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## Fibers vs. Threads

In Parataxis, your **Perl code** always runs on a single OS thread. However, when you call an `await_*` function, the
current fiber is suspended, and the actual blocking work is performed on a **different** OS thread in a native pool.
Once the task completes, your fiber is automatically queued for resumption on the main thread.

# SCHEDULER FUNCTIONS

The following functions are the primary interface for the integrated cooperative scheduler.

## `run( $code )`

Starts the event loop and executes `$code` as the initial fiber. The loop continues to run as long as there are active
fibers or pending background tasks.

```perl
Acme::Parataxis::run(sub {
    say "The scheduler is running!";
});
```

## `spawn( $code )`

Creates a new fiber and adds it to the scheduler's queue. Returns a [Future](#acme-parataxis-future-object-methods)
that will eventually contain the fiber's return value.

```perl
my $future = Acme::Parataxis->spawn(sub {
    return "Hello from fiber #" . Acme::Parataxis->current_fid;
});
```

## `yield( @args )`

Pauses the current fiber and returns control to the scheduler. If `@args` are provided, they are passed to the context
that next resumes this fiber. Arguments can be of any Perl data type.

## `stop( )`

Tells the scheduler to exit the loop after the current iteration. Note that this does not immediately terminate other
fibers; it simply prevents the scheduler from starting new ones.

# THREAD POOL CONFIGURATION

`Acme::Parataxis` uses a native thread pool to handle blocking tasks. While it manages itself automatically, you can
tune its behavior using these functions.

## `set_max_threads( $count )`

Sets the maximum number of worker threads the pool is allowed to spawn. By default, this is set to the number of
logical CPU cores detected on your system (up to a hard limit of 64).

```
# Limit the pool to 4 threads
set_max_threads(4);
```

## `max_threads( )`

Returns the currently configured maximum thread pool size.

# BLOCKING & I/O FUNCTIONS

These functions **suspend** the current fiber and offload the actual blocking work to the native thread pool.

## `await_sleep( $ms )`

Suspends the fiber for `$ms` milliseconds. While the background thread sleeps, other fibers can continue to execute.

## `await_read( $fh, $timeout = 5000 )`

Suspends the fiber until the filehandle `$fh` is ready for reading, or the `$timeout` (in milliseconds) is reached.

```perl
my $status = Acme::Parataxis->await_read($socket);
if ($status > 0) {
    my $data = <$socket>;
}
```

## `await_write( $fh, $timeout = 5000 )`

Suspends the fiber until the filehandle `$fh` is ready for writing.

## `await_core_id( )`

Offloads a request to the thread pool and returns the ID of the CPU core that handled the job.

# MANUAL FIBER MANAGEMENT

Advanced users can manage context switching themselves without using the integrated scheduler.

## `new( code => $sub )`

Instantiates a new fiber. The `code` argument must be a subroutine reference.

```perl
my $fiber = Acme::Parataxis->new(code => sub {
    my $arg = Acme::Parataxis->yield("Initial data");
    return "Done with $arg";
});
```

## `call( @args )`

Explicitly switches control to the fiber and passes `@args`. Arguments can be scalars, hash/array references, or
objects. This establishes a parent/child relationship: when the fiber yields or completes, control returns to the
caller.

## `transfer( @args )`

A "symmetric" switch. Suspends the current context and moves directly to the target fiber. No parent/child relationship
is established. Like `call`, it supports passing arbitrary Perl data via `@args`.

# PREEMPTION

## `maybe_yield( )`

Increments an internal operation counter for the current fiber. If the counter reaches the threshold set by
`set_preempt_threshold`, the fiber automatically yields.

README.md  view on Meta::CPAN

This example demonstrates how to perform multiple HTTP requests concurrently on a single interpretation thread.

```perl
use Acme::Parataxis;
# ... (See My::HTTP implementation in INTEGRATING SYNCHRONOUS MODULES) ...

Acme::Parataxis::run(sub {
    my $http = My::HTTP->new(verify_SSL => 0);
    my @urls = qw[http://example.com http://perl.org];

    # Spawn tasks for each URL
    my @futures = map {
        my $url = $_;
        Acme::Parataxis->spawn(sub { $http->get($url)->{status} })
    } @urls;

    # Collect results as they become ready
    say "Status for $urls[$_]: " . $futures[$_]->await( ) for 0..$#urls;
});
```

## 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