# PoKeMoNg - [About](#about) - [🗂️DCM](#dcm) - [🧬UML Class diagram](#uml-class-diagram) - [🗺NoSQL Schema Versioning Strategy](#nosql-schema-versioning-strategy) - [Schema Versioning Pattern](#schema-versioning-pattern) - [Incremental Document Migration](#incremental-document-migration) - [🐕‍🦺Services](#services) - [🌺Special requests](#special-requests) - [`Pokemong` by nickname](#pokemong-by-nickname) - [`Pokemong` in date interval](#pokemong-in-date-interval) - [Prep steps](#prep-steps) - [♨️Java version](#java-version) - [🔐Database connection](#database-connection) - [Running the application in dev mode](#running-the-application-in-dev-mode) - [API testing](#api-testing) - [🧪Sample dataset](#sample-dataset) - [🩺API testing tools](#api-testing-tools) - [📱Front end](#front-end) - [🏴‍☠️SwaggerUI](#swaggerui) - [Known limitations](#known-limitations) - [🔀Types are left at the user's mercy](#types-are-left-at-the-users-mercy) This is a [Quarkus](https://quarkus.io/) / [MongoDB](https://mongodb.com/) app for educational purposes. Instructions are [here](https://clientserveur-courses.clubinfo-clermont.fr/Notation.html) for reference. ## About A "Pokemong" is a playful term for a MongoDB pocket monster. The application is developed using the Quarkus framework and uses MongoDB as its database. This application is a RESTful service designed to emulate a basic `Pokemong` management system. It allows users to perform CRUD operations on `Pokemongs`, `Trainers`, and `Moves`. ### 🗂️DCM Let's cover the entities and relationships in this Data Concept Model: #### `Trainer` These are the individuals who capture and train `pokemongs`. They can engage in battles with other `trainers.` * a `trainer` has fought between 0 and many `trainers` * a `trainer` owns between 0 and many `pokemongs` #### `Pokemong` These are the creatures that `trainers` capture and train. They can be trained or wild. * a `pokemong` is owned by 0 or 1 `trainer` * a `pokemong` has 1 or 2 `types` * a `pokemong` knows between 0 and 4 `moves`, #### `Move` These are the abilities or actions that a `pokemong` can perform. This covers the strategic aspects of battles, as different `moves` can have different effects and powers depending on the type of the `pokemong` and the `move`. * a `move` can be known by between 0 and zillions of `pokemongs` * a `move` has 1 and only 1 `type` #### `Type` These define the elements or categories that a `pokemong` or a `move` can belong to. * a `type` can define between 0 and zillions of `pokemongs` * a `type` can define between 0 and zillions of `moves` Data Concept Model Looking at things from the point of view of entities, instead of relationships ### 🧬UML Class diagram ```mermaid classDiagram class Trainer { + id: ObjectId + name: string + dob: date + wins: int + losses: int } class Pokemong { + id: ObjectId + nickname: string? + dob: date + level: int + pokedexId: int + evoStage: int + evoTrack: PokemongName[] } class Move { + id: ObjectId + name: string + category: MoveCategoryName + power: int + accuracy: int } class Type { + id: ObjectId + name: TypeName + weakAgainst: TypeName[] + effectiveAgainst: TypeName[] } class TypeName { <> + FIRE + WATER + ... } class PokemongName { <> + BULBASAUR + IVYSAUR + ... } class MoveCategoryName { <> + PHYSICAL + SPECIAL + STATUS } Trainer --> "0..*" Trainer: pastOpponents Trainer --> "0..*" Pokemong: pokemongs Pokemong --> "0..1" Trainer: trainer Pokemong --> "0..4" Move: moveSet Pokemong --> "1..2" Type: types Move --> Type: type Type ..> TypeName Pokemong ..> PokemongName Move ..> MoveCategoryName ``` ### 🗺NoSQL Schema Versioning Strategy This application uses MongoDB, a NoSQL database, which provides flexibility in our data model. While this flexibility has its advantages, it poses a unique challenge when we need to update our data model, specifically when we want to introduce breaking changes in the existing schema. We have adopted a schema versioning strategy to overcome this challenge and manage these changes efficiently. #### Schema Versioning Pattern Schema versioning is a pattern that involves tagging each document in a collection with a version number. This version number corresponds to the schema of the document and is used to handle schema changes in the code that reads these documents. Each entity in our model extends a `GenericVersionedEntity` class, which includes a `schemaVersion` field. This field is an integer that starts at 1 and is to be incremented by one with each schema change. Every change to the schema needs to involve the schema version number being incremented. #### Incremental Document Migration When a document is read from the database, the version number in the document is checked. If the version number is less than the current version, the document is updated to the current version, and the updated document is written back to the database. This process effectively migrates the document to the current version. In the example of the `Move` class, the codec's `decodeV1` method handles documents with a `schemaVersion` of less than `2`. When it reads a document with this version, it updates the `schemaVersion` to `2`, and writes the updated document back to the database. ```java Move decodeV1(Document document){ // ... // Increment the schemaVersion to the current version move.setSchemaVersion(2); // Save the updated Move object back to the database moveRepository.persistOrUpdate(move); // ... } ``` This strategy allows for graceful schema evolution in a NoSQL environment. Instead of requiring all documents to be migrated at once, which can be a time-consuming operation for large collections, it enables incremental document migration. This approach also helps to avoid downtime during schema migration, as the application continues to function correctly regardless of the document version. As documents are read, they are updated to the current schema version, allowing the schema migration to happen gradually over time. However, note that this strategy increases write operations to the database, which could affect application performance. ### 🐕‍🦺Services Each entity (`Pokemong`, `Trainer`, `Move`) in the application has a corresponding service class. These service classes are responsible for handling the business logic related to their respective entities. They interact with the database through their associated repositories, performing CRUD operations. All service classes inherit from a `GenericService` class, which provides the following methods: * addOne(T entity): Adds a new entity to the database, after validating it. * getOneById(String id): Retrieves a single entity from the database by its ID. * getAll(): Retrieves all entities of a certain type from the database. * deleteOneById(String id): Deletes an entity from the database by its ID. * updateOne(T entity): Updates an existing entity in the database. This method is meant to be overridden in child service classes to provide the specific update logic for each type of entity. * updateAll(List entities): Updates all entities in a given list. Each entity is validated before updating. These methods allow the application to perform all the basic CRUD operations on any type of entity. The specific logic for each type of entity (like how to validate a Pokemong, how to update a Move, etc.) is provided in the child service classes that inherit from `GenericService`. Many business rules were applied, so let's use just one for an example here: when a `trainer` gets updated, it can mean consequences for any number of `pokemongs`, as this commented code from inside `TrainerService.UpdateOne()` explains ```java // all old pokemongs who are not there anymore lose their trainer reference pokemongService.batchUpdatePokemongTrainers( oldPokemongs.stream() .filter(tp->!newPokemongs.contains(tp)) .collect(Collectors.toSet()), null); // if this trainer gained a pokemong, that pokemong's ex-trainer if any needs to lose said pokemong transferNewlyArrivedTrainerPokemongs(oldPokemongs,newPokemongs); // all new pokemongs who were not there before gain this trainer's reference pokemongService.batchUpdatePokemongTrainers( newPokemongs.stream() .filter(tp->!oldPokemongs.contains(tp)) .collect(Collectors.toSet()), existingTrainer.getId() ); ``` This diagram attempts to show the relationship between services in this API ```mermaid classDiagram class GenericService~T~ { -GenericRepository~T~ repository +setRepository(GenericRepository~T~ repository) +addOne(T entity): T +validateOne(T entity) +getOneById(String id): T +getAll(): List~T~ +deleteOneById(String id) +updateOne(T entity): T +updateAll(List~T~ entities) } class MoveService { -MoveRepository moveRepository -PokemongService pokemongService +init() +validateOne(Move move) +getOneById(String id): Move +getAll(): List~Move~ +deleteOneById(String id) +updateOne(Move move): Move +existsById(String moveId): boolean -batchUpdatePokemongTrainers(Move move) -migrateToV2(Move move): Move } class TrainerService { -TrainerRepository trainerRepository -PokemongService pokemongService +init() +addOne(Trainer trainer): Trainer +validateOne(Trainer trainer) +deleteOneById(String id) +updateOne(Trainer trainer): Trainer -transferNewlyArrivedTrainerPokemongs(...) } class PokemongService { -PokemongRepository pokemongRepository -MoveService moveService -TrainerService trainerService +init() +addOne(Pokemong pokemong): Pokemong +validateOne(Pokemong pokemong) +deleteOneById(String id) +updateOne(Pokemong pokemong): Pokemong +existsById(String pokemongId): boolean -updateTrainerPokemong(...) +findByMove(String id): List~Pokemong~ +isEvoValid(String id, PokemongName species): boolean +batchUpdatePokemongTrainers(...) } GenericService <|-- "T <- Move" MoveService GenericService <|-- "T <- Trainer" TrainerService GenericService <|-- "T <- Pokemong" PokemongService ``` ### 🌺Special requests This API goes a little bit beyond basic CRUD operations. #### `Pokemong` by nickname Using a MongoDB filter with a regex, `pokemongs` are searchable by nickname with the URL `/pokemong/nickname/{nickname}` where `{nickname}` is a partial, case-insensitive search term. #### `Pokemong` in date interval Users can also use the route `pokemong/dob/{startDate}/{endDate}` to search for `pokemongs` who where born within that interval (bounds included). ## Prep steps ### ♨️Java version This project is set up to use `Java 17`. Your build will fail if the version of `Java` that your build tools are using does not match that.
