In the last part of this series I wrote some simple experiments of plugins both with WebAssembly and dynamic loading. After discarding Wasm for this specific PDK, I wanted to try to get a more realistic example with dynamic loading and work towards the final implementation.

Since the Tremor team suggested to begin by implementing connectors, we’ll first have to learn more about them. Matthias ran me through their current state in a meeting, which I’ll try to summarize. We won’t need to know much for this specific article, though.

## 1. Learning more about connectors#

First of all, Tremor is an event processing system for unstructured data. One of its many usages may be to:

2. Filter, transform, and mix them up following the same structure

3. Send all the now structured logs to your database

This currently works with onramps/sources, offramps/sinks and pipelines:

• An onramp specifies how Tremor connects to the outside world (or pipeline) in order to receive from external systems, such as TCP, periodically or PostgreSQL.

• An offramp specifies how Tremor connects to the outside world (or pipeline) in order to publish to external systems, such as stdout, Kafka or ElasticSearch.

• A pipeline is a set of operations (transformation, aggregation, dropping, etc) through which events can be routed.

The thing is that some onramps may not only want to receive from external systems, but also respond to them directly, acting like an offramp, and vice-versa. This is currently implemented with what’s called “linked transports”, and it’s specifically useful for some onramps and offramps like REST and websocket, where the protocol already provides facility for responding to events with a single connection, for example with an ACK.

Basically, connectors are just a way to abstract over both onramps and offramps under the same concept, including linked transports. As the time of writing this article they’re still being implemented by Matthias in the connectors branch of tremor-rs/tremor-runtime, but their interface, defined with the Connector trait, is somewhat stable.

It’s important to keep the plugin interface as simple as possible. The communication details should be left to the runtime, so that the plugin can be simplified to just exporting a number of synchronous functions. With this we can avoid passing some complex types (async, channels, etc) between the runtime and plugin, which can be impossible if you have to maintain ABI stability (abi_stable doesn’t even support async).

Once this lean plugin interface is defined, we can create some kind of wrapper in the runtime (a manager, in Tremor terms) that handles communication and other similar tasks. This exact same thing is done by other crates such as rdkafka , which is based on the C library rdkafka-sys , and implements a higher-level asynchronous interface on top of it.

As always, these articles include a first section with content specific to Tremor that you might want to skip. Unfortunately, with time this series will become more and more specific to Tremor; after all I’m just reporting my progress on their PDK. Still, having a step-by-step walkthrough for a real-life Plugin System will surely be helpful to those attempting to do the same.

### 2.1. My next steps#

In the first meeting we discussed the work I had exposed in my last update. Despite the complications (being forced to use #[repr(C)]), the team liked where the PDK was going.

They suggested me to start with connectors for the real-life example, even though they were incomplete because Matthias was still working on them. The best way to do this would be to copy the bare minimum from Tremor’s repository and try to get the simplest Proof of Concept working.

In previous meetings we had discussed the possibility of having generics in the interface, but that turned out to not be necessary at all. The Connector trait had a workaround to avoid generics with SinkManagerBuilder.

### 2.2. On software engineering#

At the end of the first meeting, Darach gave some very interesting advice for my software engineering career, so I took note of it and reflected for a bit:

• As you get more experience in the field, you talk more and code less. The positions you’re in become more about team management than programming. It’s good to remember that software engineering isn’t just coding. Also that with time, your personality changes, and you have to keep adapting.

• Team building isn’t about getting a group of people to carry the exact same tasks in the same way. Everyone is different; you’ll have to discover the strengths and weaknesses of each member and figure out how to mix them up. The best teams are often very heterogeneous, and it’s pretty clear to me that this is the case with Tremor as well.

• Don’t care about what others say about you (the don’t worry rule). Don’t let “You’ll never end up being X”, “You’re bad at Y” and similars ever affect you.

• Coding is mentally exhausting and burnout is a very common thing. Take good rest, breathe, and have fun. Taking a break from programming is a good idea from time to time.

