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In episode hpr2748 Writing Web Game in Haskell - Special events, I talked about how to add special events in the game. One drawback with the system presented there was that the kragii worms might attack planet that already had kragii worms present. This time we’ll look into how to prevent this. As a nice bonus, we also come up with system that can be used to record when a planet has particularly good harvest season.
Data types and Database
We need a way to represent different kinds of statuses that a planet might have. These will include things like on going kragii attack or a particularly good harvest season. And since these are will be stored in database, we are also going to use derivePersistField to generate code needed for that.
data PlanetaryStatus = GoodHarvest | PoorHarvest | GoodMechanicals | PoorMechanicals | GoodChemicals | PoorChemicals | KragiiAttack derivePersistField "PlanetaryStatus"
We could have recorded statuses as strings, but declaring a separate data type means that compiler can catch typos for us. It also makes code easier to read as
PlanetaryStatus is much more informative than
For database, we use following definition shown below in models file. It creates database table
planet_status and respective Haskell data type
PlanetStatus. There will be one row in database for each status that a planet has. I could have stored all statuses in a list and store that in database, effectively having one row for any planet. Now there’s one row for any planet + status combination. Choice wasn’t really based on any deep analysis, but merely a gut feeling that this feels like a good idea.
PlanetStatus json planetId PlanetId status PlanetaryStatus expiration Int Maybe deriving Show Read Eq
expiration column doesn’t have
NOT NULL constraint like all other columns in the table. This is reflected in
PlanetStatus record where data type of
Maybe Int instead of
Int. So some statuses will have expiration time, while others might not. I originally chose to represent time as
Int instead of own data type, but I have been recently wondering if that was really a good decision.
Kragii attack, redux
Code that does actual database query looks pretty scary on a first glance and it’s rather long. First part of the code is there to query database and join several tables into the query. Second part of the code deals with counting and grouping data and eventually returning
[Entity Planet] data that contains all planets that match the criteria.
-- | Load planets that are kragii attack candidates kragiiTargetPlanets :: (MonadIO m, BackendCompatible SqlBackend backend , PersistQueryRead backend, PersistUniqueRead backend) => Int -> Int -> Key Faction -> ReaderT backend m [Entity Planet] kragiiTargetPlanets pop farms fId = do planets <- E.select $ E.from $ (planet `E.LeftOuterJoin` population `E.LeftOuterJoin` building `E.LeftOuterJoin` status) -> do E.on (status E.?. PlanetStatusPlanetId E.==. E.just (planet E.^. PlanetId) E.&&. status E.?. PlanetStatusStatus E.==. E.val (Just KragiiAttack)) E.on (building E.?. BuildingPlanetId E.==. E.just (planet E.^. PlanetId)) E.on (population E.?. PlanetPopulationPlanetId E.==. E.just (planet E.^. PlanetId)) E.where_ (planet E.^. PlanetOwnerId E.==. E.val (Just fId) E.&&. building E.?. BuildingType E.==. E.val (Just Farm) E.&&. E.isNothing (status E.?. PlanetStatusStatus)) E.orderBy [ E.asc (planet E.^. PlanetId) ] return (planet, population, building) let grouped = groupBy ((a, _, _) (b, _, _) -> entityKey a == entityKey b) planets let counted = catMaybes $ fmap farmAndPopCount grouped let filtered = filter ((_, p, f) -> p >= pop || f >= farms) counted let mapped = fmap ((ent, _, _) -> ent) filtered return mapped
In any case, when we’re querying for possible kragii attack candidates, the query selects all planets that are owned by a given faction and have population of at least 10 (left outer join to
planet_population table), have at least 5 farming complex (left outer join to
building table) and don’t have on going kragii attack (left outer join to
planet_status table). This is encapsulated in
kragiiTargetPlanets 10 5 function in the
kragiiAttack function shown below.
Rest of the code deals with selecting a random planet from candidates, inserting a new
planet_status row to record that kragii are attacking the planet and creating special event so player is informed about the situation and can react accordingly.
kragiiAttack date faction = do planets <- kragiiTargetPlanets 10 5 $ entityKey faction if length planets == 0 then return Nothing else do n <- liftIO $ randomRIO (0, length planets - 1) let planet = maybeGet n planets let statusRec = PlanetStatus <$> fmap entityKey planet <*> Just KragiiAttack <*> Just Nothing _ <- mapM insert statusRec starSystem <- mapM (getEntity . planetStarSystemId . entityVal) planet let event = join $ kragiiWormsEvent <$> planet <*> join starSystem <*> Just date mapM insert event
Second piece to the puzzle is status removal. In can happen manually or automatically when the prerecorded date has passed. Former method is useful for special events and latter for kind of seasonal things (good harvest for example).
For example, in case of removing kragii attack status, code below serves as an example. The interesting part is
deleteWhere that does actual database activity and removes all
KragiiAttack statuses from given planet.
removeNews event odds = MaybeT $ do res <- liftIO $ roll odds case res of Success -> do _ <- lift $ deleteWhere [ PlanetStatusPlanetId ==. kragiiWormsPlanetId event , PlanetStatusStatus ==. KragiiAttack ] _ <- tell [ WormsRemoved ] return $ Just RemoveOriginalEvent Failure -> do _ <- tell [ WormsStillPresent ] return $ Just KeepOriginalEvent
Removal of expired statuses is done based on the date, by using
<=. operator to compare
expiration column to given date.
_ <- deleteWhere [ PlanetStatusExpiration <=. Just date]
Other uses and further plans
Like mentioned before, planet statuses can be used for variety of things. One such application is recording particularly good (or poor) harvest season. When such thing occurs, new
planet_status record is inserted into database with
expiration to set some suitable point in future. System will then automatically remove the status after that date is reached.
In the meantime, every time food production is calculated, we have to check for possible statuses that might affect it and take them into account (as form of small bonus or malus).
While this system is for planet statuses only, similar systems can be build for other uses (like statuses that affect a single ship or whole star system).
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