mediocre-blog/_drafts/program-structure-and-composability.md

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Program Structure and Composability Discussing the nature of program structure, the problems presented by complex structures, and a pattern which helps in solving those problems.

TODO:

  • Double check if I'm using "I" or "We" everywhere (probably should use "I")

Part 0: Introduction

This post is focused on a concept I call "program structure", which I will try to shed some light on before discussing complex program structures, then discussing why complex structures can be problematic to deal with, and finally discussing a pattern for dealing with those problems.

My background is as a backend engineer working on large projects that have had many moving parts; most had multiple services interacting with each other, using many different databases in various contexts, and facing large amounts of load from millions of users. Most of this post will be framed from my perspective, and will present problems in the way I have experienced them. I believe, however, that the concepts and problems I discuss here are applicable to many other domains, and I hope those with a foot in both backend systems and a second domain can help to translate the ideas between the two.

Also note that I will be using Go as my example language, but none of the concepts discussed here are specific to Go. To that end, I've decided to favor readable code over "correct" code, and so have elided things that most gophers hold near-and-dear, such as error checking and comments on all public types, in order to make the code as accessible as possible to non-gophers as well. As with before, I trust someone with a foot in Go and another language can translate help me translate between the two.

Part 1: Program Structure

In this section I will discuss the difference between directory and program structure, show how global state is antithetical to compartmentalization (and therefore good program structure), and finally discuss a more effective way to think about program structure.

Directory Structure

For a long time I thought about program structure in terms of the hierarchy present in the filesystem. In my mind, a program's structure looked like this:

// The directory structure of a project called gobdns.
src/
    config/
    dns/
    http/
    ips/
    persist/
    repl/
    snapshot/
    main.go

What I grew to learn was that this conflation of "program structure" with "directory structure" is ultimately unhelpful. While I won't deny that every program has a directory structure (and if not, it ought to), this does not mean that the way the program looks in a filesystem in any way corresponds to how it looks in our mind's eye.

The most notable way to show this is to consider a library package. Here is the structure of a simple web-app which uses redis (my favorite database) as a backend:

src/
    redis/
    http/
    main.go

If I were to ask you, based on that directory strucure, what the program does, in the most abstract terms, you might say something like: "The program establishes an http server which listens for requests, as well as a connection to the redis server. The program then interacts with redis in different ways, based on the http requests which are received on the server."

And that would be a good guess. Here's a diagram which depicts the program structure, wherein the root node, main.go, takes in requests from http and processes them using redis.

TODO diagram

This is certainly a viable guess for how a program with that directory structure operates, but consider another: "A component of the program called server establishes an http server which listens for requests, as well as a connection to a redis server. server then interacts with that redis connection in different ways, based on the http requests which are received on the http server. Additionally, server tracks statistics about these interactions and makes them available to other components. The root component of the program establishes a connection to a second redis server, and stores those statistics in that redis server."

TODO diagram

The directory structure could apply to either description; redis is just a library which allows for interacting with a redis server, but it doesn't specify which server, or how many. And those are extremely important factors which are definitely reflected in our concept of the program's structure, and yet not in the directory structure. What the directory structure reflects are the different kinds of components available to use, but it does not reflect how a program will use those components.

Global State vs. Compartmentalization

The directory-centric approach to structure often leads to the use of global singletons to manage access to external resources like RPC servers and databases. In the above example the redis library might contain code which looks something like:

// A mapping of connection names to redis connections.
var globalConns = map[string]*RedisConn{}

func Get(name string) *RedisConn {
    if globalConns[name] == nil {
        globalConns[name] = makeRedisConnection(name)
    }
    return globalConns[name]
}

Even though this pattern would work, it breaks with our conception of the program structure in the more complex case shown above. Rather than having the server component own the redis server it uses, the root component would be the owner of it, and server would be borrowing it. Compartmentalization has been broken, and can only be held together through sheer human discipline.

This is the problem with all global state. It's shareable amongst all components of a program, and so is owned by none of them. One must look at an entire codebase to understand how a globally held component is used, which might not even be possible for a large codebase. And so the maintainers of these shared components rely entirely on the discipline of their fellow coders when making changes, usually discovering where that discipline broke down once the changes have been pushed live.

