def open(self):
        scheduler = AsyncIOScheduler()

        print("WebSocket opened")

        # A Subject is both an observable and observer, so we can both subscribe
        # to it and also feed (send) it with new values
        self.subject = Subject()

        # Get all distinct key up events from the input and only fire if long enough and distinct
        searcher = self.subject.pipe(
            ops.map(lambda x: x["term"]),
            ops.filter(lambda text: len(text) > 2),  # Only if the text is longer than 2 characters
            ops.debounce(0.750),                     # Pause for 750ms
            ops.distinct_until_changed(),            # Only if the value has changed
            ops.flat_map_latest(search_wikipedia)
        )

        def send_response(x):
            self.write_message(x.body)

        def on_error(ex):
            print(ex)

        searcher.subscribe(send_response, on_error, scheduler=scheduler)
Beispiel #2
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def main():
    app = QApplication(sys.argv)
    scheduler = QtScheduler(QtCore)

    window = Window()
    window.show()

    text = 'TIME FLIES LIKE AN ARROW'

    def on_next(info):
        label, (x, y), i = info
        label.move(x + i*12 + 15, y)
        label.show()

    def handle_label(label, i):
        delayer = ops.delay(i * 0.100)
        mapper = ops.map(lambda xy: (label, xy, i))

        return window.mousemove.pipe(
            delayer,
            mapper,
            )

    labeler = ops.flat_map_indexed(handle_label)
    mapper = ops.map(lambda c: QLabel(c, window))

    rx.from_(text).pipe(
        mapper,
        labeler,
    ).subscribe(on_next, on_error=print, scheduler=scheduler)

    sys.exit(app.exec_())
Beispiel #3
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    def test_map_disposeinsidemapper(self):
        scheduler = TestScheduler()
        xs = scheduler.create_hot_observable(on_next(100, 1), on_next(200, 2), on_next(500, 3), on_next(600, 4))
        results = scheduler.create_observer()
        d = SerialDisposable()
        invoked = [0]

        def projection(x, *args, **kw):
            invoked[0] += 1

            if scheduler.clock > 400:
                d.dispose()
            return x

        d.disposable = xs.pipe(
            map(projection)
        ).subscribe(results, scheduler)

        def action(scheduler, state):
            return d.dispose()

        scheduler.schedule_absolute(ReactiveTest.disposed, action)
        scheduler.start()

        assert results.messages == [on_next(100, 1), on_next(200, 2)]
        assert xs.subscriptions == [ReactiveTest.subscribe(0, 500)]

        assert invoked[0] == 3
Beispiel #4
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    def handle_label(label, i):
        delayer = ops.delay(i*0.100)
        mapper = ops.map(lambda xy: (label, xy, i))

        return window.mousemove.pipe(
            delayer,
            mapper,
        )
Beispiel #5
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        def factory():
            def projection(x):
                invoked[0] += 1
                if invoked[0] == 3:
                    raise Exception(ex)

                return x + 1
            return xs.pipe(map(projection))
        def create():
            def mapper(x):
                return TimeInterval(x.value, x.interval)

            return xs.pipe(
                ops.time_interval(),
                ops.map(mapper),
            )
        def create():
            def mapper(x):
                return Timestamp(x.value, x.timestamp)

            return xs.pipe(
                ops.timestamp(),
                ops.map(mapper),
            )
        def factory():
            def key_mapper(x):
                key_invoked[0] += 1
                return x.lower().strip()

            return xs.pipe(
                    ops.group_by(key_mapper, lambda x: x),
                    ops.map(lambda g: g.key),
                    )
    def handle_label(label, i):
        label.config(dict(borderwidth=0, padx=0, pady=0))

        mapper = ops.map(lambda ev: (label, ev, i))
        delayer = ops.delay(i*0.1)

        return mousemove.pipe(
            delayer,
            mapper
        )
Beispiel #10
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def _all(predicate: Predicate) -> Callable[[Observable], Observable]:

    filtering = ops.filter(lambda v: not predicate(v))
    mapping = ops.map(lambda b: not b)
    some = ops.some()

    return pipe(
        filtering,
        some,
        mapping
    )
Beispiel #11
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def _pluck(key: Any) -> Callable[[Observable], Observable]:
    """Retrieves the value of a specified key using dict-like access (as in
    element[key]) from all elements in the Observable sequence.

