faust.streams

Streams.

faust.streams.current_event() → Optional[faust.types.events.EventT][source]

Return the event currently being processed, or None.

Return type:Optional[EventT[]]
class faust.streams.Stream(channel: AsyncIterator[T_co], *, app: faust.types.app.AppT, processors: Iterable[Callable[T]] = None, combined: List[faust.types.streams.JoinableT] = None, on_start: Callable = None, join_strategy: faust.types.joins.JoinT = None, beacon: mode.utils.types.trees.NodeT = None, concurrency_index: int = None, prev: faust.types.streams.StreamT = None, active_partitions: Set[faust.types.tuples.TP] = None, enable_acks: bool = True, prefix: str = '', loop: asyncio.events.AbstractEventLoop = None) → None[source]

A stream: async iterator processing events in channels/topics.

logger = <Logger faust.streams (WARNING)>
mundane_level = 'debug'
get_active_stream() → faust.types.streams.StreamT[source]

Return the currently active stream.

A stream can be derived using Stream.group_by etc, so if this stream was used to create another derived stream, this function will return the stream being actively consumed from. E.g. in the example:

>>> @app.agent()
... async def agent(a):
..      a = a
...     b = a.group_by(Withdrawal.account_id)
...     c = b.through('backup_topic')
...     async for value in c:
...         ...

The return value of a.get_active_stream() would be c.

Notes

The chain of streams that leads to the active stream is decided by the _next attribute. To get to the active stream we just traverse this linked-list:

>>> def get_active_stream(self):
...     node = self
...     while node._next:
...         node = node._next
Return type:StreamT[+T_co]
get_root_stream() → faust.types.streams.StreamT[source]
Return type:StreamT[+T_co]
add_processor(processor: Callable[T]) → None[source]

Add processor callback executed whenever a new event is received.

Processor functions can be async or non-async, must accept a single argument, and should return the value, mutated or not.

For example a processor handling a stream of numbers may modify the value:

def double(value: int) -> int:
    return value * 2

stream.add_processor(double)
Return type:None
info() → Mapping[str, Any][source]

Return stream settings as a dictionary.

Return type:Mapping[str, Any]
clone(**kwargs) → faust.types.streams.StreamT[source]

Create a clone of this stream.

Notes

If the cloned stream is supposed to “supercede” this stream, like in group_by/through/etc., you should use _chain() instead so stream._next = cloned_stream is set and get_active_stream() returns the cloned stream.

Return type:StreamT[+T_co]
noack() → faust.types.streams.StreamT[source]
Return type:StreamT[+T_co]
events() → AsyncIterable[faust.types.events.EventT][source]

Iterate over the stream as events exclusively.

This means the stream must be iterating over a channel, or at least an iterable of event objects.

Return type:AsyncIterable[EventT[]]
enumerate(start: int = 0) → AsyncIterable[Tuple[int, T_co]][source]

Enumerate values received on this stream.

Unlike Python’s built-in enumerate, this works with async generators.

Return type:AsyncIterable[Tuple[int, +T_co]]
through(channel: Union[str, faust.types.channels.ChannelT]) → faust.types.streams.StreamT[source]

Forward values to in this stream to channel.

Send messages received on this stream to another channel, and return a new stream that consumes from that channel.

Notes

The messages are forwarded after any processors have been applied.

Example

topic = app.topic('foo')

@app.agent(topic)
async def mytask(stream):
    async for value in stream.through(app.topic('bar')):
        # value was first received in topic 'foo',
        # then forwarded and consumed from topic 'bar'
        print(value)
Return type:StreamT[+T_co]
echo(*channels) → faust.types.streams.StreamT[source]

Forward values to one or more channels.

Unlike through(), we don’t consume from these channels.

Return type:StreamT[+T_co]
group_by(key: Union[faust.types.models.FieldDescriptorT, Callable[T, Union[bytes, faust.types.core._ModelT, Any, None]]], *, name: str = None, topic: faust.types.topics.TopicT = None, partitions: int = None) → faust.types.streams.StreamT[source]

Create new stream that repartitions the stream using a new key.

Parameters:
  • key (Union[FieldDescriptorT, Callable[[~T], Union[bytes, _ModelT, Any, None]]]) –

    The key argument decides how the new key is generated, it can be a field descriptor, a callable, or an async callable.

