ReactiveX Backpressure Library

rxbp is a Python library that integrates backpressure into the Observable via Flowables.

Features

• Observable Pattern: built on the reactive programming model.
• Backpressure: enables memory-safe handling of fast data producers and slow consumers.
• Continuation certificate: ensures that the execution of a Flowable completes, avoiding any continuation deadlock.
• RxPY compatibility: interoperates with RxPY, bridging classic observables and backpressure-aware Flowables.
• Favor usability - Favor an implementation that is simple, safe, and user-friendly, while accepting some computational overhead.

Installation

You can install rxbp using pip:

pip install rxbp

Example

import rxbp

source = rxbp.from_iterable(("Alpha", "Beta", "Gamma", "Delta", "Epsilon"))

flowable = (
    source
    .map(lambda s: len(s))
    .filter(lambda i: i >= 5)
    .tap(on_next=lambda v: print(f'Received {v}'))
)

# execute the flowable
rxbp.run(flowable)

<!-- ## Run a Flowable `result = rxbp.run(flowable)` ## Share a Flowable -->

Operations

Create a Flowable

• connectable - create a Flowable whose source must be specified by the connections argument when calling the run function
• count - create a Flowable emitting 0, 1, 2, ...
• create - creates a Flowable from a ContinuationMonad
• empty - create a Flowable emitting no items
• error - create a Flowable emitting an exception
• from_iterable (or from_) - create a Flowable that emits each element of an iterable
• from_value (or return_) - create a Flowable that emits a single element
• from_rx - wrap a rx.Observable and exposes it as a Flowable, relaying signals in a backpressure-aware manner.
• interval - create a Flowable emitting an item after every time interval
• repeat - create a Flowable that repeats the given element
• schedule_on - schedule task on a dedicated scheduler
• sleep (or delay) - schedule task on a dedicated scheduler after a relative time

<!-- - `schedule_relative` - schedule task on a dedicated scheduler after a relative time - `schedule_absolute` - schedule task on a dedicated scheduler after an absolute time -->

Transforming operators

• accumulate - apply an accumulator function over a Flowable sequence and returns each intermediate result.
• batch - gathers items into batches of provided size
• concat_map - apply a function to each item emitted by the source and flatten the results sequentially
• default_if_empty - emits a given value if the source completes without emitting anything
• filter - emit only those items for which the given predicate holds
• first - emit the first element only
• flat_map - apply a function to each item emitted by the source and flattens the result
• last - emit last item
• map - map each element emitted by the source by applying the given function
• reduce - apply an accumulator function over a Flowable sequence and emits a single element
• repeat - returns a Flowable that will resubscribe to the source when the source completes
• repeat_first - return a Flowable that repeats the first element it receives from the source forever (until disposed).
• skip - skip the first n items
• skip_while - skip first items while the given predicate holds
• take - take the first n items
• take_while - take items while the given predicate holds
• tap - used to perform side-effects for notifications from the source Flowable
• to_list - create a new Flowable that collects the items from the source sequence, and emits a single item
• zip_with_index - zip each item emitted by the source with the enumerated index

Combining operators

• merge - merge the items of the Flowable sequences into a single Flowable
• zip - Create a new Flowable from two Flowables by combining their item in pairs in a strict sequence

Other operators

• share - share a Flowable to possibly multiple subscribers

Output functions

• to_rx - create a rx Observable from a Observable

RxPY integration

A Flowable can be created from an RxPY Observable using the rxbp.from_rx function. Likewise, a Flowable can be converted to an RxPY Observable using the rxbp.to_rx function. The example below demonstrates the two conversion:

import reactivex as rx
import rxbp

rx_source = rx.of("Alpha", "Beta", "Gamma", "Delta", "Epsilon")

# convert Observable to Flowable
source = rxbp.from_rx(rx_source)

flowable = (
    source
    .map(lambda s: len(s))
    .filter(lambda i: i >= 5)
)

# convert Flowable to Observable
rxbp.to_rx(flowable).subscribe(lambda v: print(f"Received {v}"))

Reference

Below are some references related to this project:

• continuationmonad is a Python library that implements stack-safe continuations based on schedulers.

<!-- * [donotation](https://github.com/MichaelSchneeberger/continuationmonad/) is a Python library that implements stack-safe continuations based on schedulers. -->

• RxPY is rx extension for Python implementing the Observable pattern (without backpressure).