    Args:
        key: The key to pluck.

    Returns a new Observable {Observable} sequence of key values.

    To pluck an attribute of each element, use pluck_attr.
    """

    return ops.map(lambda x: x[key])
        def factory():
            def key_mapper(x):
                key_invoked[0] += 1
                return x.lower().strip()

            def element_mapper(x):
                ele_invoked[0] += 1
                return x[::-1]  # Yes, this is reverse string in Python

            return xs.pipe(
                    ops.group_by(key_mapper, element_mapper),
                    ops.map(lambda g: g.key),
                    )
Beispiel #13
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    def average(source: Observable) -> Observable:
        """Partially applied average operator.

        Computes the average of an observable sequence of values that
        are in the sequence or obtained by invoking a transform
        function on each element of the input sequence if present.

        Examples:
            >>> res = average(source)

        Args:
            source: Source observable to average.

        Returns:
            An observable sequence containing a single element with the
            average of the sequence of values.
        """

        if key_mapper:
            return source.pipe(
                operators.map(key_mapper),
                operators.average()
            )

        def accumulator(prev, cur):
            return AverageValue(sum=prev.sum+cur, count=prev.count+1)

        def mapper(s):
            if s.count == 0:
                raise Exception('The input sequence was empty')

            return s.sum / float(s.count)

        seed = AverageValue(sum=0, count=0)
        return source.pipe(
            operators.scan(accumulator, seed),
            operators.last(),
            operators.map(mapper)
        )
        def factory():
            def key_mapper(x):
                key_invoked[0] += 1
                return x.lower().strip()

            def element_mapper(x):
                ele_invoked[0] += 1
                return x[::-1]

            return xs.pipe(
                    ops.group_by(key_mapper, element_mapper),
                    ops.map(lambda g: g.key),
                    )
        def subscribe(observer, scheduler_):
            _scheduler = scheduler or scheduler_ or timeout_scheduler
            last = _scheduler.now

            def mapper(value):
                nonlocal last

                now = _scheduler.now
                span = now - last
                last = now
                return TimeInterval(value=value, interval=span)

            return source.pipe(ops.map(mapper)).subscribe(observer, scheduler_)
Beispiel #16
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        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),
                    ),
                ops.map(mapper),
                )
Beispiel #17
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        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),
                )
Beispiel #18
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def observable_window_with_openings(self, window_openings, window_closing_mapper):

    def mapper(args):
        _, window = args
        return window

    return window_openings.pipe(
        ops.group_join(
            self,
            window_closing_mapper,
            lambda _: empty(),
            ),
        ops.map(mapper),
        )
Beispiel #19
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def _pluck_attr(prop: str) -> Callable[[Observable], Observable]:
    """Retrieves the value of a specified property (using getattr) from
    all elements in the Observable sequence.

    Args:
        property: The property to pluck.

    Returns a new Observable {Observable} sequence of property values.

    To pluck values using dict-like access (as in element[key]) on each
    element, use pluck.
    """

    return ops.map(lambda x: getattr(x, prop))
Beispiel #20
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        def factory(scheduler):
            nonlocal source

            has_accumulation = [False]
            accumulation = [None]

            def projection(x):
                if has_accumulation[0]:
                    accumulation[0] = accumulator(accumulation[0], x)
                else:
                    accumulation[0] = accumulator(seed, x) if has_seed else x
                    has_accumulation[0] = True

                return accumulation[0]
            return source.pipe(ops.map(projection))
Beispiel #21
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    def test_map_throws(self):
        mapper = map(lambda x: x)
        with self.assertRaises(RxException):
            return_value(1).pipe(
                mapper
            ).subscribe(lambda x: _raise("ex"))