Global state also makes it easier for disparate services/components to share datastores for completely unrelated tasks. In the above example, rather than creating a new redis instance for the root component's statistics storage, the coder might have instead said "well, there's already a redis instance available, I'll just use that." And so compartmentalization would have been broken further. Perhaps the two instances could be coalesced into the same one, for the sake of resource efficiency, but that decision would be better made at runtime via the configuration of the program, rather than being hardcoded into the code.

From the perspective of team management, global state-based patterns do nothing except slow teams down. The person/team responsible for maintaining the central library which holds all the shared resources (redis, in the above example) becomes the bottleneck for creating new instances for new components, which will further lead to re-using existing instances rather than create new ones, further breaking compartmentalization. The person/team responsible for the central library often finds themselves as the maintainers of the shared resource as well, rather than the team actually using it.

Component Structure

So what does proper program structure look like? In my mind the structure of a program is a hierarchy of components, or, in other words, a tree. The leaf nodes of the tree are almost always IO related components, e.g. database connections, RPC server frameworks or clients, message queue consumers, etc... The non-leaf nodes will generally be components which bring together the functionalities of their children in some useful way, though they may also have some IO functionality of their own.

Let's look at an even more complex structure, still only using the redis and http component types:

TODO diagram:

    root
        rest-api
            redis
            http
        redis // for stats keeping
        debug
            http

This component structure contains the addition of the debug component. Clearly the http and redis components are reusable in different contexts, but for this example the debug endpoint is as well. It creates a separate http server which can be queried to perform runtime debugging of the program, and can be tacked onto virtually any program. The rest-api component is specific to this program and therefore not reusable. Let's dive into it a bit to see how it might be implemented:

// RestAPI is very much not thread-safe, hopefully it doesn't have to handle
// more than one request at once.
type RestAPI struct {
    redisConn *redis.RedisConn
    httpSrv   *http.Server

    // Statistics exported for other components to see
    RequestCount int
    FooRequestCount int
    BarRequestCount int
}

func NewRestAPI() *RestAPI {
    r := new(RestAPI)
    r.redisConn := redis.NewConn("127.0.0.1:6379")

    // mux will route requests to different handlers based on their URL path.
    mux := http.NewServeMux()
    mux.Handle("/foo", http.HandlerFunc(r.fooHandler))
    mux.Handle("/bar", http.HandlerFunc(r.barHandler))
    r.httpSrv := http.NewServer(mux)

    // Listen for requests and serve them in the background.
    go r.httpSrv.Listen(":8000")

    return r
}

func (r *RestAPI) fooHandler(rw http.ResponseWriter, r *http.Request) {
    r.redisConn.Command("INCR", "fooKey")
    r.RequestCount++
    r.FooRequestCount++
}

func (r *RestAPI) barHandler(rw http.ResponseWriter, r *http.Request) {
    r.redisConn.Command("INCR", "barKey")
    r.RequestCount++
    r.BarRequestCount++
}

As can be seen, rest-api coalesces http and redis into a simple REST api, using pre-made library components. main.go, the root component, does much the same:

func main() {
    // Create debug server and start listening in the background
    debugSrv := debug.NewServer()

    // Set up the RestAPI, this will automatically start listening
    restAPI := NewRestAPI()

    // Create another redis connection and use it to store statistics
    statsRedisConn := redis.NewConn("127.0.0.1:6380")
    for {
        time.Sleep(1 * time.Second)
        statsRedisConn.Command("SET", "numReqs", restAPI.RequestCount)
        statsRedisConn.Command("SET", "numFooReqs", restAPI.FooRequestCount)
        statsRedisConn.Command("SET", "numBarReqs", restAPI.BarRequestCount)
    }
}

One thing which is clearly missing in this program is proper configuration, whether from command-line, environment variables, etc.... As it stands, all configuration parameters, such as the redis addresses and http listen addresses, are hardcoded. Proper configuration actually ends up being somewhat difficult, as the ideal case would be for each component to set up the configuration variables of itself, without its parent needing to be aware. For example, redis could set up addr and pool-size parameters. The problem is that there are two redis components in the program, and their parameters would therefore conflict with each other. An elegant solution to this problem is discussed in the next section.

