Every example of a grapqhl schema I found consisted of just a couple of ObjectTypes which all made sense in the global context of the schema like "Person", "Dog", "Animal".
In real life scenarios there are way more types. More importantly there might be types that make sense only within a group of other types but are called similarly e.g StatisticsType. StatisticsType held by a field inside a GroupType would be different than this held inside PresentationType. We could call them GroupStatisticsType and PresentationStatisticsType. However, following this approach I end up with types with very very long names.
As far as I know all types must be named uniquely within the schema and end up thrown in so to say one scope. Is there some design pattern, best practice or am I missing something that help to design a decent schema?
If you have any example of a schema with numerous types (20+ is something) might be helpful.
Related
There is a pattern or term that is used to avoid codes like
myObject.fieldA.fieldB.fieldC
something like this. I forgot what this term is called. Can anyone let me know about it?
It violates the Law of Demeter, which states that code should only access its own local variables, parameters, and instance members.
It could be a case of of feature envy, where a class calls a lot of getters or accesses a lot of data from another class.
If these are really fields, they are poorly encapsulated (i.e., not behind a function), and any change to these fields forces you to modify all code that's using them.
Testing such code becomes hard, as you will have to mock not only fieldA, but also that's fieldB, and in turn that's fieldC.
I think you are trying to create a new object and add certain properties to that object. If that is the case then it's Builder design patten where you seperate the construction and representation.
If you are trying to call a certain field with the above shown code then your design is very poor. An object should store only it's own properties.
I'm not quite sure the wording I should be searching for on this.
I have a GraphQL schema which wraps a group of services using graphql-link-schema to perform the data resolution on the client side. The schema is intended to be built against a separate reference schema. How can I programmatically validate that my implementation matches the reference?
For bonus points- is it possible to determine whether a schema is a superset of another?
Thanks in advance (:
It's an interesting use case, but it's a bit unclear how validation like that would work. What causes validation to fail? Any differences between the two schemas? Extra types? Extra fields on existing types? Differences in return types? Differences in arguments or argument types?
Depending on your answer to the above questions, though, you may be able to cobble together your own validation function using the utility functions available here. Outside the main findBreakingChanges function, some of the utility functions available in that module:
findRemovedTypes
findTypesThatChangedKind
findFieldsThatChangedTypeOnObjectOrInterfaceTypes
findFieldsThatChangedTypeOnInputObjectTypes
findTypesRemovedFromUnions
findValuesRemovedFromEnums
findArgChanges
findInterfacesRemovedFromObjectTypes
If you have a reference or base schema available, though, rather than validating against it, you might also consider extending it when building the second schema. In doing so, you would effectively guarantee that the second schema matches the first except in whatever ways you intentionally deviate from it (by extending existing types, etc.). You could use extendSchema for relatively simply changes, or something like graphql-tool's mergeSchemas for more complicated changes.
I have developed a system where various classes have attributes consisting of a custom formula. The formula can contain special tokens which refer to different types of object. For example an object of class FruitSalad may have the following attribute;
$contents = "[A12] + [B76]";
In somewhat abstract terms, this means "add apple 12 to banana 76". It can also get significantly more complex than that with as many as 15 or 20 references to other objects involved in one formula.
I have a trait which passes formulae such as this and each time it finds a reference to a model (i.e. "[A12]") it gets it from the database with A::find(12) and adds it to an array of component objects which can be used for other processes later on in the request.
So, in essence, it's a relationship. But instead of a pivot table to describe the relationship, there is a formula on the parent model which can include references to child models.
This is all working. Yay! But it's really inefficient because there are so many tiny queries to get single models as formulae are parsed. One request may quite easily result in hundreds of queries. Oops.
I see two potential options;
1. Get all my apples and bananas from the database at the start of the request and get them from an in-memory store instead of from the database when parsing a formula (is this the repository pattern??).
2. Create a custom relation type (something like hasManyFromFormula) which makes eager loading work so that the parsing becomes much simpler because the relevant apples and bananas would already be loaded into the parent model.
Is there a precedent for this? As for why I am doing it like this, it would a bit tough to explain in brief but suffice to say it is to support a highly configurable data retrieval system which supports as-yet unknown input data configurations.
Help!
Thanks,
Geoff
Am not completely sure if it is the best solution, but in the end I created a new directory class for basic components and then set it up in the app service provider as a singleton. The constructor for the directory class loaded all models of several relevant classes and made them available as collections throughout the app.
In our new project we decided to use hexagonal architecture. We decided to use repository pattern to gain more data access abstraction. We are using command bus pattern as service layer.
In our dashboard page we need a lot of data and because of that we should use 3 level many to many relations (user -> projects -> skills -> review) and also skills should be active(status=1).
The problem rises here, where should i put this?
$userRepository->getDashboardData($userId).
