2019-05-18 20:29:48 +00:00
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---
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title: >-
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Program Structure and Composability
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description: >-
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Discussing the nature of program structure, the problems presented by
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complex structures, and a pattern which helps in solving those problems.
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---
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2019-05-22 20:26:51 +00:00
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TODO:
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* Double check if I'm using "I" or "We" everywhere (probably should use "I")
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2019-05-19 19:07:02 +00:00
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## Part 0: Introduction
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This post is focused on a concept I call "program structure", which I will try
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2019-05-19 19:07:02 +00:00
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to shed some light on before discussing complex program structures, then
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2019-05-18 20:29:48 +00:00
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discussing why complex structures can be problematic to deal with, and finally
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discussing a pattern for dealing with those problems.
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My background is as a backend engineer working on large projects that have had
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2019-05-19 19:07:02 +00:00
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many moving parts; most had multiple services interacting with each other, using
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many different databases in various contexts, and facing large amounts of load
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from millions of users. Most of this post will be framed from my perspective,
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and will present problems in the way I have experienced them. I believe,
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however, that the concepts and problems I discuss here are applicable to many
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other domains, and I hope those with a foot in both backend systems and a second
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domain can help to translate the ideas between the two.
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Also note that I will be using Go as my example language, but none of the
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concepts discussed here are specific to Go. To that end, I've decided to favor
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readable code over "correct" code, and so have elided things that most gophers
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hold near-and-dear, such as error checking and comments on all public types, in
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order to make the code as accessible as possible to non-gophers as well. As with
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before, I trust someone with a foot in Go and another language can translate
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help me translate between the two.
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2019-05-18 20:29:48 +00:00
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## Part 1: Program Structure
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2019-05-19 19:07:02 +00:00
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In this section I will discuss the difference between directory and program
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structure, show how global state is antithetical to compartmentalization (and
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therefore good program structure), and finally discuss a more effective way to
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think about program structure.
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### Directory Structure
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2019-05-18 20:29:48 +00:00
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For a long time I thought about program structure in terms of the hierarchy
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present in the filesystem. In my mind, a program's structure looked like this:
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```
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// The directory structure of a project called gobdns.
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src/
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config/
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dns/
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http/
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ips/
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persist/
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repl/
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snapshot/
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main.go
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```
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2019-05-19 19:07:02 +00:00
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What I grew to learn was that this conflation of "program structure" with
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"directory structure" is ultimately unhelpful. While I won't deny that every
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program has a directory structure (and if not, it ought to), this does not mean
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that the way the program looks in a filesystem in any way corresponds to how it
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looks in our mind's eye.
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The most notable way to show this is to consider a library package. Here is the
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structure of a simple web-app which uses redis (my favorite database) as a
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backend:
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```
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src/
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redis/
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http/
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main.go
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```
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If I were to ask you, based on that directory strucure, what the program does,
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in the most abstract terms, you might say something like: "The program
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establishes an http server which listens for requests, as well as a connection
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to the redis server. The program then interacts with redis in different ways,
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based on the http requests which are received on the server."
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2019-05-19 19:07:02 +00:00
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And that would be a good guess. Here's a diagram which depicts the program
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structure, wherein the root node, `main.go`, takes in requests from `http` and
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processes them using `redis`.
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TODO diagram
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This is certainly a viable guess for how a program with that directory structure
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operates, but consider another: "A component of the program called `server`
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establishes an http server which listens for requests, as well as a connection
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to a redis server. `server` then interacts with that redis connection in
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different ways, based on the http requests which are received on the http
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server. Additionally, `server` tracks statistics about these interactions and
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makes them available to other components. The root component of the program
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establishes a connection to a second redis server, and stores those statistics
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in that redis server."
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TODO diagram
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The directory structure could apply to either description; `redis` is just a
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library which allows for interacting with a redis server, but it doesn't specify
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_which_ server, or _how many_. And those are extremely important factors which
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are definitely reflected in our concept of the program's structure, and yet not
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2019-05-19 19:07:02 +00:00
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in the directory structure. **What the directory structure reflects are the
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different _kinds_ of components available to use, but it does not reflect how a
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program will use those components.**
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2019-05-18 20:29:48 +00:00
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2019-05-19 19:07:02 +00:00
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### Global State vs. Compartmentalization
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The directory-centric approach to structure often leads to the use of global
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singletons to manage access to external resources like RPC servers and
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databases. In the above example the `redis` library might contain code which
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looks something like:
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```go
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// A mapping of connection names to redis connections.