    Note: The name argument must be provided if the key
    argument is a callable.
  • name (Optional[str]) – Suffix to use for repartitioned topics. This argument is required if key is a callable.

Examples

Using a field descriptor to use a field in the event as the new key:

s = withdrawals_topic.stream()
# values in this stream are of type Withdrawal
async for event in s.group_by(Withdrawal.account_id):
    ...

Using an async callable to extract a new key:

s = withdrawals_topic.stream()

async def get_key(withdrawal):
    return await aiohttp.get(
        f'http://e.com/resolve_account/{withdrawal.account_id}')

async for event in s.group_by(get_key):
    ...

Using a regular callable to extract a new key:

s = withdrawals_topic.stream()

def get_key(withdrawal):
    return withdrawal.account_id.upper()

async for event in s.group_by(get_key):
    ...
Return type:StreamT[+T_co]
derive_topic(name: str, *, key_type: Union[Type[faust.types.models.ModelT], Type[bytes], Type[str]] = None, value_type: Union[Type[faust.types.models.ModelT], Type[bytes], Type[str]] = None, prefix: str = '', suffix: str = '') → faust.types.topics.TopicT[source]

Create Topic description derived from the K/V type of this stream.

Parameters:
  • name (str) – Topic name.
  • key_type (Union[Type[ModelT], Type[bytes], Type[str], None]) – Specific key type to use for this topic. If not set, the key type of this stream will be used.
  • value_type (Union[Type[ModelT], Type[bytes], Type[str], None]) – Specific value type to use for this topic. If not set, the value type of this stream will be used.
Raises:

ValueError – if the stream channel is not a topic.

Return type:

TopicT[]

combine(*nodes, **kwargs) → faust.types.streams.StreamT[source]
Return type:StreamT[+T_co]
contribute_to_stream(active: faust.types.streams.StreamT) → None[source]
Return type:None
join(*fields) → faust.types.streams.StreamT[source]
Return type:StreamT[+T_co]
left_join(*fields) → faust.types.streams.StreamT[source]
Return type:StreamT[+T_co]
inner_join(*fields) → faust.types.streams.StreamT[source]
Return type:StreamT[+T_co]
outer_join(*fields) → faust.types.streams.StreamT[source]
Return type:StreamT[+T_co]
coroutine on_merge(self, value: T = None) → Optional[T][source]
Return type:Optional[~T]
coroutine ack(self, event: faust.types.events.EventT) → bool[source]

Ack event.

This will decrease the reference count of the event message by one, and when the reference count reaches zero, the worker will commit the offset so that the message will not be seen by a worker again.

Parameters:event (EventT[]) – Event to ack.
Return type:bool
items() → AsyncIterator[Tuple[Union[bytes, faust.types.core._ModelT, Any, None], T_co]][source]

Iterate over the stream as key, value pairs.

Examples

@app.agent(topic)
async def mytask(stream):
    async for key, value in stream.items():
        print(key, value)
Return type:AsyncIterator[Tuple[Union[bytes, _ModelT, Any, None], +T_co]]
coroutine on_start(self) → None[source]

Service is starting.

Return type:None
coroutine on_stop(self) → None[source]

Service is being stopped/restarted.

Return type:None
coroutine remove_from_stream(self, stream: faust.types.streams.StreamT) → None[source]
Return type:None
coroutine send(self, value: T_contra) → None[source]

Send value into stream locally (bypasses topic).

Return type:None
coroutine stop(self) → None[source]

Stop the service.

Return type:None
take(max_: int, within: Union[datetime.timedelta, float, str]) → AsyncIterable[Sequence[T_co]][source]

Buffer n values at a time and yield a list of buffered values.

Parameters:within (Union[timedelta, float, str]) – Timeout for when we give up waiting for another value, and process the values we have. Warning: If there’s no timeout (i.e. timeout=None), the agent is likely to stall and block buffered events for an unreasonable length of time(!).
Return type:AsyncIterable[Sequence[+T_co]]
coroutine throw(self, exc: BaseException) → None[source]
Return type:None
label

Label used for graphs. :rtype: str

shortlabel[source]