I’ve personally experienced burnout myself so I know this first hand. You may immerse yourself too much in computers or coding (specially under a pandemic that restricts how much you can go out). Finding a hobby outside of that is incredibly helpful.

### 2.3. How Tremor works#

After starting to write the PDK example for connectors and failing because I didn’t know what I was doing, I decided to step back and try to understand in detail how Tremor works. Once I had that covered, I could try to simplify the PDK as much as possible in order to keep my sanity.

I jumped into the codebase of tremor/tremor-runtime and tried to figure out how it was structured, also with the help of the team later on. First of all: Tremor is loosely based on the actor model. Quoting Wikipedia:

[The actor model treats the] actor as the universal primitive of concurrent computation. In response to a message it receives, an actor can: make local decisions, create more actors, send more messages, and determine how to respond to the next message received. Actors may modify their own private state, but can only affect each other indirectly through messaging (removing the need for lock-based synchronization).

It doesn’t use a language (e.g. Erlang) or framework (e.g. bastion , maybe in the future) that strictly follows the actor model, but it often re-implements the same patterns manually. Tremor is currently implemented with asynchronous programming, which means that instead of threads we’ll be working with tasks, a higher level concept. From the async-std documentation:

An executing asynchronous Rust program consists of a collection of native OS threads, on top of which multiple stackless coroutines are multiplexed. We refer to these as “tasks”. Tasks can be named, and provide some built-in support for synchronization.

We could summarize this with the sentence “Tremor is based on actors running in separate tasks which communicate asynchronously via channels”. The main actor is called the World. It contains the state of the program, such as the available artifacts (repositories) and the running ones (registries), and it’s used to initialize and control the program.

I’ll try to follow what Tremor does in order to get a connector running with the help of a few diagrams. The following diagram showcases what happens when a World is created. This introduces the concept of Managers, which simply are actors in the system that wrap up some functionality.

Managers help decouple the communication and the implementation of the underlying functionality. They are also useful to remove some boilerplate when initializing the components, such as creating the communication channel or spawning the component in a separate task.

Generally, there’s one manager per artefact type, which helps with their initialization process, and then there’s one manager per running instance, handling their communication details.

Once all the managers are initialized, Tremor currently registers all the built-in artifacts in a “hardcoded” way with register_builtin_types. But after the PDK is implemented, this will happen dynamically, i.e. Tremor will automatically look for DLL/SO files in its configured directory and try to register all the plugins it can find. The user may additionally request a specific plugin to be loaded while Tremor is running.

Note that the initialization of the connectors is done in two steps: first they’re registered, which just means that the connector is now available for loading (they’re added to the repository). The connector doesn’t actually start running until a binding is created with it, for example with launch_binding, which will remove it from the repository and add it to the registry, with the currently running artifacts.

connectors::Manager contains all the connectors running in Tremor, which we’ll now try to understand:

Since it’s a multi-step process (it’s actually more complicated than registration + creation), the first part of it already provides the tools to initialize the connector (mainly the builder). When the connector needs to start running because it’s been added to a binding in the pipeline, the builder helps to construct it generically with the previously provided configuration details. Finally, it’s moved into a task of its own, so that it may communicate with other parts of Tremor.

Now that we have a connector running, let’s see how it’s split up into the source and sink parts. In a very similar way, a builder is used to initialize the underlying source, sink, or both, and then a new task is spawned for them.

A manager is also created for each instance of source/sink, which will handle the communication with other actors. This way, the source and sink interfaces can be kept as simple as possible. These managers will receive connection requests from the pipeline and then redirect or read from it.

The main difference between sinks and sources currently is that the former can also reply to messages within the same connection. This is useful to acknowledge the package (“Ack”) or to notify something has failed in the sink (“Fail” for a specific event, “CircuitBreaker” to completely stop data from being sent).

