I am developing a smart contract where users need to deposit funds. Something similar to the DeFi projects. I am still new in solidity development and was wondering can you recommend to me an efficient way to store those user addresses? I found a similar question where I understood that storing them in an array is not very efficient, because when I iterate through it, it will be very costly. I saw other recommendations for using Maps, which are good alternatives, however, I don't know whether they will solve my issue.
My idea is to create a smart contract -> store user's addresses who interact/deposit funds -> transfer those addresses to another smart contract that is going to pay interest, etc.
I assume most of the DeFi projects should have resolved that, because they need to store the addresses of their users, so can you give me some tips on how it is done?
You could use the combinations of mapping. Mapping is like an object in javascript or a dictionary in python.
You want to keep track of addresses that deposits. for this, you might still need to keep them in an array for different purposes.
// keep private and then set a getter.
address[] private fundersAddresses;
also set a mapping to keep track of the index to address. for this, I can also set a variable to keep track of index of array
// you could call fundersAddresses.length and it's time complexity most likely O(1) but since I am not 100% sure, I set up a index variable
uint256 private index;
mapping(uint256=>address) private indexToAddress
Now if you write a function to store the funders
function storeFunders() public payable {
// add some logic
fundersAddresses.push(msg.sender);
index++;
// then also store in a mapping
indexToAddress[index]=msg.sender
}
Now if you want to get the i'th item in an array, it will take O(1) time because you will look up the mapping instead of calling array[i]. array[i]'s time complexity is O(n) because ethereum engine would iterate over array till the i'th index.
function getIndexedAddress (uint index) public returns(address){
require(index<fundersAddresses.length,"Index out of bounds")
return indexToAddress[index]
}
This is just a simple example. Based on the needs of your contract you might set up different structure.
If the addresses are final at the deployment, you can use a Merkle tree.
I have a question:
I have a domain : LoanAccount. We have different product of loans but they just different on how to calculate the interest.
for example:
1. Regular Loan calculate interest rate using Annuity Interest Rate formula
2. Vehicle Loan calculate interest rate using Flat Interest Rate formula
3. Temporary Loan calculate interest rate with another formula (i have no idea what is that).
We also could change the rule every year ... we use different formula as well ...
My Question:
Should I put all the logic formula in services ?
Should I make every loan in different domain class ?
or should I make 1 domain class but it has different interest rate calculation methods ?
Any example would be good :)
Thank you in advance !
My suggestion is to separate interest calculating logic from the domain objects.
Hard-wiring the domain object and it's interest calculation is likely to lead you in trouble.
It would be more complicated to change the type of interest calculation for existing account type (which could be expected business request)
When new account type is created you can easily use all the calculation methods you have already implemented for it
It's likely that interest-calculating algorithm will grow in complexity in the future and it may need properties that should not be part of Account domain object, like some business constants, list of transactions etc.
Grails (because Spring) naturally supports to have business logic in services (declarative transactions etc.) rather than in the domain objects. You will always have less pain when going along with the framework than otherwise.
I'm giving up traditional DDD, which is often a massive timewaster, and forces me to do endless mapping: data layer <--> domain layer <--> presentation layer.
For even a small change I must change data models, domain models, presentation models / viewmodels, then the repositories, manager/service classes, and of course the AutoMapper maps, and then test the whole thing! Each call requires calling a layer which calls a layer which calls the underlying code. And I don't get anything in return other than "you might need it in the future". Meh.
My current approach is more pragmatic:
I don't worry about the difference between the "data layer" and "domain layer" any longer, as there's no point - the terms are interchangeable. I let EF do it's thing, and add interfaces and repositories on top when needed.
I've merged my "data" and "domain" projects (into "core", boring name, I know), and I could almost swear that Visual Studio is actually running faster.
I allow EF entities to go up and down the stack, but, I still map them to presentation models / viewmodels as usual.
For simple operations I call repositories directly from controllers, for complex operations I use domain managers/services as usual; the repositories never expose IQueryable.
I define entities/POCOs as partial classes, so I can add domain behavior separately in corresponding partial classes.