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var globalConns = map[string]*RedisConn{}
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func Get(name string) *RedisConn {
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if globalConns[name] == nil {
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globalConns[name] = makeConnection(name)
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}
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return globalConns[name]
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}
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```
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Even though this pattern would work, it breaks with our conception of the
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program structure in the more complex case shown above. Rather than having the
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`server` component own the redis server it uses, the root component would be the
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owner of it, and `server` would be borrowing it. Compartmentalization has been
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broken, and can only be held together through sheer human discipline.
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This is the problem with all global state. It's shareable amongst all components
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of a program, and so is owned by none of them. One must look at an entire
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codebase to understand how a globally held component is used, which might not
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even be possible for a large codebase. And so the maintainers of these shared
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components rely entirely on the discipline of their fellow coders when making
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changes, usually discovering where that discipline broke down once the changes
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have been pushed live.
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Global state also makes it easier for disparate services/components to share
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datastores for completely unrelated tasks. In the above example, rather than
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creating a new redis instance for the root component's statistics storage, the
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coder might have instead said "well, there's already a redis instance available,
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I'll just use that." And so compartmentalization would have been broken further.
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Perhaps the two instances _could_ be coalesced into the same one, for the sake
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of resource efficiency, but that decision would be better made at runtime via
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the configuration of the program, rather than being hardcoded into the code.
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From the perspective of team management, global state-based patterns do nothing
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except slow teams down. The person/team responsible for maintaining the central
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library which holds all the shared resources (`redis`, in the above example)
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becomes the bottleneck for creating new instances for new components, which will
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further lead to re-using existing instances rather than create new ones, further
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breaking compartmentalization. The person/team responsible for the central
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library often finds themselves as the maintainers of the shared resource as
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well, rather than the team actually using it.
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2019-05-22 20:26:51 +00:00
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### Component Structure
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So what does proper program structure look like? In my mind the structure of a
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program is a hierarchy of components, or, in other words, a tree. The leaf nodes
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of the tree are almost _always_ IO related components, e.g. database
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connections, RPC server frameworks or clients, message queue consumers, etc...
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The non-leaf nodes will _generally_ be components which bring together the
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functionalities of their children in some useful way, though they may also have
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some IO functionality of their own.
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Let's look at an even more complex structure, still only using the `redis` and
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`http` component types:
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TODO diagram:
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```
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root
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rest-api
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redis
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http
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redis // for stats keeping
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debug
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http
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```
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2019-05-22 20:26:51 +00:00
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This component structure contains the addition of the `debug` component. Clearly
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the `http` and `redis` components are reusable in different contexts, but for
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this example the `debug` endpoint is as well. It creates a separate http server
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which can be queried to perform runtime debugging of the program, and can be
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tacked onto virtually any program. The `rest-api` component is specific to this
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program and therefore not reusable. Let's dive into it a bit to see how it might
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be implemented:
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```go
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// RestAPI is very much not thread-safe, hopefully it doesn't have to handle
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// more than one request at once.
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type RestAPI struct {
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redisConn *redis.RedisConn
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httpSrv *http.Server
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// Statistics exported for other components to see
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RequestCount int
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FooRequestCount int
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BarRequestCount int
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}
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func NewRestAPI() *RestAPI {
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r := new(RestAPI)
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r.redisConn := redis.NewConn("127.0.0.1:6379")
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// mux will route requests to different handlers based on their URL path.
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mux := http.NewServeMux()
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mux.Handle("/foo", http.HandlerFunc(r.fooHandler))
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mux.Handle("/bar", http.HandlerFunc(r.barHandler))
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r.httpSrv := http.NewServer(mux)
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// Listen for requests and serve them in the background.