Part 2: Context, Configuration, and Runtime

The key to the configuration problem is to recognize that, even if there are two of the same component in a program, they can't occupy the same place in the program's structure. In the above example there are two http components, one under rest-api and the other under debug. Since the structure is represented as a tree of components, the "path" of any node in the tree uniquely represents it in the structure. For example, the two http components in the previous example have these paths:

root -> rest-api -> http
root -> debug -> http

If each component were to know its place in the component tree, then it would easily be able to ensure that its configuration and initialization didn't conflict with other components of the same type. If the http component sets up a command-line parameter to know what address to listen on, the two http components in that program would set up:

--rest-api-listen-addr
--debug-listen-addr

So how can we enable each component to know its path in the component structure? To answer this we'll have to take a detour through go's Context type.

Context and Configuration

As I mentioned in the Introduction, my example language in this post is Go, but there's nothing about the concepts I'm presenting which are specific to Go. To put it simply, Go's builtin context package implements a type called context.Context which is, for all intents and purposes, an immutable key/value store. This means that when you set a key to a value on a Context (using the context.WithValue function) a new Context is returned. The new Context contains all of the original's key/values, plus the one just set. The original remains untouched.

(Go's Context also has some behavior built into it surrounding deadlines and process cancellation, but those aren't relevant for this discussion.)

Context makes sense to use for carrying information about the program's structure to it's different components; it is informing each of what context it exists in within the larger structure. To use Context effectively, however, it is necessary to implement some helper functions. Here are their function signatures:

// Package mctx

// NewChild creates and returns a new Context based off of the parent one. The
// child will have a path which is the parent's path appended with the given
// name.
func NewChild(parent context.Context, name string) context.Context

// Path returns the sequence of names which were used to produce this Context
// via calls to the NewChild function.
func Path(ctx context.Context) []string

NewChild is used to create a new Context, corresponding to a new child node in the component structure, and Path is used retrieve the path of any Context within that structure. For the sake of keeping the examples simple let's pretend these functions have been implemented in a package called mctx. Here's an example of how mctx might be used in the redis component's code:

// Package redis

func NewConn(ctx context.Context, defaultAddr string) *RedisConn {
    ctx = mctx.NewChild(ctx, "redis")
    ctxPath := mctx.Path(ctx)
    paramPrefix := strings.Join(ctxPath, "-")

    addrParam := flag.String(paramPrefix+"-addr", defaultAddr, "Address of redis instance to connect to")
    // finish setup

    return redisConn
}

In our above example, the two redis components' parameters would be:

// This first parameter is for stats redis, whose parent is the root and
// therefore doesn't have a prefix. Perhaps stats should be broken into its own
// component in order to fix this.
--redis-addr
--rest-api-redis-addr

The prefix joining stuff will probably get annoying after a while though, so let's invent a new package, mcfg, which acts like flag but is aware of mctx. Then redis.NewConn is reduced to:

// Package redis

func NewConn(ctx context.Context, defaultAddr string) *RedisConn {
    ctx = mctx.NewChild(ctx, "redis")
    addrParam := flag.String(ctx, "-addr", defaultAddr, "Address of redis instance to connect to")
    // finish setup

    return redisConn
}

Sharp-eyed gophers will notice that there's a key piece missing: When is mcfg.Parse called? When does addrParam actually get populated? Because you can't create the redis connection until that happens, but that can't happen inside redis.NewConn because there might be other things after redis.NewConn which want to set up parameters. To illustrate the problem, let's look at a simple program which wants to set up two redis components:

func main() {
    // Create the root context, an empty Context.
    ctx := context.Background()

    // Create the Contexts for two sub-components, foo and bar.
    ctxFoo := mctx.NewChild(ctx, "foo")
    ctxBar := mctx.NewChild(ctx, "bar")

    // Now we want to try to create a redis sub-component for each component.

    // This will set up the parameter "--foo-redis-addr", but bar hasn't had a
    // chance to set up its corresponding parameter, so the command-line can't
    // be parsed yet.
    fooRedis := redis.NewConn(ctxFoo, "127.0.0.1:6379")

    // This will set up the parameter "--bar-redis-addr", but, as mentioned
    // before, redis.NewConn can't parse command-line.
    barRedis := redis.NewConn(ctxBar, "127.0.0.1:6379")

    // If the command-line is parsed here, then how can fooRedis and barRedis
    // have been created yet? Creating the redis connection depends on the addr
    // parameters having already been parsed and filled.
}

We will solve this problem in the next section.

Instantiation vs Initialization

Let's break down redis.NewConn into two phases: instantiation and initialization. Instantiation refers to creating the component on the component structure and having it declare what it needs in order to initialize. After instantiation nothing external to the program has been done; no IO, no reading of the command-line, no logging, etc... All that's happened is that the empty shell of a redis component has been created.