        with self.assertRaises(RxException):
            throw('ex').pipe(
                mapper
            ).subscribe(on_error=lambda ex: _raise(ex))

        with self.assertRaises(RxException):
            empty().pipe(
                mapper
            ).subscribe(lambda x: x, lambda ex: ex, lambda: _raise('ex'))

        def subscribe(observer, scheduler=None):
            _raise('ex')

        with self.assertRaises(RxException):
            create(subscribe).pipe(
                map(lambda x: x)
            ).subscribe()
Beispiel #22
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        def factory(scheduler):
            has_accumulation = False
            accumulation = None

            def projection(x):
                nonlocal has_accumulation
                nonlocal accumulation

                if has_accumulation:
                    accumulation = accumulator(accumulation, x)
                else:
                    accumulation = accumulator(seed, x) if has_seed else x
                    has_accumulation = True

                return accumulation
            return source.pipe(ops.map(projection))
Beispiel #23
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def main():
    scheduler = GtkScheduler()
    scrolled_window = Gtk.ScrolledWindow()

    window = Window()
    window.connect("delete-event", Gtk.main_quit)

    container = Gtk.Fixed()

    scrolled_window.add(container)
    window.add(scrolled_window)
    text = 'TIME FLIES LIKE AN ARROW'

    def on_next(info):
        label, (x, y), i = info
        container.move(label, x + i*12 + 15, y)
        label.show()

    def handle_label(label, i):
        delayer = ops.delay(i*0.100)
        mapper = ops.map(lambda xy: (label, xy, i))

        return window.mousemove.pipe(
            delayer,
            mapper,
        )

    def make_label(char):
        label = Gtk.Label(label=char)
        container.put(label, 0, 0)
        label.hide()
        return label

    mapper = ops.map(make_label)
    labeler = ops.flat_map_indexed(handle_label)

    rx.from_(text).pipe(
        mapper,
        labeler,
    ).subscribe(on_next, on_error=print, scheduler=scheduler)

    window.show_all()

    Gtk.main()
Beispiel #24
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        def create():
            def right_duration_mapper(y):
                if len(y.value) >= 0:
                    raise Exception(ex)
                else:
                    return rx.empty()

            def mapper(xy):
                x, y = xy
                return "{}{}".format(x.value, y.value)

            return xs.pipe(
                ops.join(
                    ys,
                    lambda x: rx.timer(x.interval),
                    right_duration_mapper,
                    ),
                ops.map(mapper),
                )
Beispiel #25
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def _max(comparer: Optional[Comparer] = None) -> Callable[[Observable], Observable]:
    """Returns the maximum value in an observable sequence according to
    the specified comparer.

    Examples:
        >>> op = max()
        >>> op = max(lambda x, y:  x.value - y.value)

    Args:
        comparer: [Optional] Comparer used to compare elements.

    Returns:
        An operator function that takes an observable source and returns
        an observable sequence containing a single element with the
        maximum element in the source sequence.
    """

    return pipe(
        ops.max_by(identity, comparer),
        ops.map(first_only)
    )
Beispiel #26
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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)))
    )
Beispiel #27
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    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!"))
Beispiel #28
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def _min(comparer: Callable = None) -> Callable[[Observable], Observable]:
    """The `min` operator.

    Returns the minimum element in an observable sequence according to
    the optional comparer else a default greater than less than check.

    Examples:
        >>> res = source.min()
        >>> res = source.min(lambda x, y: x.value - y.value)

    Args:
        comparer: [Optional] Comparer used to compare elements.

    Returns:
        An observable sequence containing a single element
        with the minimum element in the source sequence.
    """

    return pipe(
        ops.min_by(identity, comparer),
        ops.map(first_only)
    )
Beispiel #29
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    def flat_map_latest(source: Observable) -> Observable:
        """Projects each element of an observable sequence into a new
        sequence of observable sequences by incorporating the element's
        index and then transforms an observable sequence of observable
        sequences into an observable sequence producing values only
        from the most recent observable sequence.