💻 Run from command line You should have `JDK 17` installed locally, and accessible to `Gradle`. That may involve updating your `JAVA_HOME` and `Path` environment variables.
🛠️ Run from an IDE If you're planning to run this app directly from an IDE like IntelliJ, make sure to update any `Gradle JVM` (or similar) settings to use `JDK 17` for `Gradle` tasks
### 🔐Database connection Note that the DB connection properties are not included -- your `src/main/resources/application.properties` should look like this : ```properties quarkus.mongodb.connection-string=mongodb+srv://:@..mongodb.net quarkus.mongodb.database= ```
🏫 If you are the corrector To be able to use this app, update `application.properties` with the provided database secrets. If none were provided, that was a mistake. Sorry. Please request them to the owner of this repo.
👥 If you are another user or developer To be able to use this app, first create a MongoDB database, either locally or on their [Atlas Cloud](https://cloud.mongodb.com/), then update `application.properties` with your database secrets. You may want to look up the nice [MongoDB official documentation](https://www.mongodb.com/docs/) if you get stuck.
## Running the application in dev mode You can run the application in dev mode using: ```shell script ./gradlew quarkusDev ``` ## API testing ### 🧪Sample dataset
🏫 If you are the corrector Please navigate to the root of this project in a terminal and run the provided `load_data.sh` script. If the script wasn't provided, that was a mistake. Sorry. Please request them to the owner of this repo, or follow the alternate procedure below.
👥 If you are another user or developer You can find a sample dataset at `data/sample-dataset/`. Each JSON file contains a collection. For example, to load the `moves` collection into an existing MongoDB cluster, you may use [MongoDB Shell ("mongosh")](https://www.mongodb.com/docs/mongodb-shell/) to run ```shell script mongoimport --uri=mongodb+srv://:@..mongodb.net/ --collection=moves --file=./data/sample-dataset/moves.json ``` You can then do the same, but changing `moves` for `pokemongs`, and then `trainers`
### 🩺API testing tools You can use an API testing tool such as [Postman](https://www.postman.com/) or [Insomnia](https://insomnia.rest/) to test this app. If you use Postman, you can even import `data/postman_collection.json`, designed to work with the `🧪 Sample dataset`. ### 📱Front end A corresponding [front-end app](https://github.com/draialexis/pokemong_app) comes into play for trying out this API. ⚠️ That only includes the `Move` entity, so [`Postman`](#api-testing-tools) seems like your best option at the moment. ### 🏴‍☠️SwaggerUI Thanks to this project's OpenAPI specs, you can explore the API in a lot of ways. A popular choice is SwaggerUI -- after you run the app, just go to http://localhost:8080/q/swagger-ui and have fun. ⚠️ Swagger or Quarkus or SmallRye adds the field `id` to all request examples, but in fact ***you should NOT include id** when you POST or UPDATE a new document.* The app takes care of it for you. Same thing for the field `species` with `Pokemong` documents. ## Known limitations ### 🔀Types are left at the user's mercy This API doesn't ensure that *a `Move` can't be both effective against a type and weak against that type*. It probably should. But then again, this API doesn't deal with types very much at all anyway. Users are free to create all sorts of weird types within `pokemongs` and `moves`, such as a Pikachu with `GRASS` type effective against `ROCK`, who has an Ember move with `GRASS` type weak against `ROCK` and effective against `FLYING`...