Readme description bump after talks with multiple would-be users
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README.rst
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README.rst
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@ -10,7 +10,7 @@ An async-native "`actor model`_" built on trio_ and multiprocessing_.
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.. _actor model: https://en.wikipedia.org/wiki/Actor_model
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.. _trio: https://github.com/python-trio/trio
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.. _multiprocessing: https://docs.python.org/3/library/multiprocessing.html
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.. _multiprocessing: https://en.wikipedia.org/wiki/Multiprocessing
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.. _trionic: https://trio.readthedocs.io/en/latest/design.html#high-level-design-principles
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.. _async sandwich: https://trio.readthedocs.io/en/latest/tutorial.html#async-sandwich
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.. _always propagate: https://trio.readthedocs.io/en/latest/design.html#exceptions-always-propagate
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@ -21,17 +21,31 @@ An async-native "`actor model`_" built on trio_ and multiprocessing_.
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.. _chaos engineering: http://principlesofchaos.org/
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``tractor`` is an attempt to bring trionic_ `structured concurrency`_ to distributed multi-core Python.
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``tractor`` is an attempt to bring trionic_ `structured concurrency`_ to
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distributed multi-core Python.
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``tractor`` lets you spawn ``trio`` *"actors"*: processes which each run a ``trio`` scheduler and task
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tree (also known as an `async sandwich`_). *Actors* communicate by exchanging asynchronous messages_ over
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channels_ and avoid sharing any state. This model allows for highly distributed software architecture
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which works just as well on multiple cores as it does over many hosts.
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``tractor`` lets you spawn ``trio`` *"actors"*: processes which each run
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a ``trio`` scheduled task tree (also known as an `async sandwich`_).
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*Actors* communicate by exchanging asynchronous messages_ and avoid
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sharing any state. This model allows for highly distributed software
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architecture which works just as well on multiple cores as it does over
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many hosts.
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``tractor`` is an actor-model-*like* system in the sense that it adheres to the `3 axioms`_ but does
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not (yet) fufill all "unrequirements_" in practice. The API and design takes inspiration from pulsar_ and
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execnet_ but attempts to be more focussed on sophistication of the lower level distributed architecture as
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well as have first class support for streaming using `async generators`_.
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``tractor`` is an actor-model-*like* system in the sense that it adheres
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to the `3 axioms`_ but does not (yet) fulfil all "unrequirements_" in
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practise. It is an experiment in applying `structured concurrency`_
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constraints on a parallel processing system where multiple Python
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processes exist over many hosts but no process can outlive its parent.
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In `erlang` parlance, it is an architecture where every process has
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a mandatory supervisor enforced by the type system. The API design is
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almost exclusively inspired by trio_'s concepts and primitives (though
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we often lag a little). As a distributed computing system `tractor`
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attempts to place sophistication at the correct layer such that
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concurrency primitives are powerful yet simple, making it easy to build
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complex systems (you can build a "worker pool" architecture but it's
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definitely not required). There is first class support for inter-actor
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streaming using `async generators`_ and ongoing work toward a functional
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reactive style for IPC.
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The first step to grok ``tractor`` is to get the basics of ``trio`` down.
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A great place to start is the `trio docs`_ and this `blog post`_.
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@ -56,7 +70,7 @@ Its tenets non-comprehensively include:
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- strict adherence to the `concept-in-progress`_ of *structured concurrency*
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- no spawning of processes *willy-nilly*; causality_ is paramount!
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- (remote) errors `always propagate`_ back to the parent / caller
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- (remote) errors `always propagate`_ back to the parent supervisor
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- verbatim support for ``trio``'s cancellation_ system
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- `shared nothing architecture`_
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- no use of *proxy* objects or shared references between processes
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