Ep 026: One Call to Rule Them All

April 26, 2019

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Christoph thinks goals are data, not function names.

We were talking about the twitter handle again.
Last week, we talked about faking. It's not mocking.
The magic that makes it possible is using a protocol.
Switch out the real handle or the fake handle in component based on configuration.
"Yes, I do want to speak to the log file."
"Sometimes, the log file gets lonely."
(02:43) Christoph wants to talk about the protocol.
We made a function for each operation we did in Twitter.
- Post tweet
- Search
- Get timeline
Each function took the information needed for that operation as individual parameters.
(04:32) Example: the AWS API wrapper that Cognitect released.
Other wrappers are enormous, with functions for each AWS functions.
Cognitect's wrapper has just one: invoke. At least only one that gets work done.
Unconventional (aka "weird").
Take a step back. What needs to happen to call a remote API?
We need to make an HTTP call to some end point.
"100% of the information that that server needs to get from us, we transmit as data."
"The path, the headers, everything about it is data."
"The function is in the URL and the URL is in the data. It's all data."
If you want the operations to be exposed as functions, you end up promoting the operation to be a function name, but when making the request you need to put the operation back into the data.
Benefit (not really): we get to write a lot of boilerplate code.
"Nothing like some boilerplate to get you warmed up in the morning."
(09:15) Back to the Twitter handle, what if we just had one function?
"Making a function for each endpoint goes against what we talked about last week, which is making our context explicit."
(09:55) First benefit of one function: Simplifies the worker half of our algorithm.
Before:
- Decider creates map with {:command :twitter/fetch-timeline :twitter/last-tweet-id 1234}
- Worker uses a multi-method to convert that to (handle/fetch-timeline handle {:twitter/last-tweet-id 1234})
- Handle function will construct Twitter request {:url "https://twitter.com/fetch-timeline" :last-tweet 1234}
- Handle sends request to Twitter and handles the response.
After:
- Decider creates map with {:command :twitter/operation :twitter/command :fetch-timeline :twitter/last-tweet-id 1234}
- Worker's multi-method detects a Twitter operation and passes the entire operation map to the handle.
- Handle transforms the operation into the data needed for the request.
- Handle sends request to Twitter and handles the response.
When the data is in the map, it's easier to test.
(18:03) Second benefit of one function: a place for common code in the handle.
Inside the handle, you can use a multi-method.
If there is common code, like auth checking or data transformation, that can go into the single function.
The same tick-tock that was used to get separate side effects from logic in our algorithm can be used inside the handle.
"Imperative logic is like a branching tree of side-effects."
The handle works on a rich map of information, and with one function, we're handing it one rich map of information.
"You have deciders all the way down."
(20:52) How do we do spec this single function?
One function needs to take data in multiple shapes. Making a spec that matches all of those shapes will be difficult.
This function call other, more specific functions to get its work done, so there can be specific specs on those.
"You don't have to spec everything at all the levels."
We can also lightly check the entry point to check for attributes that are common to all shapes.
"Spec is an open system. I can check for the presence of what I need without having to assert a closed world."
(22:55) Thinking about the symmetry. The following are equivalent:
- 4 functions that each take 5 parameters.
- 4 functions that each take a map with 5 keys.
- 1 function that takes a map with 6 keys (the last one being the operation).
Programming systems that are strongly typed push you toward more functions and less data.
Trampoline from data to function to data to function to data...
Clojure's structural checking makes it so that we can have assurances about data without being forced to check or name everything.
"Say what you mean, don't make me read your body language and guess."

Message Queue discussion:

(25:50) Separating logic from side effects.
"The tree of side effects is like a bowl where you swirl around into the bottom and then swirl back up to the top."
In a call stack, side-effects should be shallow on the stack.
"Pure things can't screw you over."
"Keep your friends close and your side-effects closer."
Running this concept out to its logical conclusion enabled us to discover the tick-tock approach.

Related episodes:

Clojure in this episode:

defprotocol
defrecord