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.. _additional_reading:
Additional Reading
==================
Open Material
-------------
The RxPY source repository contains `example notebooks
<https://github.com/ReactiveX/RxPY/tree/master/notebooks>`_.
The official ReactiveX website contains additional tutorials and documentation:
* `Introduction <http://reactivex.io/intro.html>`_
* `Tutorials <http://reactivex.io/tutorials.html>`_
* `Operators <http://reactivex.io/documentation/operators.html>`_
Several commercial contents have their associated example code available freely:
* `Packt Reactive Programming in Python <https://github.com/PacktPublishing/Reactive-Programming-in-Python>`_
RxPY 3.0.0 has removed support for backpressure here are the known community projects supporting backpressure:
* `rxbackpressure rxpy extension <https://github.com/MichaelSchneeberger/rxbackpressure>`_
* `rxpy_backpressure observer decorators <https://github.com/daliclass/rxpy-backpressure>`_
Commercial Material
--------------------
**O\'Reilly Video**
O'Reilly has published the video *Reactive Python for Data Science* which is
available on both the `O\'Reilly Store
<https://shop.oreilly.com/product/0636920064237.do>`_ as well as `O\'Reilly
Safari <https://www.safaribooksonline.com/library/view/reactive-python-for/9781491979006>`_.
This video teaches RxPY from scratch with applications towards data science, but
should be helpful for anyone seeking to learn RxPY and reactive programming.
**Packt Video**
Packt has published the video *Reactive Programming in Python*, available on
`Packt store
<https://www.packtpub.com/application-development/reactive-programming-python-video>`_.
This video teaches how to write reactive GUI and network applications.
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