        Args:
            source: Source observable to flat map latest.

        Returns:
            An observable sequence whose elements are the result of
            invoking the transform function on each element of source
            producing an observable of Observable sequences and that at
            any point in time produces the elements of the most recent
            inner observable sequence that has been received.
        """

        return source.pipe(
            ops.map(mapper),
            ops.switch_latest()
        )
def main():
    root = Tk()
    root.title("Rx for Python rocks")
    scheduler = TkinterScheduler(root)

    mousemove = Subject()

    frame = Frame(root, width=600, height=600)

    frame.bind("<Motion>", mousemove.on_next)

    text = 'TIME FLIES LIKE AN ARROW'

    def on_next(info):
        label, ev, i = info
        label.place(x=ev.x + i*12 + 15, y=ev.y)

    def handle_label(label, i):
        label.config(dict(borderwidth=0, padx=0, pady=0))

        mapper = ops.map(lambda ev: (label, ev, i))
        delayer = ops.delay(i*0.1)

        return mousemove.pipe(
            delayer,
            mapper
        )

    labeler = ops.flat_map_indexed(handle_label)
    mapper = ops.map(lambda c: Label(frame, text=c))

    rx.from_(text).pipe(
        mapper,
        labeler
    ).subscribe(on_next, on_error=print, scheduler=scheduler)

    frame.pack()
    root.mainloop()
Beispiel #31
0
from rx import operators as ops
import asyncio

loop = asyncio.get_event_loop()
done = loop.create_future()

filepath = os.path.join(VIDEO_DIR, 'nascar_01.mp4')

inputparameters = {}
outputparameters = {}

videogen = skvideo.io.vreader(filepath,
                              inputdict=inputparameters,
                              outputdict=outputparameters)

source = rx.from_iterable(videogen).pipe(ops.map(vision.rgb_to_bgr))
dm = vision.DisplayManager('Nascar')


class Player:
    def __init__(self):
        self.count = 0

    def on_next(self, frame):
        self.count += 1
        print("frame: {} {}".format(self.count, frame.shape))
        dm.show(frame)
        vision.wait_for_esc_key(40)
        pass

    def on_error(self, error):
Beispiel #32
0
 def mapper(ys):
     return ys.pipe(
             ops.zip(ys),
             ops.map(sum),
             )
Beispiel #33
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 def _map(source):
     if isinstance(source, rs.MuxObservable):
         return map_mux(mapper)(source)
     else:
         return ops.map(mapper)(source)
from rx import from_, operators as ops

from_(["Alpha", "Theta", "Kappa", "Beta", "Gamma", "Delta", "Epsilon"]).pipe(
    ops.map(lambda s: len(s)),
    ops.distinct_until_changed()
).subscribe(lambda i: print(i))


from_(["Alpha", "Theta", "Kappa", "Beta", "Gamma", "Delta", "Epsilon"]).pipe(
    ops.distinct_until_changed(lambda s: len(s))
).subscribe(lambda i: print(i))
Beispiel #35
0
    def on_completed(self):
        print("Finished")

    def on_error(self, error):
        print("Error: {}".format(error))


some_urls = ["google", "youtube", "twitter", "stackoverflow", "localhost"]
print("urls in order to be queried")
print(some_urls)
source = rx.create(rx_url_loop(some_urls))

source.pipe(
    op.filter(lambda x: x.get("time") % 2 == 0),
    op.map(lambda x: {
        "url": x.get("url").upper(),
        "time": x.get("time")
    }),
    op.map(
        lambda x: "Received: {0}, has successfully completed after {1} seconds"
        .format(x.get("url"), x.get("time")))).subscribe(RxAsyncRequest())