Some connectors are based on streams. They are equivalent for example to TCP streams, which help to group up messages and avoid mixing them up. They are manually started and ended via messages, and the manager saves their state in a field called states (since for instance preprocessors may need to keep a state). If a connector doesn’t need this, such as the metronome, it may simply specify DEFAULT_STREAM_ID as the stream ID always.

Codecs and preprocessors are involved here both at the source and sink levels. In the source part, the data is transformed or split up through a chain of preprocessors and then the codec is applied. For the sinks, the inverse process is followed: the data is first encoded into bytes with the codec, and then a series of post-processors are applied to the raw binary data.

After the full interface of connectors is done, I could implement the two following connector plugins:

• Blackhole is used for benchmarking. It takes measurements of the end to end times of each event traversing the pipeline and at the end prints an HDR (High Dynamic Range) histogram.

• Blaster replays a series of events specified in a file, which is specially useful for performance testing.

Both of these are relatively simple and will be helpful to benchmark the PDK later on. But that isn’t really important right now; I first need to get the PDK working, and then I can care about performance.

## 3. Taking a look at eBPF first#

In the previous articles I mostly considered using either WebAssembly or Dynamic Loading. What I didn’t even know about is eBPF, “a revolutionary technology with origins in the Linux kernel that can run sandboxed programs in an operating system kernel”. However, similarly to WebAssembly, its usage has been expanded to user-space applications. eBPF defines a set of bytecode instructions that may be ran by a virtual machine anywhere, similarly to how Wasm works.

There are multiple active crates for eBPF in Rust. libbpf_rs , redbpf and aya are specific to the Linux Kernel. solana_rbpf is a virtual machine, so it only works for user-space. The maintainers of the latter use it to safely run apps on the blockchain, and their crate seems to be a fork of the now abandoned (?) rbpf . This recent talk at LPC 2021 explains the situation of eBPF in Rust quite well (mainly for Aya, so it’s mostly related to the Linux Kernel).

Unlike WebAssembly, you don’t necessarily need to serialize or write to an intermediate memory. Since you fully control how the virtual machine works, the runtime could implement a custom sandbox that simply checks for the read/written addresses in the plugins to make sure they aren’t out of bounds, while still sharing the same memory space. So in terms of performance, Tremor itself could use it — though there’s still the penalty of interpreting plugins instead of running them natively.

The problem in this case is that, for what I’ve found, Rust support leaves to be desired. Most people seem to use C for eBPF and I think it shows; the number of tutorials/guides/articles about eBPF on Rust is incredibly small. There’s no official target to compile Rust to eBPF, and the only user-space runtime we can use is rbpf and its derivatives. Looking for information about this topic was somewhat frustrating, specially because the search results are mixed up with kernel-only BPF, which is not relevant to us.

It doesn’t really seem like the best choice right now, in my opinion. We would have to write almost everything about the plugin system from scratch, including the sandbox itself (allowing only different sets of syscalls, bounds checking, etc). It would be considerably more cumbersome than using something like abi_stable. Maybe in the future it’d be worth considering it in detail and running some benchmarks, but for now I think dynamic loading is still the clear winner for Tremor. Still, I’m surprised by how flexible eBPF seems to be, and how it’s possible to avoid the memory barrier problem found in Wasm.

Cheers to Dr. Florentin Rochet for letting me know about this technology — though he’s considering switching to WebAssembly for his project. He’s currently using it to research pluggable anonymous protocols like Tor, which would allow patches to their code to happen at runtime [1] [2] [3] [4]. This makes it faster to fix vulnerabilities until it’s properly updated upstream, among other things. Pretty cool :)

## 4. Getting deeper into dynamic linking#

Now that we definitely know how to approach the PDK, we have two choices: using raw dynamic linking with the C ABI and libloading, or trying out the abi_stable crate. I suggest we do both. We’ll most likely end up using the latter because it should be easier and safer, but it’s still a very good idea to know how abi_stable works under the hood.