Initialization is the phase when that shell is filled. Configuration parameters are read, startup actions like the creation of database connections are performed, and logging is output for informational and debugging purposes.

The key to making effective use of this dichotemy is to allow all components to instantiate themselves before they initialize themselves. By doing this we can ensure that, for example, all components have had the chance to declare their configuration parameters before configuration parsing is done.

So let's modify redis.NewConn so that it follows this dichotemy. It makes sense to leave instantiation related code where it is, but we need a mechanism by which we can declare initialization code before actually calling it. For this, I will introduce the idea of a "hook".

A hook is, simply a function which will run later. We will declare a new package, calling it mrun, and say that it has two new functions:

// Package mrun

// WithInitHook returns a new Context based off the passed in one, with the //
given hook registered to it.
func WithInitHook(ctx context.Context, hook func()) context.Context

// Init runs all hooks registered using WithInitHook. Hooks are run in the order
// they were registered.
func Init(ctx context.Context)

With these two functions we are able to defer the initialization phase of startup by using the same Contexts we were passing around for the purpose of denoting component structure. One thing to note is that, since hooks are being registered onto Contexts within the component instantiation code, the parent Context will not know about these hooks. Therefore it is necessary to add the child component's Context back into the parent. To do this we add two final functions to the mctx package:

// Package mctx

// WithChild returns a copy of the parent with the child added to it. Children
// of a Context can be retrieved using the Children function.
func WithChild(parent, child context.Context) context.Context

// Children returns all child Contexts which have been added to the given one
// using WithChild, in the order they were added.
func Children(ctx context.Context) []context.Context

Now, with these few extra pieces of functionality in place, let's reconsider the most recent example, and make a program which creates two redis components which exist independently of each other:

// Package redis

// NOTE that NewConn has been renamed to WithConn, to reflect that the given
// Context is being returned _with_ a redis component added to it.

func WithConn(parent context.Context, defaultAddr string) (context.Context, *RedisConn) {
    ctx = mctx.NewChild(parent, "redis")

    // we instantiate an empty RedisConn instance and parameters for it. Neither
    // has been initialized yet. They will remain empty until initialization has
    // occurred.
    redisConn := new(RedisConn)
    addrParam := flag.String(ctx, "-addr", defaultAddr, "Address of redis instance to connect to")

    ctx = mrun.WithInitHook(ctx, func() {
        // This hook will run after parameter initialization has happened, and
        // so addrParam will be usable. redisConn will be usable after this hook
        // has run as well.
        *redisConn = makeRedisConnection(*addrParam)
    })

    // Now that ctx has had configuration parameters and intialization hooks
    // instantiated into it, return both it and the empty redisConn instance
    // back to the parent.
    return mctx.WithChild(parent, ctx), redisConn
}

////////////////////////////////////////////////////////////////////////////////

// Package main

func main() {
    // Create the root context, an empty Context.
    ctx := context.Background()

    // Create the Contexts for two sub-components, foo and bar.
    ctxFoo := mctx.NewChild(ctx, "foo")
    ctxBar := mctx.NewChild(ctx, "bar")

    // Add redis components to each of the foo and bar sub-components. The
    // returned Contexts will be used to initialize the redis components.
    ctxFoo, redisFoo := redis.WithConn(ctxFoo, "127.0.0.1:6379")
    ctxBar, redisBar := redis.WithConn(ctxBar, "127.0.0.1:6379")

    // Add the sub-component contexts back to the root, so they can all be
    // initialized at once.
    ctx = mctx.WithChild(ctx, ctxFoo)
    ctx = mctx.WithChild(ctx, ctxBar)

    // Parse will descend into the Context and all of its children, discovering
    // all registered configuration parameters and filling them from the
    // command-line.
    mcfg.Parse(ctx)

    // Now that configuration has been initialized, run the Init hooks for each
    // of the sub-components.
    mrun.Init(ctx)

    // At this point the redis components have been fully initialized and may be
    // used. For this example we'll copy all keys from one to the other.
    keys := redisFoo.Command("KEYS", "*")
    for i := range keys {
        val := redisFoo.Command("GET", keys[i])
        redisBar.Command("SET", keys[i], val)
    }
}

Full example

Part 3: Annotations, Logging, and Errors