The problem: I now use the entities all over the place, so client code can see their navigation properties. And the models are always materialized after they leave a repository, so those navigation properties are often null.
Possible solutions:
1. Live with it. It's ugly but preferable to the problems explained above.
2. For each entity, define an interface which hides the navigation properties; and make client code use the interfaces. But ironically, this means another layer (albeit thin and manageable).
3. What else?
I'm not used to this sort of fast-and-loose programming style, so maybe I'm missing some obvious tricks. Is there anything else I should take into account? I'm sure there are other problems I will encounter soon.
EDIT:
This question is not about DDD. And note that many struggle with a traditional DDD approach -- Seemann appears to arrive at the same conclusion, Rahien speaks about the "Useless Abstraction For The Sake Of Abstraction Anti Pattern", and Evans himself said DDD is only truly useful in 5% of cases. Also see this thread. Some of the comments/answers are predictably about how I'm doing DDD wrong, or how I can tweak my system to do it right. However, I'm not asking about DDD or bashing it for the cases where it is suitable, rather I'd like to know what others are doing in line with the thinking I've described above. It's not as if DDD is a panacea to all design ills, every decade a new process comes out (RUP anyone? XP, Agile, Booch, blah...). DDD is just the shiniest new one, and the most well known and used. But pragmatism should come first as I'm trying to build salable products that ship on time and are easy to maintain. The most useful programming axiom I've learned, by far, is YAGNI. What I want is to change my system to a sort of "DDD-lite", where I get it's strong design/OOP/pattern philosophy, but without the fat.
A typical persistence approach with DDD is to map the domain model directly to corresponding tables. Technically, the mappings are still there (and are usually declared in code), but there is no explicit data model, as pointed out by lazyberezovsky.
The problem with navigation properties can be resolved in a few different ways, regardless of whether you are employing DDD or not. I dislike approach 1 because it makes it more difficult to reason about your code - you never know which properties will be set and which won't. Approach 2 is much better in theory, because it makes it very explicit what that a given query requires and making things explicit is a good practice in general. A similar, but simpler and less brittle approach is to use read-models, which are just objects designed to fulfill requirements of a given query of set of queries. Within the context of DDD, they allow you to decouple behavior rich entities from queries, which are quite often at odds. Now proponents of DRY may scream heresy and come at you with torches and pitchforks, but in practice it is often much easier to maintain a read-model and an entity then to try to coerce entities to fulfill query requirements by way of interfaces or complex mapping strategies. Additionally, the responsibilities of a read-model and a behavior model are quite different, therefore DRY isn't applicable.
This is not to say that DDD is applicable in your scenario. It is often a wise decision to avoid full fledged DDD, especially in scenarios that are mostly CRUD. You are correct to be cautious, a good example of KISS and YAGNI. DDD reaps benefits when your domain consists of complex behavior, not just data. At any rate, the read-model pattern applies.
UPDATE
For implementations that don't employ a read-model, take a look at Fetching Strategy Design where the notion of a fetching strategy allows the specification of exactly what is needed from the database which mitigates issues with navigational properties. The material referenced in the linked post is also of interest. Overall, this attempts to avoid the a layer of indirection present in other approaches. However, in my opinion, using the proposed fetching strategy is more complex than using a read-model while the net result is the same.
Some thoughts about this point:
... the repositories never expose IQueryable ... the models are always
materialized after they leave a repository ...
Your question is tagged with "asp.net-mvc", so you have a web application in mind. 90% or more of all requests will be GET requests that are supposed to fetch some data from the database and show those data in a web view. How often are those needed data really entities rather than only bags of properties (a selection of properties of an entity type or perhaps composed of properties from multiple entities)?
Say, your application has 100 views. Only a minority of these will show complete entities:
50 of them are list views that show selected data (a customer with ID and address, but without the customer's contact person, phone number and sales volume)
20 of them contain autocomplete text boxes to select a reference (the customer for an order, but only the customer's name and city is shown in the autocomplete list, not the rest of the address nor contact person, phone number and sales volume and only the first 5 hits are displayed)
1 is an edit view for a customer that shows everything, but not the sales volume
1 is a details view for a customer with his last five orders
1 is a details view for an order including order items including product of each item but without the product's supplier name
1 is the same view but specialized for the purchasing department that wants to see the supplier for each item and item's product with average supplier's lead time for the last three months.