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go r.httpSrv.Listen(":8000")
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return r
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}
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func (r *RestAPI) fooHandler(rw http.ResponseWriter, r *http.Request) {
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r.redisConn.Command("INCR", "fooKey")
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r.RequestCount++
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r.FooRequestCount++
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}
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func (r *RestAPI) barHandler(rw http.ResponseWriter, r *http.Request) {
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r.redisConn.Command("INCR", "barKey")
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r.RequestCount++
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r.BarRequestCount++
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}
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```
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As can be seen, `rest-api` coalesces `http` and `redis` into a simple REST api,
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using pre-made library components. `main.go`, the root component, does much the
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same:
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```go
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func main() {
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// Create debug server and start listening in the background
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debugSrv := debug.NewServer()
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// Set up the RestAPI, this will automatically start listening
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restAPI := NewRestAPI()
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// Create another redis connection and use it to store statistics
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statsRedisConn := redis.NewConn("127.0.0.1:6380")
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for {
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time.Sleep(1 * time.Second)
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statsRedisConn.Command("SET", "numReqs", restAPI.RequestCount)
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statsRedisConn.Command("SET", "numFooReqs", restAPI.FooRequestCount)
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statsRedisConn.Command("SET", "numBarReqs", restAPI.BarRequestCount)
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}
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}
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```
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2019-05-19 19:07:02 +00:00
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One thing which is clearly missing in this program is proper configuration,
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whether from command-line, environment variables, etc.... As it stands, all
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configuration parameters, such as the redis addresses and http listen addresses,
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are hardcoded. Proper configuration actually ends up being somewhat difficult,
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as the ideal case would be for each component to set up the configuration
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variables of itself, without its parent needing to be aware. For example,
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`redis` could set up `addr` and `pool-size` parameters. The problem is that
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there are two `redis` components in the program, and their parameters would
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therefore conflict with each other. An elegant solution to this problem is
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discussed in the next section.
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## Part 2: Context, Configuration, and Runtime
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2019-05-22 20:26:51 +00:00
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The key to the configuration problem is to recognize that, even if there are two
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of the same component in a program, they can't occupy the same place in the
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program's structure. In the above example there are two `http` components, one
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under `rest-api` and the other under `debug`. Since the structure is represented
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as a tree of components, the "path" of any node in the tree uniquely represents
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it in the structure. For example, the two `http` components in the previous
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example have these paths:
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```
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root -> rest-api -> http
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root -> debug -> http
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```
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If each component were to know its place in the component tree, then it would
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easily be able to ensure that its configuration and initialization didn't
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conflict with other components of the same type. If the `http` component sets up
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a command-line parameter to know what address to listen on, the two `http`
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components in that program would set up:
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```
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--rest-api-listen-addr
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--debug-listen-addr
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```
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So how can we enable each component to know its path in the component structure?
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To answer this we'll have to take a detour through go's `Context` type.
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### Context and Configuration
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As I mentioned in the Introduction, my example language in this post is Go, but
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there's nothing about the concepts I'm presenting which are specific to Go. To
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put it simply, Go's builtin `context` package implements a type called
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`context.Context` which is, for all intents and purposes, an immutable key/value
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store. This means that when you set a key to a value on a Context (using the
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`context.WithValue` function) a new Context is returned. The new Context
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contains all of the original's key/values, plus the one just set. The original
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remains untouched.
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(Go's Context also has some behavior built into it surrounding deadlines and
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process cancellation, but those aren't relevant for this discussion.)
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Context makes sense to use for carrying information about the program's
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structure to it's different components; it is informing each of what _context_
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it exists in within the larger structure. To use Context effectively, however,
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it is necessary to implement some helper functions. Here are their function
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signatures:
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```go
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// NewChild creates and returns a new Context based off of the parent one. The
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// child will have a path which is the parent's path appended with the given
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// name.
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func NewChild(parent context.Context, name string) context.Context
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// Path returns the sequence of names which were used to produce this Context
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// via calls to the NewChild function.
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func Path(ctx context.Context) []string
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```
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`NewChild` is used to create a new Context, corresponding to a new child node in
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the component structure, and `Path` is used retrieve the path of any Context
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within that structure. For the sake of keeping the examples simple let's pretend
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these functions have been implemented in a package called `mctx`. Here's an
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example of how `mctx` might be used in the `redis` component's code:
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|
|
```go
|
|
|
|
func NewRedis(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 `NewRedis` is reduced to:
|
|
|
|
|
|
|
|
```go
|
|
|
|
func NewRedis(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 `NewRedis` because there might be other things after `NewRedis` 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:
|
|
|
|
|
|
|
|
```go
|
|
|
|
func main() {
|
|
|
|
// Create the root context, and 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 instances for each component. But...
|
|
|
|
|
|
|
|
// 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.NewRedis(ctxFoo, "127.0.0.1:6379")
|
|
|
|
|
|
|
|
// This will set up the parameter "--bar-redis-addr", but, as mentioned
|
|
|
|
// before, NewRedis can't parse command-line.
|
|
|
|
barRedis := redis.NewRedis(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.
|
2019-05-19 19:07:02 +00:00
|
|
|
|
2019-05-22 20:26:51 +00:00
|
|
|
## Init vs. Start
|