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155 lines
4.7 KiB
Markdown
155 lines
4.7 KiB
Markdown
# Implementing on the Server
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Now that we've got a config defined in `common/` for a GPT, we need to implement
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parts of it on the server.
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## Where do Server Implementations go?
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Implementations should be written in `server/src/game-implementations/games/GAMENAME.ts`.
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Once you have written a config, go to `server/src/game-implementations/game-implementations.ts` and import it. Mount the game configuration on `GPT_SERVER_IMPLEMENTATIONS`.
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## `chartSpecificValidators`
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Any metrics you declared as being `chartSpecificMax: true` in the config need
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an implementation here. You can declare a function that takes in the metric's value
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and the chart the score is on and validate accordingly.
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These functions should return a string on error, and true on success. This is aligned
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with how [Prudence](https://github.com/zkldi/Prudence) works, so you can re-use prudence
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functions here.
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!!! example
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```ts
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musicRate: (rate, chart) => {
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switch (chart.difficulty) {
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case "BSC":
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case "ADV":
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case "EXT":
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return p.isBetween(0, 100)(rate);
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case "HARD BSC":
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case "HARD ADV":
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case "HARD EXT":
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return p.isBetween(0, 120)(rate);
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}
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},
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```
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## `scoreDeriver`
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Any derived metrics you declared are produced by a single function
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`(scoreData, chart) => derivedMetrics` that returns all derived fields at once.
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!!! example
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```ts
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(scoreData, chart) => ({
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percent: (100 * scoreData.score) / (chart.data.notecount * 2),
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grade: GetGrade(G, scoreData.score),
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});
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```
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## `scoreCalcs`, `sessionCalcs`, `profileCalcs`
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For any `{score, session, profile}RatingAlgs` you defined, implement them here.
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## `classDerivers`
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For all the classes you declared with `type: "DERIVED"`, implement the derivers here.
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## `goalCriteriaFormatters`
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When creating a goal on a metric, how should we format the title?
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```
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Get a score of 1234 on 5.1.1 SP ANOTHER
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^^^^^^^^^^^^^^^^^^^^^^
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this bit
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```
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## `goalOutOfFormatters`
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When creating a goal on a metric, how should we format the "outOf" part?
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```
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HARD CLEAR/FULL COMBO
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^^^^^^^^
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this bit
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```
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## `goalProgressFormatters`
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How should we format the progress of this goal?
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```
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HARD CLEAR/FULL COMBO
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^^^^^^^^
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this bit
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```
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## `pbMergeFunctions`
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How should we combine scores into one PB? There is an _extraordinarily_ useful helper
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function for this called `CreatePBMergeFor`.
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The way PBs are merged works like a chain: the first score is the best score this user
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has on this chart for the `defaultMetric` declared in the config. Then, every
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merge function defined in this pipeline is ran on the score and mutates the original.
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Eventually, you have a fully merged PB document.
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The below code defines a PB merger that gets the largest lamp. It will then run the
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final function with the base score and the score it just fetched.
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In the event it doesn't find a score (i.e. the user has no scores with `optional.bp`)
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the function will simply not be called.
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```ts
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[
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CreatePBMergeFor("largest", "enumIndexes.lamp", "Best Lamp", (base, lamp) => {
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base.scoreData.lamp = lamp.scoreData.lamp;
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base.scoreData.optional.gsmEasy = lamp.scoreData.optional.gsmEasy;
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base.scoreData.optional.gsmNormal = lamp.scoreData.optional.gsmNormal;
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base.scoreData.optional.gsmHard = lamp.scoreData.optional.gsmHard;
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base.scoreData.optional.gsmEXHard = lamp.scoreData.optional.gsmEXHard;
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base.scoreData.optional.gauge = lamp.scoreData.optional.gauge;
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base.scoreData.optional.gaugeHistory = lamp.scoreData.optional.gaugeHistory;
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base.scoreData.optional.comboBreak = lamp.scoreData.optional.comboBreak;
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}),
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CreatePBMergeFor("smallest", "optional.bp", "Lowest BP", (base, bp) => {
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base.scoreData.optional.bp = bp.scoreData.optional.bp;
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}),
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];
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```
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## `defaultMergeRefName`
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As mentioned above, the chain of PB functions starts by plucking the best score this
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user has on this chart under the `defaultMetric`. What should we call that score?
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!!! example
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For IIDX, this is "Best Score". For something like GITADORA, which only has percent,
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this might be called "Best Percent".
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## `scoreValidators`
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Out of the box, Tachi will assume complete independence of all variables in a score.
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However, this is often not the case, and there are certain things you expect to be true
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between the metrics of a score.
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For example, you shouldn't be able to submit a `PERFECT ULTIMATE CHAIN` if your score
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isn't 10 million - the two imply each other!
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In this part of the server implementation, you may specify as many validation functions
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as you like. These assert relations between the fields on a score, and allow you
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to restrict certain things.
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Like real life, passing judgements subjects you to more scrutiny -- getting a `FULL COMBO` with misses should likely fail a validation function.
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## That's it!
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The only thing left is to define the [Client Implementation](./client-impl.md)!
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