Skip to main content

Ordered Demultiplexer in Python

Single pass approach to Demultiplexing/Demuxing

Break an iterator into multiple iterators based on a set of filters.

Typical demuxers will place elements into different iterators, such as splitting [0,1,2,3] into ([0,2], [1,3]) based on odd or even elements. Ordered Demuxers focus on breaking iterators into contiguous blocks that are meant to be immediately worked upon, without having to iterate over the list more than once.

This makes them appropriate to use with iterators where the contents cannot be fully held in memory, such as retrieving data online.

Example

With any iterable input such as

x = iter([ (_, 0), (_, 1), (MessageEnd, 2), (_, 3), (_, 4), (MessageEnd, 5) ])

This can be broken into;

Iterator [
  Iterator [(_, 0), (_, 1), (MessageEnd, 2)], 
  Iterator [(_, 3), (_, 4), (MessageEnd, 5)]
]

Without passing over each element of data multiple times. This allows for methods like;

for data_stream in demuxed_stream:
  for element in data_stream:
    function(element)

Or more interestingly;

def foo(x: Iterator[T]):
  ...

for data_stream in demuxed_stream:
  foo(data_stream)

foo will consume part of the original iterator, up until the next break point, but still behave identically to passing it an iterator of just the data required.

Due to the way the filters are available within the Demuxer, it's also possible to send these partial iterators to functions according to the relevant filter, i.e.

conditions = [
  FilterCondition(lambda x: x[0] == 'MessageEnd', 'SuccessfulMessageStream'),
  FilterCondition(lambda x: x[0] == 'MessageFailed', 'FailedMessageStream')
]

for data_stream in demuxed_stream:
  if demuxed_stream.condition_met is not None:
    match demuxed_stream.condition_met.name:
      case 'SuccessfulMessageStream':
        foo(data_stream)
      case 'FailedMessageStream':
        foo2(data_stream)
  else:
    foo3(data_stream)

Although it requires the consumption of each iterator entirely to make this possible.

Installation

python -m pip install ordered-demuxer

Usage

>>> from ordered_demuxer import FilterCondition, OrderedDemuxer
>>> x = [1, 2, 3, 4]
>>> y = FilterCondition(lambda x: x == 2)
>>> splt = OrderedDemuxer(data_source=iter(x), filter=y, split_after=True)
>>> x_iter = splt.__next__()
>>> print(list(x_iter))
  [1, 2]

Release files for ordered-demuxer 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ordered-demuxer 0.1.0
File Size Uploaded
ordered_demuxer-0.1.0.tar.gz 3.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for ordered-demuxer 0.1.0
File Interpreter ABI Platform
ordered_demuxer-0.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 7.6 kB

Release files / ordered_demuxer-0.1.0.tar.gz

Download URL ordered_demuxer-0.1.0.tar.gz
Size 3.6 kB
Tags Source
SHA-256 checksum
How to use checksums
96c220bcaf6c8f93f0e4e6e7cbcdeaa742043f28f24cdc0b0bc716f7f47ab440
BLAKE2b-256 checksum
How to use checksums
ac415fc2f384a904b4c4b65ca44078baa880d164daff9d6888fcbe1892d4b156
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

Release files / ordered_demuxer-0.1.0-py3-none-any.whl

Download URL ordered_demuxer-0.1.0-py3-none-any.whl
Size 3.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
41c60299e0284d6056482336c70ea03bdae91c9b32a61966d9f41aab1d90fc3a
BLAKE2b-256 checksum
How to use checksums
8f7f4a2ddfab5c457e67b6cc6f2e819121a896d4663499463d76560121c83731
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10

Release history Release notifications | RSS feed

This release

0.1.0 This release

2 release files

0.0.3

2 release files

0.0.2

2 release files

0.0.1

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page