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## Symmetric Producer/Consumer

A low-level example of Passing control sideways between fibers.

```perl
my ($p, $c);

$p = Acme::Parataxis->new(code => sub {
    for my $item (qw[Apple Banana Cherry]) {
        say "Producer: Sending $item";
        $c->transfer($item);
    }
    $c->transfer('DONE');
});

$c = Acme::Parataxis->new(code => sub {
    my $item = Acme::Parataxis->yield( ); # Initial wait
    while (1) {
        last if $item eq 'DONE';
        say "Consumer: Eating $item";
        $item = $p->transfer( );
    }
});

$c->call( ); # Prime consumer
$p->call( ); # Start producer
```

# BEST PRACTICES & GOTCHAS

- **Avoid blocking syscalls:** Never call blocking `sleep( )` or `sysread( )` on the main interpretation thread.
Always use the `await_*` equivalents to offload work to the pool.
- **Thread Safety:** While Perl code remains single-threaded, background tasks run on separate OS threads. Shared
C-level data (if accessed via FFI) must be mutex-protected.
- **Stack Limits:** Each fiber is allocated a 512KB stack by default. This is more than sufficient for most
Perl code and allows for high concurrency with a small memory footprint. Extremely deep recursion or massive regex
backtracking might still hit limits.
- **Efficiency:** The native thread pool is initialized dynamically upon the first asynchronous request. It
starts with a small "seed" pool and grows on demand up to the configured limit. Worker threads use condition
variables to sleep efficiently when idle, ensuring near-zero CPU usage when no background tasks are pending.
- **Reference Cycles:** Be careful when passing fiber objects into their own closures, as this can create
memory leaks.

# GORY TECHNICAL DETAILS

## Architectural Inspiration

The concurrency model in Parataxis is heavily inspired by the **Wren** programming language, specifically its treatment
of fibers as the primary unit of execution and its deterministic cooperative scheduling.

## Stack Virtualization

On Unix-like systems, we use `ucontext.h` to manage stack and register state. On Windows, we leverage the native
`Fiber API`. In both cases, we perform heart surgery on the Perl interpreter by manually teleporting its internal
global pointers (the `PL_*` variables) between contexts.

## Shared CVs and Pad Virtualization

A significant challenge in Perl green threads is the shared nature of PadLists and the global `CvDEPTH` counter. In
debug builds of Perl, calling a shared subroutine from multiple fibers can trigger internal assertions (like
`AvFILLp(av) == -1`). Parataxis includes a specialized workaround that surgically cleans the next landing pad before
every context switch to satisfy these assertions without clobbering active lexical state.

## `eval` vs. `try/catch`

While `feature 'try'` is available in modern Perl, manually teleporting interpreter state can occasionally confuse the
compiler's expectations for stack unwinding. Standard `eval { ... }` remains the most predictable way to handle
exceptions within fibers.

## Signal Handling

Signals are delivered to the main process thread. Perl handles these at 'safe points,' which in this module typically
occur during a context switch (yield, transfer, or call). If you send a signal while a fiber is suspended, it will
generally be processed when the fiber is resumed and hits the next internal Perl opcode.

## The 'Final Transfer' Requirement

In a symmetric coroutine model (using `transfer( )`), fibers don't have a natural 'parent' to return to. I've added
fallback logic to return to the `last_sender` or the main thread on exit but it's good practice to explicitly
`transfer( )` back to a partner fiber or the `root( )` context to ensure your application logic remains predictable.
Leaving a fiber to just 'fall off the end' is like walking out of a room without closing the door; eventually, the
draft will bother someone.

## `is_done( )` vs. Destruction

A fiber being `is_done( )` simply means its Perl code has finished executing. The underlying C-level memory (stacks,
context, etc.) is not immediately freed until the `Acme::Parataxis` object is destroyed or the runtime performs its
final `cleanup( )`. This is why you might see memory usage stay flat even after a fiber finishes, until the garbage
collector finally catches up with the object.

# AUTHOR

Sanko Robinson <sanko@cpan.org>

# LICENSE

Copyright (C) Sanko Robinson.

This library is free software; you can redistribute it and/or modify it under the terms found in the Artistic License
2.