In the previous article I created a dynamic-simple experiment in examples to the pdk-experiments repository. In this one we’ll try to get an implementation that’s closer to what we need for connectors, so I’ll call the new experiment dynamic-connectors.

## 5. Versioning#

In order to get more advanced things running, we should figure out how to properly embed metadata in the plugin. In order to export any type, we already know that it must be FFI-safe. But there’s something else of great importance: versioning. In order to safely load the plugin, one must ensure that the versions of the common crate match — or at least that they’re compatible — for both the runtime and the plugin. Here’s an example of how this could go wrong if we don’t save information about versioning:

Plugin implementation
pub mod common {
// This is the declaration for the plugin data in version 0.1
#[repr(C)]
pub struct PluginData {
pub name: &'static [u8],
pub new: unsafe extern "C" fn() -> State,
}
}

#[no_mangle]
pub static PLUGIN_DATA: common::PluginData = common::PluginData {
name: b"test",
new
};
Runtime implementation
pub mod common {
// And this is the same type, but in version 0.2
#[repr(C)]
pub struct PluginData {
pub name: &[u8],
pub new: unsafe extern "C" fn() -> State,
// NOTE: this field is new here!
pub connect: unsafe extern "C" fn(&mut State) -> bool
}
}

fn main() -> Result<(), anyhow::Error> {
unsafe {
let library = Library::new(path)?;

let data = library
.get::<*const common::PluginData>(b"PLUGIN_DATA")?
.read(); // !!! UNDEFINED BEHAVIOUR !!! What will data.connect be?
}

Ok(())
}

In the code above, we can see that, even though both versions of PluginData are FFI-safe, their layouts aren’t the same, because the last one has a new field. When trying to read PLUGIN_DATA, undefined behaviour will occur (most likely accessing to an invalid memory address).

Every plugin should at least export the version of common it uses, and the runtime should check it before anything else.

Specifically, the type used to export the version has to be:

• FFI-safe, so &str or CStr are discarded (the latter is a Rust wrapper and not #[repr(C)]).

• Stable. abi_stable::Rstr won’t work either because the versions for abi_stable might mismatch, since we’re reading the symbol before knowing that. Its layout must be always the same.

• Thread-safe (implement Sync). If we wanted to use something like *const c_char, the compiler would throw the following error, because it’s a pointer:

error[E0277]: *const i8 cannot be shared between threads safely
--> src/lib.rs:4:1
|
4 | pub static VERSION: *const c_char = b"0.1.0\0".as_ptr() as _;
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ *const i8 cannot be shared between threads safely
|
= help: the trait Sync is not implemented for *const i8
= note: shared static variables must have a type that implements Sync

Instead, we can use a function that returns the string:

#[no_mangle]
pub extern "C" fn get_version() -> *const c_char {
b"0.1.0\0".as_ptr() as _
}

Finally, there are multiple ways to handle versioning within the runtime, depending on how fine-grained (but also more error-prone) it should be:

• The simplest way possible: both version strings must be strictly the same.

• The plugin system could take advantage of semantic versioning. Only differences in the major version (X.0.0) would be incompatible. The problem in this case is that this is kept track of manually, and it’s possible that a breaking change is introduced by mistake.

• Since there are actually many kinds of plugins (connectors, codecs, etc), rather than checking the version for the entire common crate, there could be a version per type of plugin. If a change in the common crate only modifies structures for codec plugins, the rest of the plugins would still work.

Another complicated topic is plugin distribution and management. In order to make it easier for the user, plugins should be found and loaded automatically. But how exactly should this work? I’ll explain a few ideas.

First of all, the plugins can be found automatically by searching one or more user-configurable directories. For instance, in Tremor’s case we could use the environment variable TREMOR_PATH. Once we have a list of directories where we should look for plugins there are two ways to do it:

• Only checking the immediate files in the directory

• Recursively, which is more convenient but might cause issues if the node is too deep. If the user specified / as a directory, the runtime would most likely crash unless we used something efficient like fd or added a depth limit (which is probably the most sensible choice here).