# other_urls = ["yahoo", "vk", "instagram", "reddit", "noip"]
# print(other_urls)
# source2 = of(*other_urls)
# source2.pipe(
#     op.map(lambda s: len(s)),
#     op.filter(lambda s: s > 5)
# ).subscribe(RxAsyncRequest())
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.element_at()
op.first()
op.ignore_elements()
op.last()
op.skip()
op.skip_last()
op.take()
op.take_last()
Beispiel #37
0
def capitalize():
    return op.pipe(
        op.map(lambda i: i.capitalize())
    )
Beispiel #38
0
def deepspeech_server(aio_scheduler, sources):
    argv = sources.argv.argv
    stt = sources.httpd.route
    stt_response = sources.deepspeech.text
    ds_logs = sources.deepspeech.log

    http_ds_error, route_ds_error = make_error_router()

    args = parse_arguments(argv)

    read_request, read_response = args.pipe(
        ops.map(lambda i: file.Read(id='config', path=i.value)),
        file.read(sources.file.response),
    )
    read_request = read_request.pipe(ops.subscribe_on(aio_scheduler), )
    config = parse_config(read_response)

    logs_config = config.pipe(
        ops.flat_map(
            lambda i: rx.from_(i.log.level, scheduler=ImmediateScheduler())),
        ops.map(lambda i: logging.SetLevel(logger=i.logger, level=i.level)),
    )
    logs = rx.merge(logs_config, ds_logs)

    ds_stt = stt.pipe(
        ops.flat_map(lambda i: i.request),
        ops.map(
            lambda i: deepspeech.SpeechToText(data=i.data, context=i.context)),
    )

    # config is hot, the combine operator allows to keep its last value
    # until logging is initialized
    ds_arg = config.pipe(
        ops.map(lambda i: deepspeech.Initialize(
            model=i.deepspeech.model,
            scorer=deepspeech.Scorer(
                scorer=getattr(i.deepspeech, 'scorer', None),
                lm_alpha=getattr(i.deepspeech, 'lm_alpha', None),
                lm_beta=getattr(i.deepspeech, 'lm_beta', None),
            ),
            beam_width=getattr(i.deepspeech, 'beam_width', None),
        )), )
    ds = rx.merge(ds_stt, ds_arg)

    http_init = config.pipe(
        ops.flat_map(lambda i: rx.from_([
            httpd.Initialize(request_max_size=i.server.http.request_max_size),
            httpd.AddRoute(
                methods=['POST'],
                path='/stt',
                id='stt',
            ),
            httpd.StartServer(host=i.server.http.host, port=i.server.http.port
                              ),
        ])), )

    http_response = stt_response.pipe(
        route_ds_error(error_map=lambda e: httpd.Response(
            data="Speech to text error".encode('utf-8'),
            context=e.args[0].context,
            status=500)),
        ops.map(lambda i: httpd.Response(
            data=i.text.encode('utf-8'),
            context=i.context,
        )),
    )

    http = rx.merge(http_init, http_response, http_ds_error)

    return DeepspeechSink(file=file.Sink(request=read_request),
                          logging=logging.Sink(request=logs),
                          deepspeech=deepspeech.Sink(speech=ds),
                          httpd=httpd.Sink(control=http))
Beispiel #39
0
def expand_and_next(mbs):
    logging.info(f"in CalcService.fetch_values {mbs}")
    rx.from_(mbs).pipe(ops.map(expand_array), ops.do_action(
        stream.on_next)).subscribe(
            on_next=lambda data: logging.info(f"expand_and_next {data}"),
            on_error=print_error)
Beispiel #40
0
 def mapper(w, i):
     return w.pipe(ops.map(lambda x: "%s %s" % (i, x)))
Beispiel #41
0
import rx
from rx import operators as ops

items = ["134/34/235/132/77", "64/22/98/112/86/11", "66/08/34/778/22/12"]

rx.from_(items).pipe(ops.flat_map(lambda s: rx.from_(s.split("/"))),
                     ops.map(lambda s: int(s))).subscribe(lambda i: print(i))
Beispiel #42
0
            def mapper(ys, i):
                def proj(y):
                    return "%s %s" % (i, y)

                return ys.pipe(ops.map(proj), ops.concat(rx.return_value('%s end' % i)))
Beispiel #43
0
rowStream = rx.create(observeRowPins(ROW_PINS))