2.$userRepository->getUser($userId)->withProjects()->withActiveSkills()->withReviews();
3.$user = $userRepository->getById();
$projects = $projectRepository->getByUserId($user->id);
$skills = $skillRepository->getActiveSkillsByProjectsIds($projectIds);
In this case, I couldn't find the benefits of repository pattern except coding to interface which can be achived with model interfac.
I think solution 3 is prefect but it adds a lot of work.
You have to decide (for example) from an object-oriented perspective if a "User" returned is one that has a collection of skills within it. If so, your returned user will already have those objects.
In the case of using regular objects, try to avoid child entities unless it makes good sense. Like, for example.. The 'User' entity is responsible for ensuring that the child entities play by the business rules. Prefer to use a different repository to select the other types of entities based on whatever other criteria.
Talking about a "relationship" in this way makes me feel like you're using ActiveRecord because otherwise they'd just be child objects. The "relationship" exists in the relational database. It only creeps into your objects if you're mixing database record / object like with AR.
In the case of using ActiveRecord objects, you might consider having specific methods on the repository to load the correctly configured member objects. $members->allIncludingSkills() or something perhaps. This is because you have to solve for N+1 when returning multiple entities. Then, you need to use eager-loading for the result set and you don't want to use the same eager loading configuration for every request.. Therefore, you need a way to delineate configurations per request.. One way to do this is to call different methods on the repository for different requests.
However, for me.. I'd prefer not to have a bunch of objects with just.. infinite reach.. For example.. You can have a $member->posts[0]->author->posts[0]->author->posts[0]->author->posts[0].
I prefer to keep things as 'flat' as possible.
$member = $members->withId($id);
$posts = $posts->writtenBy($member->id);
Or something like that. (just typing off the top of my head).
Nobody likes tons of nested arrays and ActiveRecord can be abused to the point where its objects are essentially arrays with methods and the potential for infinite nesting. So, while it can be a convenient way to work with data. I would work to prevent abusing relationships as a concept and keep your structures as flat as possible.
It's not only very possible to code without ORM 'relationship' functionality.. It's often easier.. You can tell that this functionality adds a ton of trouble because of just how many features the ORM has to provide in order to try to mitigate the pain.
And really, what's the point? It just keeps you from having to use the ID of a specific Member to do the lookup? Maybe it's easier to loop over a ton of different things I guess?
Repositories are really only particularly useful in the ActiveRecord case if you want to be able to test your code in isolation. Otherwise, you can create scopes and whatnot using Laravel's built-in functionality to prevent the need for redundant (and consequently brittle) query logic everywhere.
It's also perfectly reasonable to create models that exist SPECIFICALLY for the UI. You can have more than one ActiveRecord model that uses the same database table, for example, that you use just for a specific user-interface use-case. Dashboard for example. If you have a new use-case.. You just create a new model.
This, to me.. Is core to designing systems. Asking ourselves.. Ok, when we have a new use-case what will we have to do? If the answer is, sure our architecture is such that we just do this and this and we don't really have to mess with the rest.. then great! Otherwise, the answer is probably more like.. I have no idea.. I guess modify everything and hope it works.
There's many ways to approach this stuff. But, I would propose to avoid using a lot of complex tooling in exchange for simpler approaches / solutions. Repository is a great way to abstract away data persistence to allow for testing in isolation. If you want to test in isolation, use it. But, I'm not sure that I'm sold much on how ORM relationships work with an object model.
For example, do we have some massive Member object that contains the following?
All comments ever left by that member
All skills the member has
All recommendations that the member has made
All friend invites the member has sent
All friends that the member has established
I don't like the idea of these massive objects that are designed to just be containers for absolutely everything. I prefer to break objects into bits that are specifically designed for use-cases.
But, I'm rambling. In short..
Don't abuse ORM relationship functionality.
It's better to have multiple small objects that are specifically designed for a use-case than a few large ones that do everything.
Just my 2 cents.
We are using the aws-sdk for ruby, specifically AWS::Record::Base.
For various reasons we need to put records of various objects within the same domain in sdb.
The approach we thought we'd use here would be to add an attribute to each object that contains the object name and then include that in the where clause of finder methods when obtaining objects from sdb.
My questions to readers are:
what are your thoughts on this approach?
how would this be best implemented tidily? How is it best to add a default attribute included in an object without defining it explicitly in each model? Is overriding find or where in the finder methods sufficient to ensure that obtaining objects from sdb includes the clauses considering the new default attribute?
Thoughts appreciated.
It really depends on your problem, but I find it slightly distasteful. Variant records are fine and dandy, but when you start out with apples and dinosaurs and they have no common attributes, this approach has no benefit that I know of [aside from conserving your (seemingly pointless) quota of 250 SimpleDB domains]. If your records have something in common, then I can see where this approach might be useful, but someone scarred like me by legacy systems with variant records in Btrieve (achieved through C unions) has a hardwired antipathy toward this approach.
The cleanest approach I can think of is to have your models share a common parent through inheritance. The parent could then know of the child types, and implement the query appropriately. However, this design is definitely not SOLID and violates the Law of Demeter.