- #JSON TEST DATA GENERATOR MONGODB DRIVER#
- #JSON TEST DATA GENERATOR MONGODB CODE#
- #JSON TEST DATA GENERATOR MONGODB ZIP#
Uni updated = ReactivePerson.update("name", "Mortal"). Uni deleteCount = lete("status", Status.Alive) ĭeleteCount = leteAll() Uni countAlive = unt("status", Status.Alive) Uni> livingPersons = ReactivePerson.list("status", Status.Alive) PersonById = optional.map(o -> o.orElseThrow(() -> new NotFoundException())) Uni> optional = ReactivePerson.findByIdOptional(personId)
Uni personById = ReactivePerson.findById(personId) Uni> allPersons = ReactivePerson.listAll() and accessible when uni1 will be resolved persist it: if you keep the default ObjectId ID field, it will be populated by the MongoDB driver, ReactivePerson person = new ReactivePerson() Long updated = personRepository.update("name", "Mortal").where("status", Status.Alive) lete("status", Status.Alive) īoolean deleted = leteById(personId) Long countAlive = unt("status", Status.Alive)
#JSON TEST DATA GENERATOR MONGODB CODE#
It was derived from JavaScript, but many modern programming languages include code to generate and parse JSON-format.
List livingPersons = personRepository.list("status", Status.Alive) JSON is a language-independent data format. Optional optional = personRepository.findByIdOptional(personId)
Person = personRepository.findById(personId) List allPersons = personRepository.listAll() Long updated = Person.update("name", "Mortal").where("status", Status.Alive) set the name of all living persons to 'Mortal' Long countAlive = unt("status", Status.Alive) īoolean deleted = leteById(personId) List livingPersons = Person.list("status", Status.Alive) Person = optional.orElseThrow(() -> new NotFoundException()) Optional optional = Person.findByIdOptional(personId) finding a specific person by ID via an Optional
#JSON TEST DATA GENERATOR MONGODB ZIP#
ObjectId personId = new ObjectId(idAsString) drag a folder with files, you need to zip it and upload in Test Data section and use it like so. here we build a new ObjectId, but you can also retrieve it from the existing entity after being persisted Your must call update() in order to send your entity modifications to MongoDB
#JSON TEST DATA GENERATOR MONGODB DRIVER#
persist it: if you keep the default ObjectId ID field, it will be populated by the MongoDB driver That’s when i noticed the difference between these documents and those created by = LocalDate.of(1910, Month.FEBRUARY, 1) After a few minutes of wondering how I could have introduced a bug in the code I went back to the documents I had manually created to find these were returned by id without issue. Back to the Api, I tried a quick test to see if I could locate a document by Id and, boom, no result. I went my 1000 documents and now had 1003 to work with. In this case, I found the import option in the Compass client was fine for the job. I can save this out to a json file and then use whatever MongoDb tool I choose to import the documents. Very quickly I can a mapping for my client class and generate 1000 documents: I want to add 1000 documents in and do so in the quickest way, so I turn to – a mock data generator site. Set up a SwaggerUI for the web api and we’re good to spin up the api and try adding a few documents, getting all, by id… etc.īut after trying it out with 3 documents it gets a bit boring. Using my MongoDb nuget package, I can quickly knock up a web api prototype that provides basic Get/ Get by Id/ Post/ Put and Delete operations on a Mongo Db using the following class as an example: // from nuget library When creating the document in dotnet code, developers will usually map this uid to a System.Guid. NoSql/ Document-based databases often prefer to rely on object identities in the form a uid, unlike Sql Server which will often use a sequential number seed.
It turned out a little more complex than I first anticipated. There are plenty of sources of mock data creation and I don’t intend to go into any review of these in this post, Instead, I wanted to cover off a little quirk I noticed when using Mongo Db as my data engine and creating mock data with guids as they’re Id. When dealing with smaller scale projects in which the creation of the data itself is also new, being able to quickly create enough test data to make any prototype/ demo/ early testing of any worth is of massive value. Be the focus on UI or the need for extensive e2e test coverage, having access to streams of data is invaluable. When consulting for large firms, where the existence of copious amounts of test data is established, it makes it very easy to realise the potential of any prototype or greenfield work very quickly.
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