return value.pipe(ops.to_iterable(), ops.map(list))
def predicate(value):
return len(value) > 0
return source.pipe(ops.window_with_count(count, skip), ops.flat_map(mapper), ops.filter(predicate))
def test_flat_map_then_error_error(self):
ex = 'ex'
scheduler = TestScheduler()
xs = scheduler.create_cold_observable(
on_next(100, 4), on_next(200, 2), on_next(300, 3),
on_next(400, 1), on_error(500, ex))
ys = scheduler.create_cold_observable(
on_next(50, "foo"), on_next(100, "bar"), on_next(150, "baz"),
on_next(200, "qux"), on_error(250, ex))
results = scheduler.start(lambda: xs.pipe(ops.flat_map(ys)))
assert results.messages == [
on_next(350, "foo"), on_next(400, "bar"), on_next(450, "baz"),
on_next(450, "foo"), on_next(500, "qux"), on_next(500, "bar"),
on_error(550, ex)]
assert xs.subscriptions == [subscribe(200, 550)]
assert ys.subscriptions == [
subscribe(300, 550), subscribe(400, 550), subscribe(500, 550)]
def create():
def right_duration_mapper(y):
if len(y.value) >= 0:
raise Exception(ex)
else:
return rx.empty()
def mapper(x_yy):
x, yy = x_yy
return yy.pipe(ops.map(lambda y: '{}{}'.format(x.value, y.value)))
return xs.pipe(
ops.group_join(
ys,
lambda x: rx.timer(x.interval),
right_duration_mapper,
),
ops.flat_map(mapper),
)
def open(self):
print("WebSocket opened")
# A Subject is both an observable and observer, so we can both subscribe
# to it and also feed (on_next) it with new values
self.subject = Subject()
# Now we take on our magic glasses and project the stream of bytes into
# a ...
query = self.subject.pipe(
# 1. stream of keycodes
ops.map(lambda obj: obj["keycode"]),
# 2. stream of windows (10 ints long)
ops.window_with_count(10, 1),
# 3. stream of booleans, True or False
ops.flat_map(lambda win: win.pipe(ops.sequence_equal(codes))),
# 4. stream of Trues
ops.filter(lambda equal: equal)
)
# 4. we then subscribe to the Trues, and signal Konami! if we see any
query.subscribe(lambda x: self.write_message("Konami!"))
def _buffer(buffer_openings=None, buffer_closing_mapper=None) -> Callable[[Observable], Observable]:
"""Projects each element of an observable sequence into zero or more
buffers.
Args:
buffer_openings -- Observable sequence whose elements denote the
creation of windows.
buffer_closing_mapper -- [optional] A function invoked to define
the closing of each produced window. If a closing mapper
function is specified for the first parameter, this parameter is
ignored.
Returns:
A function that takes an observable source and retuerns an
observable sequence of windows.
"""
return pipe(
ops.window(buffer_openings, buffer_closing_mapper),
ops.flat_map(pipe(ops.to_iterable(), ops.map(list)))
)
def test_flat_map_then_complete_never(self):
scheduler = TestScheduler()
xs = scheduler.create_cold_observable(
on_next(100, 4), on_next(200, 2), on_next(300, 3),
on_next(400, 1), on_completed(500))
ys = scheduler.create_cold_observable(
on_next(50, "foo"), on_next(100, "bar"), on_next(150, "baz"),
on_next(200, "qux"))
results = scheduler.start(lambda: xs.pipe(ops.flat_map(ys)))
assert results.messages == [
on_next(350, "foo"), on_next(400, "bar"), on_next(450, "baz"),
on_next(450, "foo"), on_next(500, "qux"), on_next(500, "bar"),
on_next(550, "baz"), on_next(550, "foo"), on_next(600, "qux"),
on_next(600, "bar"), on_next(650, "baz"), on_next(650, "foo"),
on_next(700, "qux"), on_next(700, "bar"), on_next(750, "baz"),
on_next(800, "qux")]
assert xs.subscriptions == [subscribe(200, 700)]
assert ys.subscriptions == [
subscribe(300, 1000), subscribe(400, 1000),
subscribe(500, 1000), subscribe(600, 1000)]
def factory():
def projection(x):
return rx.interval(10).pipe(ops.map_indexed(lambda a, b: x), ops.take(x))
return xs.pipe(ops.flat_map(projection))
def _buffer_with_time_or_count(timespan, count, scheduler = None) -> Callable[[Observable], Observable]:
return pipe(
ops.window_with_time_or_count(timespan, count, scheduler),
ops.flat_map(lambda x: x.pipe(ops.to_iterable()))
)
import concurrent.futures
import time
import rx
from rx import operators as ops
seconds = [5, 1, 2, 4, 3]
def sleep(tm):
time.sleep(tm)
return tm
def output(result):
print('%d seconds' % result)
with concurrent.futures.ProcessPoolExecutor(5) as executor:
rx.from_(seconds).pipe(
ops.flat_map(lambda s: executor.submit(sleep, s))
).subscribe(output)
# 1 seconds
# 2 seconds
# 3 seconds
# 4 seconds
# 5 seconds
def factory():
return xs.pipe(ops.flat_map(lambda x: x))
def create():
return xs.pipe(ops.flat_map(lambda x: x))
def factory():
return xs.pipe(ops.flat_map(ys))
def create():
def mapper(x):
ys = [x] * x
inners.append(ys)
return ys
return xs.pipe(ops.flat_map(mapper))
"""
Tests MergeMap from rxjs
https://github.com/ReactiveX/rxjs/blob/master/spec/operators/mergeMap-spec.ts
it should flat_map many regular interval inners
"""
with marbles_testing(timespan=1.0) as context:
start, cold, hot, exp = context
a = cold(' ----a---a----a----(a,|) ')
b = cold(' ----1----b----(b,|) ')
c = cold(' -------c---c---c----c---(c,|)')
d = cold(' -------(d,|) ')
e1 = hot('-a---b-----------c-------d------------| ')
ex = exp('-----a---(a,1)(a,b)(a,b)c---c---(c,d)c---(c,|)')
expected = ex
observableLookup = {"a": a, "b": b, "c": c, "d": d}
obs = e1.pipe(
ops.flat_map(lambda value: observableLookup[value])
)
results = start(obs)
assert results == expected
print('flat_map: results vs expected')
for r, e in zip(results, expected):
print(r, e)