1 is a view for the service department that shows the order with only the order items of product category "repair service"
1 view for the Human Resources department shows employees including a photo stored as a big blob
1 view for personnel planning department shows a short version of the employee without photo
etc., etc.
As a UI programmer I would have all kinds of data requirements to render a view with the examples above:
I need only a selection of properties
I need even different selections of the same entity's properties for different views
I need an order including all items but without a reference to a product
I need an order including all items (but not all properties of the items) and including a reference to a product and to a supplier (but not all supplier's properties)
I need an order including only a filtered list of order items
I need a customer including the last five orders, not all 3000 orders he ever had
I need an employee but please without the big blob image
etc., etc.
How to fulfill these requirements as a data access/repository/service developer?
I only provide a handful of methods and materialize entities: load order header, load order header with items, load order header with items and product, load order header with items and product and supplier, load customer header (throw 15 of the 20 properties away, dear UI developer, if you only need five properties), load customer header with all 3000 orders (throw 2995 away, dear UI developer, if you only need five), etc., etc. I return interfaces from the repositories that hide not loaded navigation properties.
I care about every detail that the UI needs: I create repository/service methods like GetFiveCustomerPropertiesForAutoComplete, GetCustomerWithLastFiveOrders, etc. etc. I return interfaces from the repositories that hide the properties (also scalar) I haven't loaded. Or I return "DTOs" that contain the requested properties. I change the repository/services and create new DTOs every day when a UI developer calls with a data requirement for the next view.
I return IQueryable<TEntity> from the repositories and tell the UI developer "create the LINQ query yourself to fetch the data you need for your views". (Next morning the DBA is complaining about hundreds of terrible performing database queries.)
I return "prepared" IQueryable<TEntity>s from the repositories/services that cover - for example - security concerns like applying Where clauses for the user's access rights or append a Where clause for a search term or apply a NoTracking option to the query. I tell the UI developer: "You are allowed to extend the query with a) projections (Select), b) paging (Take and Skip) and perhaps c) sorting (OrderBy) because I consider those three query parts as UI concerns. All other query requirements (filtering, joining, grouping, etc.) have to be implemented in the repository/service layer and are forbidden in the UI layer." The most important piece here are projections that materialize ViewModels directly through the LINQ/SQL query without intermediate mapping layer and without the overhead to load more than the needed columns/properties.
These are only some thoughts. Every approach has its benefits and downsides. Working in small teams where at least one or a few developers have an overview what is happening in both the repository/service and the UI/"projection" layer the last option works fine for me in my experience although it doesn't always work with the strict rules decribed (for example, the filter by product category for included order items of an order requires to apply a Where clause inside of the projection, i.e. in the UI layer). For POST requests and data modifications I would use DTOs that send to data collected from a view back to a service to be processed there.
For stricter separation of "query layer" and UI layer I would probably prefer something close to the second option, maybe not with an interface/DTO for every UI requirement, but somehow reduced to a set of DTOs for the most common requirements (with the price of a little overhead of sometimes unnecessarily loaded properties). However, I expect that to be more work than the last option due to the larger amount of necessary repository/service methods, the additional maintenance of (perhaps many) DTOs and the intermediate mapping between DTOs and ViewModels.
Personally I am concerned about materializing full entities, especially complex object graphs, when I don't need them 90% of the time. But my concern is not verified by extensive performance measurements proving that this approach is really a problem for a "normal" application that doesn't have special high performance needs.
How can anyone give you sound advice when we have no clue as to what it is you are building? In the grand scheme of things, you might be building the wrong solution (not saying you are). So do realize all we can relate to is technical design issues and similar past experiences.
Many people face your problem, indeed. The mapping is loose coupling tax in the land of static typing. Maybe a more dynamic language could solve some of your pain. Or maybe you might find virtue in automating more (DSL, MDA). You could also switch to client server instead.