#colStream.subscribe(on_next=lambda i: print(i))
#rowStream.subscribe(on_next=lambda i: print(i))

def findKey(xy):
  row, col = xy
  return KEYPAD[row.n][col.n]

keyStream = rowStream.pipe(
                ops.join(
                  colStream,
                  lambda l: rx.timer(.01),
                  lambda r: rx.timer(.01)
                ),
                ops.map(findKey),
            )

def makeColor(i):
  print(i)
  if i == 1:
    led.red = 1
  if i == 2:
    led.green = 1
  if i == 3:
    led.blue = 1
  if i == 4:
    led.red = 0.66
  if i == 5:
    led.green = 0.66
  if i == 6:
Beispiel #44
0
import rx
from rx import operators as ops

items = ["134/34/235/132/77", "64/22/98/112/86/11", "66/08/34/778/22/12"]

# RxPy v3.0 에서 부터 concat_all() 이 없어지고 merge 연산을 사용하고 max_concurrent 아규먼트를 1로 설정하도록 변경되었다.

rx.from_(items).pipe(
    ops.map(lambda s: rx.from_(s.split("/"))),
    ops.merge(max_concurrent=1),
    ops.map(lambda s: int(s))
).subscribe(
    lambda i: print(i)
)




Beispiel #45
0
import rx
from rx import operators as ops

letters = rx.from_(["Alpha", "Beta", "Gamma", "Delta", "Epsilon"])
intervals = rx.interval(1.0)

letters.pipe(ops.zip(intervals),
             ops.map(lambda z: z[0])).subscribe(lambda s: print(s))

input("Press any key to quit\n")
Beispiel #46
0
def left(a: Observable) -> Observable:
    return a.pipe(ops.map(lambda v: (v, None)))
Beispiel #47
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import rx
from rx import operators as ops

rx.from_(["Alpha", "Beta", "Gamma", "Delta", "Epsilon"]).pipe(
    ops.group_by(lambda s: len(s)),
    ops.flat_map(
        lambda grp: grp.pipe(ops.count(), ops.map(lambda ct: (grp.key, ct)))),
    ops.to_dict(lambda key_value: key_value[0],
                lambda key_value: key_value[1])).subscribe(lambda i: print(i))
Beispiel #48
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import rx
import rx.operators as ops
from rx.scheduler import NewThreadScheduler
import threading
import time

new_thread_scheduler = NewThreadScheduler()
numbers = rx.from_([1, 2, 3, 4])

subscription = numbers.pipe(
    ops.map(lambda i: i*2),
    ops.observe_on(new_thread_scheduler),
    ops.map(lambda i: "number is: {}".format(i)),
).subscribe(
        on_next=lambda i: print("on_next({}) {}"
            .format(threading.get_ident(), i)),
        on_error=lambda e: print("on_error({}): {}"
            .format(threading.get_ident(), e)),
        on_completed=lambda: print("on_completed({})"
            .format(threading.get_ident()))
    )

print("main({})".format(threading.get_ident()))
time.sleep(1.0)

Beispiel #49
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def extract_word(word, filter_word):
    return rx.from_(word).pipe(
        ops.filter(lambda tup: tup[1] == filter_word and len(tup[0]) > 1),
        ops.map(lambda tup: tup[0]),
        ops.reduce(lambda acc, t1: acc + " " + t1))
Beispiel #50
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def add_and_multiply(nums, add_value, multiply_value):
    return nums.pipe(
        ops.map(lambda i: i + add_value),
        ops.map(lambda i: i * multiply_value)
    )
Beispiel #51
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from rx import from_, interval, operators as ops

source1 = interval(10).pipe(ops.map(lambda i: "Source 1: {0}".format(i)))
source2 = interval(5).pipe(ops.map(lambda i: "Source 2: {0}".format(i)))
source3 = interval(3).pipe(ops.map(lambda i: "Source 3: {0}".format(i)))

from_([source1, source2,
       source3]).pipe(ops.merge_all()).subscribe(lambda s: print(s))