Once we’re traversing a directory, we have to figure out which files are plugins and which aren’t. The easiest way to do it is with file extensions, but this introduces the problem of cross-compatibility. Dynamic libraries usually have a different extension name for each Operating System: Windows uses .dll, Linux and FreeBSD use .so, and MacOS uses .dylib, as specified by std::env::consts::DLL_EXTENSION. It would make sense that our runtime only tried to load plugins with their respective extensions.

However, these extensions are just conventions; we could just enforce a single extension name, as libloading suggests. It might be easier if we just used .module for everything, for example. In order to make them even more convenient, it’d be nice if they also worked for all of these Operating Systems within a single file. Apparently, this is called a “Fat binary” and it was used in the past, but it’d be extremely complicated to get working now [5], so we’ll just forget about it.

Additionally, the Tremor plugin system requires that plugins can be loaded both at initialization time and at runtime. There is a decision to be made in here about how the latter should work:

• Manually: after adding the new plugin to the configured directories (or specifying its full path), the user would input in some way that it should be loaded (for example with the CLI tool).

• Automatically: the runtime could detect whenever a new plugin is added to the list with a crate like notify . Most Operating Systems have some way to get a notification whenever a file or directory changes. In case a new file was added to any of the configured directories, the runtime could try to load it. This way, it’d work with no user interaction, other than adding the file to one of the directories.

• A combination of both: if the directories configured to look for plugins can’t be changed at runtime it might be interesting to also let the user manually load plugins in specific paths.

## 7. Handling state#

Most plugins will want to keep some kind of state between calls to its interface. For example, the TCP connector will need to keep its socket after its initialization in order to send or receive messages. This means that most of them will follow the following pattern:

let state = plugin.new();
plugin.something(&mut state);

The state is first created with a new function that initializes everything as needed, and then a mutable reference is passed to its functions. The main problem here is, if each plugin is going to have its own type of state, what’s the function signature of Plugin::something, defined in common?

### 7.1. Generics in plugins?#

In a regular Rust project we’d just make Plugin::something generic over a common trait that all states should implement. Unfortunately, generics in plugins are fundamentally impossible. In Rust, monomorphization turns generic code into specific code by filling in the concrete types that are used when compiled [6]. Plugins are loaded at runtime, so they may want to use types the compiler didn’t generate code for.

It’s really easy to prove in Rust with the following example. We’ll try to load an external function with generics:

extern "C" {
fn foo<T>(_: T);
}

This results in the following error:

error[E0044]: foreign items may not have type parameters
--> src/lib.rs:2:5
|
2 |     fn foo<T>(_: T);
|     ^^^^^^^^^^^^^^^^ can't have type parameters
|
= help: replace the type parameters with concrete types like u32

error: aborting due to previous error

For more information about this error, try rustc --explain E0044.

Interestingly enough, the compiler lets you export generic functions declared in Rust:

extern fn foo<T>(_: T) {}

This confused me in the beginning; it made me think generic functions through FFI were somehow be possible. But as described in the original issue that allowed them, they’re only supported to pass callbacks to C functions.

Note that generics in plugins do work for lifetimes. This will compile:

extern "C" {
fn foo<'a>(_: &'a str) -> &'a str;
}

Even though lifetimes and generics share the same syntax, in the case of lifetimes they are only annotations for the Rust compiler; monomorphization is not applied.

If you want to know more about this topic I’d suggest watching this video by Jon Gjengset.