Interfaces are not layers, rather abstractions. Use them wisely.
Personally, I'd never take these shortcuts. Been bitten too many times trying to skip steps. Logic starts popping up in odd places. If I have a data driven app to develop simple datasets come to mind, EF as well. But I don't call the objects aggregate or entity in the DDD sense, just entity in the ERD sense. Transactionscript might be a better fit than doing the partial method sprinkeling. As for read model objects, these are not layers of indirection.
Overall, I get the feeling, and it is just that, you're making a mess of things because you fight the mapping friction by taking on a dependency on objects that don't reveal the required shape (navigation properties that are null) thereby causing problems in a different area.
I'll just try to be short - we went for the method 2 - ie, add layer of interfaces that you use on the client. You can have EF generate them for you, just a little tweak of the .tt templates.
Yes, it creates (yet) another layer, but it's logic-free and adds no complexity. Of course, if your client needs to deserialize entities, you have to add (yet) another layer that will handle deserialization and reference both the entities definitions and the interfaces that he'll return to the client. But it's also thin, so we learned to live with it, because it turned out to work just fine, and the client really stays clean...
The problem: I now use the entities all over the place, so client code
can see their navigation properties.
I don't quite get why this is a problem and how it's related to EF entities in particular. By client code do you mean presentation layer code or any code consuming your entities ?
For UI code a simple solution is to define ViewModels that just don't expose these navigation properties (or only expose a few of them depending on the object graph depth your GUIs need).
For other code it's only normal to be able to see the navigation properties of entities. They are public for a reason. You can end up breaking the Law of Demeter if you abuse them, but it's a matter of developer discipline not to fall into that trap.
An entity contains its own contract - all code that has access to the entity is supposed to be able to use any part of this contract. If you feel like your entities are exposing too much and that you need to put interfaces on top of them to restrain access to certain parts, maybe it's just a different entity.
I don't worry about the difference between the "data layer" and "domain layer" any longer, as there's no point - the terms are
interchangeable. I let EF do it's thing, and add interfaces and
repositories on top when needed.
I've merged my "data" and "domain" projects (into "core", boring name, I know), and I could almost swear that Visual Studio is
actually running faster.
I allow EF entities to go up and down the stack, but, I still map them to presentation models / viewmodels as usual.
For simple operations I call repositories directly from controllers, for complex operations I use domain managers/services as
usual; the repositories never expose IQueryable.
I define entities/POCOs as partial classes, so I can add domain behavior separately in corresponding partial classes.
None of these things seems to be fundamentally anti-DDD to me, except data/domain separation.
Especially if you do database-first EF -DDD is clearly a domain-centric approach and you shouldn't define your tables before defining your entities. It's also not clear whether some of your domain entities talk to the database or EF directly (not DDD - and more generally, layered-architecture - compliant) or you systematically have data access objects in between (DDD compliant).
I am a complete newbie to both caching, nhibernate, and everything involving the two, so this question may be excessively stupid.
I have certain instances of objects that are used by multiple other objects in my system. So for instance..
class Template {
// lots of data
}
class One {
IList<Template> Templates { get; set; }
}
class Two {
IList<Template> Templates { get; set; }
}
class Three {
IList<Template> Templates { get; set; }
}
Now, then, certain instances of Template are going to be used very, very frequently. (think like, every 20 seconds) and it includes a lot of things that need to be mathematically computed.
My question is basically which approach will yield the least stress on my database/server.
Am I best to just leave everything to Level 2 Caching in nHibernate? Or am I wiser to retrieve the Template object and store it in a static variable when my ASP.NET application starts up, and refresh this variable if it changes?
I've looked at some of the other similar questions around SO but I am still very much in the dark. Most of the documentation on caching assumes a good deal of knowledge on the subject, so I'm having a difficult time discerning what the optimal process is.
once every 20 second doesn't really sound very stressful. You need to weight the need for updated data vs the stress you can live with on your database.