# keep application alive until user presses a key
input("Press any key to quit\n")
Beispiel #52
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def right(a: Observable) -> Observable:
    return a.pipe(ops.map(lambda v: (None, v)))
Beispiel #53
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def worker(consumer):
    # num_cores = multiprocessing.cpu_count()
    with ProcessPoolExecutor(3) as executor:
        rx.from_(consumer.iterable).pipe(
            ops.map(lambda msg: executor.submit(consumer.process_consumer, msg)
                    ), ).subscribe(consumer)
Beispiel #54
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from rx import interval, operators as ops

"""
this method will give a series of values produced after a timeout.

:parameter
    period: to start the Number sequence
    
:return value
    it returns an observable with all the values in sequential order
"""

my_interval = interval(1.2).pipe(
    ops.map(lambda i: i * i),
    # ops.map(lambda x: x + " x") ## TypeError: unsupported operand type(s) for +: 'int' and 'str'
).subscribe(lambda x: print("value is {}".format(x)))

input("press any key to exit\n")
Beispiel #55
0
def get_token_stream(context: Context) -> Observable:
    return return_value(context).pipe(
        op.map(validate_grant_type),
        op.flat_map(call_async(validate_code)),
        op.flat_map(call_async(get_token_by_code)),
    )
Beispiel #56
0
import rx
import rx.operators as ops
from time import sleep


NUM_TESTRUNS_PER_CATEGORY = 3

source = rx.timer(0, 7).pipe(
    ops.map(lambda i: i + 1),
    ops.take(2),
)

testresultStream = source.pipe(
    ops.flat_map_latest(
        lambda selectedJobId: getCategoryAndDependencies(selectedJobId)
    ),
)


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(
Beispiel #57
0
import rx
import rx.operators as ops


def add_and_multiply(nums, add_value, multiply_value):
    return nums.pipe(
        ops.map(lambda i: i + add_value),
        ops.map(lambda i: i * multiply_value)
    )


numbers = rx.from_([1, 2, 3]).pipe(
    ops.map(lambda i: i + 1),
    ops.map(lambda i: i * 2)
)


numbers.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")
)
Beispiel #58
0
 def _next_valid_id(self) -> int:
     self._eclient.reqIds(-1)  # Argument is ignored
     return self._messages.pipe(
         _.first(lambda m: m.type == IbApiMessageType.NEXT_VALID_ID),
         _.map(lambda m: m.payload[0])).run()
Beispiel #59
0
import rx
from rx import operators as ops

source1 = rx.interval(1.0).pipe(
    ops.map(lambda i: "Source 1: {0}".format(i))
)
source2 = rx.interval(0.5).pipe(
    ops.map(lambda i: "Source 2: {0}".format(i))
)
source3 = rx.interval(0.3).pipe(
    ops.map(lambda i: "Source 3: {0}".format(i))
)

rx.merge(source1, source2, source3).subscribe(lambda s: print(s))

# keep application alive until user presses a key
input("Press any key to quit\n")

Beispiel #60
0
from rx import of, operators as op
import rx

ob = of(1, 2, 34, 5, 6, 7, 7)
subscription = ob.pipe(
    op.map(lambda i: i ** 2),
    op.filter(lambda i: i >= 10)
).subscribe(lambda i: print(f'Received: {i}'))


def capitalize():
    return op.pipe(
        op.map(lambda i: i.capitalize())
    )


of('ab', 'cd', 'efg').pipe(capitalize()).subscribe(lambda i: print(f'Received: {i}'))