### 7.2. dyn in plugins?#

The alternative to generics is often using trait object types with dyn. Again, will that work for plugins? Let’s try:

pub trait PluginState {}
pub extern fn foo<T>(_: &dyn PluginState) {}

Compiling…​

warning: extern fn uses type dyn PluginState, which is not FFI-safe
--> src/lib.rs:2:25
|
2 | pub extern fn foo<T>(_: &dyn PluginState) {}
|                         ^^^^^^^^^^^^^^^^ not FFI-safe
|
= note: #[warn(improper_ctypes_definitions)] on by default
= note: trait objects have no C equivalent

Nope. dyn is strictly part of the Rust ABI, so it’s not stable for our plugin system.

### 7.3. The C way#

There are two popular ways to approach this in C:

1. Globals, but they are hard to deal with in concurrent programs

2. void*, which is a pointer with no associated type [7]

For safety’s sake, let’s see how the second one works. This pattern is used for example in PulseAudio [8], in which callbacks pass a void* parameter for user data. Here’s a simpler program:

#include <stdio.h>
#include <stdlib.h>

// The state of the plugin
typedef struct {
int counter;
} plugin_state_t;

// Exported by the plugin, initializes the state
void* new() {
plugin_state_t* plugin_state = malloc(sizeof(plugin_state_t));
plugin_state->counter = 0;
return (void*) plugin_state;
}

// Exported by the plugin, which takes a pointer to its state
void something(void* state) {
// We know the runtime used new to initialize the state, so we can cast it
// back to its original type.
plugin_state_t* plugin_state = (plugin_state_t*) state;

printf("Current state: { counter = %d }\n", plugin_state->counter);
plugin_state->counter++;
printf("Final state: { counter = %d }\n", plugin_state->counter);
}

int main() {
// We initialize the plugin, which returns its state
void* state = new();
// When calling anything from the plugin we pass its state
something(state);
// Don't forget!
free(state);
}

This does work perfectly, and we could port it to Rust as a straightforward solution. However, it has the following inconvenients:

• It’s very unsafe. We’d need to add some kind of wrapper/macro for the plugin developers to avoid invoking undefined behaviour.

• We know nothing about the state. A void* can’t enforce Debug being implemented, nor any base other method or trait that might be of interest to us.

Based on how this works, we can try to extend it by implementing intheritance-based polymorphism manually. This blog post by Michael F. Bryan’s covers the topic extremely well.

Here’s how our previous example would look like, which could be translated to Rust with no problems whatsoever:

#include <stdio.h>
#include <stdlib.h>

// The base plugin type
typedef struct base_state_t {
void (*print)(struct base_state_t *);
} base_state_t;

// The state of the plugin, child of the above type
typedef struct {
base_state_t base;
int counter;
} plugin_state_t;

// The implementation of print for the plugin_state_t child
void print(base_state_t* state) {
plugin_state_t* plugin_state = (plugin_state_t*) state;
printf("Current state: { counter = %d }\n", plugin_state->counter);
}

// Exported by the plugin, initializes the state
base_state_t* new() {
base_state_t base = {print};

plugin_state_t* plugin_state = malloc(sizeof(plugin_state_t));
plugin_state->base = base;
plugin_state->counter = 0;
return (base_state_t*) plugin_state;
}

// Exported by the plugin, which takes a pointer to its state
void something(void* state) {
// We know the runtime used new to initialize the state, so we can cast it
// back to its original type.
plugin_state_t* plugin_state = (plugin_state_t*) state;
plugin_state->counter++;
}

int main() {
// We initialize the plugin, which returns its state
base_state_t* state = new();
// When calling anything from the plugin we pass its state
state->print(state);
something((void*) state);
state->print(state);
// Don't forget!
free(state);
}

The main difference in the code is the new base class plugin_base_t. It defines a single function print that should be implemented by its children, and it could also include other fields that would be inherited. Casting between base_state_t and plugin_base_t is explicitly allowed by the C standard as long as the base class is the first member in the struct, so this is sound.

This covers all of our necessities. The only remaining problem is that it’s still quite unsafe to use. Thankfully, we can avoid most user errors by using the crate thin_trait_object , which provides a very flexible procedural macro to automatically write all the necessary boilerplate in Rust.