2nd level cache won't necessarily help you in this case, since you use collections of objects. In order to know which object it needs, it still need to query the database, and if you do that it might even fetch the data anyway (unless it's a lot of raw data in the entities).
You basically have three different options:
1st level cache
For each connection/session that you make, NHibernate will always cache the unique entity that it has fetched. Every time you try to get a single entitity based in it's identifier (primary key), it will first check it's first level cache. This does not apply to collections of entities though, unless you can force NHibernate to only get "identifiers" for the collection and the get them one by one (usually very slow)
2nd level cache
This cache will available for each and every connection/session, and try to fetch the data from cache before it hits the database. Same rules apply as for the 1st level cache, that you can't get collections to an entity without querying the database unless it has already been loaded.
custom cache
You can always take care of caching your self, however, that way you need to model your classes accordingly (having Template objects stored, and the collections only keep track of the identifier instead of Template objects). If you refactor like this, 2nd and 1st level cache would still be equally useful though.
I will give you an example that shows you what I'm talking about:
if One contains templates with identifier [1,2,3,4]
Two contains templates with identifier [2,3]
Three contains templates with identifier [3,4,5]
In order for NHibernate to know that One needs templates 1,2,3,4, it needs to query the database. 1,2,3,4 will be cached individually here.
In order to actually know that Two needs entity 2 and 3, it still needs to query the database. It can't possibly know that 2,3 is also part of the collection in Two. Si it won't fetch them from cache, because it will select Template objects that belongs to class Two, hence full data. That is why caching won't help you here.
I think you need to give more details on what kind of data it is that you will be processing, and how it will be stored and updated in order to get an answer that is useful.
Static variables would be the less stress on your server, however that imposes some restrictions, specifically, it would be much harder to scale (web garden/farm), if you don't need to scale, that's the option you're looking for
I am reading http://en.wikipedia.org/wiki/Domain-driven_design right now, and I just need 2 quick examples so I understand what 'value objects' and 'services' are in the context of DDD.
Value Objects: An object that describes a characteristic of a thing. Value Objects have no conceptual identity. They are typically read-only objects and may be shared using the Flyweight design pattern.
Services: When an operation does not conceptually belong to any object. Following the natural contours of the problem, you can implement these operations in services. The Service concept is called "Pure Fabrication" in GRASP.
Value objexts: can someone give me a simple example this please?
Services: so if it isn't an object/entity, nor belong to repository/factories then its a service? I don't understand this.
The archetypical example of a Value Object is Money. It's very conceivable that if you build an international e-commerce application, you will want to encapsulate the concept of 'money' into a class. This will allow you to perform operations on monetary values - not only basic addition, subtraction and so forth, but possibly also currency conversions between USD and, say, Euro.
Such a Money object has no inherent identity - it contains the values you put into it, and when you dispose of it, it's gone. Additionally, two Money objects containing 10 USD are considered identical even if they are separate object instances.
Other examples of Value Objects are measurements such as length, which might contain a value and a unit, such as 9.87 km or 3 feet. Again, besides simply containing the data, such a type will likely offer conversion methods to other measurements and so forth.
Services, on the other hand, are types that performs an important Domain operation, but doesn't really fit well into the other, more 'noun'-based concepts of the Domain. You should strive to have as few Services as possible, but sometimes, a Service is the best way of encapsulating an important Domain Concept.
You can read more about Value Objects, Services and much more in the excellent book Domain-Driven Design, which I can only recommend.
Value Objects: a typical example is an address. Equality is based on the values of the object, hence the name, and not on identity. That means that for instance 2 Person objects have the same address if the values of their Address objects are equal, even if the Address objects are 2 completely different objects in memory or have a different primary key in the database.
Services: offer actions that do not necessarily belong to a specific domain object but do act upon domain objects. As an example, I'm thinking of a service that sends e-mail notifications in an online shop when the price of a product drops below a certain price.
InfoQ has a free book on DDD (a summary of Eric Evan's book): http://www.infoq.com/minibooks/domain-driven-design-quickly
This is a great example of how to identify Value Objects vs Entities. My other post also gives another example.