broqer 0.1.5

Carefully crafted library to operate with continuous streams of data in a reactive style with publish/subscribe and broker functionality.

Carefully crafted library to operate with continuous streams of data in a reactive style with publish/subscribe and broker functionality.

Synopsis

• Pure python implementation without dependencies (except Python 3.5+)

• Operators known from ReactiveX and other streaming frameworks (like distinct, combine_latest, …)

• Supporting asyncio for time depended operations and using coroutines (e.g. map_async, debounce, …)

• Publishers are awaitable (e.g. await adc_raw)

• Compact library (<1000 lines of code), but well documented (>1000 lines of comments)

• Fully unit tested (coverage towards 100%), coding style checked with flake8, static typing checked with mypy

• Under MIT license (2018 Günther Jena)

Install

pip install broqer

Example

In the first example adc_raw is a Publisher emitting values from an analog digital converter. The value will be converter (scaled by factor 0.3), sampled and a moving average is applied. Filtering for values greater 1 will be printed (with the prefix ‘Voltage too high:’)

from broqer import op
import statistics

( adc_raw
  | op.map(lambda v:v*0.3) # apply a function with one argument returning to value multiplied by 0.3
  | op.sample(0.1) # periodically emit the actual value every 0.1 seconds
  | op.sliding_window(4) # append the value to a buffer with 4 elements (and drop the oldest value)
  | op.map(statistics.mean) # use ``statistics.mean`` to calulate the average over the emitted sequence
  | op.filter(lambda v:v>1) # emit only values greater 1
  | op.sink (print, 'Voltage too high:') # call ``print`` with 'Voltage too high:' and the value
)

Output to stdout:

Voltage too high: 1.25
Voltage too high: 1.5
Voltage too high: 1.75
Voltage too high: 2
Voltage too high: 2
Voltage too high: 2
Voltage too high: 2

API

Publishers

A Publisher is the source for messages.

Subject ()	Source with .emit(*args) method to publish a new message
Value (*init)	Source with a state (initialized via init)
FromIterable (iterable)	Use an iterable and emit each value

Using asyncio event loop:

FromPolling (interval, func, …)

Call func(*args, **kwargs) periodically and emit the returned values

Operators

accumulate (func, init)	Apply func(value, state) which is returning new state and value to emit
cache (*init)	Caching the emitted values to access it via .cache property
catch_exception (*exceptions)	Catching exceptions of following operators in the pipelines
combine_latest (*publishers)	Combine the latest emit of multiple publishers and emit the combination
distinct (*init)	Only emit values which changed regarding to the cached state
filter (predicate, …)	Filters values based on a predicate function
map (map_func, *args, **kwargs)	Apply map_func(*args, value, **kwargs) to each emitted value
merge (*publishers)	Merge emits of multiple publishers into one stream
pack (*args)	Emit a multi-argument emit as tuple of arguments
partition (size)	Group size emits into one emit as tuple
pluck (*picks)	Apply sequence of picks via getitem to emitted values
reduce (func, init)	Apply func to the current emitted value and the last result of func
sliding_window (size, …)	Group size emitted values overlapping
switch (mapping)	Emit selected source mapped by mapping
unpack (args)	Unpacking a sequence of values and use it to emit as arguments

Using asyncio event loop:

debounce (duetime)	Emit a value only after a given idle time (emits meanwhile are skipped)
delay (delay)	Emit every value delayed by the given time
map_async (map_coro, mode, …)	Apply map_coro to each emitted value allowing async processing
sample (interval)	Emit the last received value periodically
throttle (duration)	Rate limit emits by the given time

Subscribers

A Subscriber is the sink for messages.

sink (func, *args, **kwargs)	Apply func(*args, value, **kwargs) to each emitted value
to_future (timeout=None)	Build a future able to await for

Credits

Broqer was inspired by:

• RxPY: Reactive Extension for Python (by Børge Lanes and Dag Brattli)

• aioreactive: Async/Await reactive tools for Python (by Dag Brattli)

• streamz: build pipelines to manage continous streams of data (by Matthew Rocklin)

• MQTT: M2M connectivity protocol

• Florian Feurstein: spending hours of discussion, coming up with great ideas and help me understand the concepts!