## 8. Error Handling#

I’ve created a few more plugins to see how this approach reacts to some common errors. Since in the end we aren’t using a sandbox, I wonder what kind of errors we can’t recover from.

### 8.1. Missing fields#

The plugin-missing directory contains an empty plugin. It doesn’t export any fields at all, like the name or the version. This one is already handled by libloading, actually. When using library.get("name"), if "name" is not exported by the shared object, the following error will show up:

$make debug-missing Error when setting up the plugin: plugin-missing/target/debug/libplugin_missing.so: undefined symbol: get_name ### 8.2. Version mismatch# After implementing the versioning system, we can see how these kinds of errors can be caught safely: $ make debug-versionmismatch
Initializing plugin versionmismatch
Version mismatch. Aborting.
Error when setting up the plugin: version mismatch: 0.0.0 incompatible with 0.1.0

### 8.3. Wrong type#

Libloading assumes the type that’s being loaded is correct. If for example the plugin exported the get_name function, but it returned an integer instead of a string, we’d be in undefined-behaviour-land:

Users of this API must specify the correct type of the function or variable loaded. Using a Symbol with a wrong type is undefined.

Ignoring this will cause an unavoidable segfault:

$make debug-wrongtype Segmentation fault (core dumped) ### 8.4. Wrong address# Unfortunately, there’s not much we can do about out of bounds pointers. If the plugin exports e.g. the name with a null pointer, we’ll just get a segmentation fault: $ make debug-wrongaddress
Segmentation fault (core dumped)

In order to avoid this, the runtime could manually check that the pointer isn’t zero, the usual value for null. But the same would still happen if the pointer’s value was 1 instead of 0. And even if it was within bounds, it could just point to garbage anyway.

### 8.5. Panicking#

Panicking is not supported in the C ABI; it’s considered undefined behaviour [9]. If a plugin panics, the entire program will most likely abort. Plugin developers should wrap every single exported function in catch_unwind in order to not crash the entire runtime when something goes wrong:

\$ make debug-panic
Segmentation fault (core dumped)

## 9. Full implementation#

The example at dynamic-connectors approaches the topics covered in this section in the simplest of ways, while still implementing a working plugin system. More specifically:

• Versioning requires an exact match between the version of common in the plugin and the runtime.

• The plugins are manually loaded given a directory.

• The runtime looks for plugins in the immediate files of the directory, i.e. non-recursively.

• The state is passed as a void pointer, rather than trying to use inheritance.

Most of these are just decisions to be made by the designer of the system. I chose to go for the easiest options so that we can focus on abi_stable sooner.

I did implement a declarative macro to make plugin-writing easier and less error-prone, just to see how it’d work. It takes care of most of the boilerplate, which basically consists on creating functions for the name, kind, and version returning *const c_char, and exporting the plugin data struct. For the curious, it’s defined in the common directory.

Sample usage of the macro
define_connector_plugin! {
name: "metronome",
data: ConnectorPlugin {
new,
something,
is_sink: false,
is_source: true
}
}

The plugin system supports multiple types of plugins (connectors, codecs, etc), so there’s actually a specific macro and data structure for each of them.

Apart from the examples listed in the Error Handling section, I’ve created a proper plugin that is supposed to work, with the name plugin-metronome. It was supposed to implement the metronome connector, but I’ve decided to just leave that for the next post. I’d rather spend my time writing the real-life example with the abi_stable version, because it’s what we’ll end up using.

## 10. Conclusion#

This article has covered a lot of questions that one may encounter when trying to use dynamic loading for a plugin system. It’s definitely a complicated task with lots of decisions to make, and plenty of pitfalls. This is why I’d love to try abi_stable in detail, which would let us do the same things but without a line of unsafe.

In my opinion, although abi_stable is a very large crate and somewhat hard to learn, most of the problems this post exposes are greatly simplified thanks to it. In the next article I’ll see the differences between both approaches.