Is there any other way to pass on variables between tasks beside using
process.var_name= value
process.save()
activation.done()
and then accessing it like,
activation.process.var_name
limitation with this approach is I have to declare a var_name member in model. I want to escape from declaring new members in model.
So any approach for passing variables between tasks without using models.
Viewflow is a thin workflow layer on top of django. So your question could be reformulated as "how to pass an object b/w views in django"
Except if your case is about one task executed immediately after another during single HTTP request processing. In that case, you should use just python functions and pass an object as a parameter as usual. On the viewflow layer - it would be a single task. So no inter-task communication would happen.
One of the goals of BPMN workflow automation is to provide an ability to build performance reports based on the workflow data. So, to report friendly saving workflow data in a process mode is mandatory.
In a very few cases, you can consider use redis or memcached to keep workflow data in it. But it's highly unrecommended.
Another rare case is to combine View and Gateway task in a single custom task node. So you can take a view data and pass it to activation.done to make a branching decision without data saving.
Related
When reading about CQRS it is often mentioned that the write model should not depend on any read model (assuming there is one write model and up to N read models). This makes a lot of sense, especially since read models usually only become eventually consistent with the write model. Also, we should be able to change or replace read models without breaking the write model.
However, read models might contain valuable information that is aggregated across many entities of the write model. These aggregations might even contain non-trivial business rules. One can easily imagine a business policy that evaluates a piece of information that a read model possesses, and in reaction to that changes one or many entities via the write model. But where should this policy be located/implemented? Isn't this critical business logic that tightly couples information coming from one particular read model with the write model?
When I want to implement said policy without coupling the write model to the read model, I can imagine the following strategy: Include a materialized view in the write model that gets updated synchronously whenever a relevant part of the involved entities changes (when using DDD, this could be done via domain events). However, this denormalizes the write model, and is effectively a special read model embedded in the write model itself.
I can imagine that DDD purists would say that such a policy should not exist, because it represents a business invariant/rule that encompasses multiple entities (a.k.a. aggregates). I could probably agree in theory, but in practice, I often encounter such requirements anyway.
Finally, my question is simply: How do you deal with requirements that change data in reaction to certain conditions whose evaluation requires a read model?
First, any write model which validates commands is a read model (because at some point validating a command requires a read), albeit one that is optimized for the purpose of validating commands. So I'm not sure where you're seeing that a write model shouldn't depend on a read model.
Second, a domain event is implicitly a command to the consumers of the event: "process/consider/incorporate this event", in which case a write model processor can subscribe to the events arising from a different write model: from the perspective of the subscribing write model, these are just commands.
Having read a lot about the topic and having thought hard about it myself, I attempt to answer my own question.
First, a clarification about the terms used. The write and read models themselves never have any dependency to one another. The corresponding command and query components might have instead. I will therefore call the entirety of the command component and its write model the command side, and the entirety of one particular query component and its read model a query side (of which there might be many).
So consider a command handler that is responsible for evaluating and executing a business policy. It takes a command DTO, validates it, loads part of the write model into memory, and applies changes to it in one atomic transaction. The question specifically was, whether this handler is allowed to query one of the query sides in order to inform its decision about what to do in the write model.
The answer would be a resounding NO. Here's why:
The command side would depend on one particular query side (it doesn't matter if you hide the dependency behind an interface – it is still there), so the query side cannot change independently.
Who actually guarantees that the command handler runs when it has to? The query side is certainly not the one responsible for it, and clients aren't either.
The command request is prolonged by performing a nested query request, which might be detrimental to the performance.
Instead, we can do the following:
Work with domain events raised by the write model, register a domain event handler in the command side that evaluates the policy. This way it is guaranteed that the policy will be executed whenever it has to be.
If the performance allows it, this domain event handler can simply load as much of the write model as it requires to evaluate the business condition. Don't prematurely optimize – maybe the entities are small and can easily be loaded into memory.
If the performance does not allow it, denormalize the write model and maintain the required statistics using domain events. No one says that the write model cannot itself contain query-oriented data. Being a write model simply says that it is a model designed to do writes, and this necessarily must include some means to read as well.
Finally, if applying the policy is not an integral part of the domain logic itself, but rather just a use case, consider putting the responsibility of calling it into a client or another microservice, where it is totally fine to first query one of our query sides, and afterwards calling our command side with the appropriate parameters.
I'm trying to follow DDD principles for my current project. Unfortunately I have to use RFCs due to technical constraints, so no OData and no REST. It's quite a long question I hope it's OK to ask this in Stackoverflow.
In any case, I have an entity class WorkOrder with a list of Operation objects.
I have a WorkOrderRepository class with a SAVE method that only receives a WorkOrder object and is able to save everything (header data, address, etc) in one go. No matter if it's creation, update or deleted. The repository hides the BAPI calls from the rest.
Now I want to implement the logic to add/update/remove Operations to the work order object and I'm not sure even if the names I give to the methods are correct. Maybe they should be insert/edit/delete... I'm quite confused with this since in every place I look they use different names.
But the most important are my 2 specific doubts:
Should I have only 1 RFC that receives all the updates to a WorkOrder entity including header, operations? Or should I create 1 RFC per operation that only handles one operation at a time? Bear in mind that the UI mockup expects that the user can add/delete multiple operations before clicking a SAVE button and RFC has implicit commit, and that to my knowledge a DDD entity should be updated always in one call.
Option 1:
FUNCTION ZWORKORDER_HDR_UPD
IMPORTING
VALUE(I_WORKORDER_ID) TYPE AUFNR
VALUE(I_WORKORDER_HDR_CHG) TYPE ZWORKORDER_HDR_CHG
VALUE(I_WORKORDER_HDR_UPD) TYPE ZWORKORDER_HDR_UPD "X structure for the BAPI
VALUE(I_OPERATIONS_CHG) TYPE ZOPERATIONS_CHG
VALUE(I_OPERATIONS_UPD) TYPE ZOPERATIONS_UPD
VALUE(I_OPERATIONS_DEL) TYPE ZOPERATIONS_DEL
EXPORTING
VALUE(E_ERRORS) TYPE BAPIRET2_T.
Option 2
FUNCTION ZWORKORDER_OPERATION_CRT
IMPORTING
VALUE(I_WORKORDER_ID) TYPE AUFNR
VALUE(I_OPERATION) TYPE ZOPERATION_CHG
EXPORTING
VALUE(E_ERRORS) TYPE BAPIRET2_T.
FUNCTION ZWORKORDER_OPERATION_UPD
IMPORTING
VALUE(I_WORKORDER_ID) TYPE AUFNR
VALUE(I_OPERATION_CHG) TYPE ZOPERATION_CHG
VALUE(I_OPERATION_UPD) TYPE ZOPERATION_UPD
EXPORTING
VALUE(E_ERRORS) TYPE BAPIRET2_T.
FUNCTION ZWORKORDER_OPERATION_DEL
IMPORTING
VALUE(I_WORKORDER_ID) TYPE AUFNR
VALUE(I_OPERATION_ID) TYPE ZOPERATION_ID
EXPORTING
VALUE(E_ERRORS) TYPE BAPIRET2_T.
How should my Workorder methods look to handle this? I'm specially confused with the update method, since I'm not sure if I should first get the existing operation and then update it or let the parent class do it. But maybe my approaches are completely wrong from the root.
Option 1:
workorder->add_operation( i_operation ). "Pass flat structure from RFC? Or first create object?
workorder->update_operation( i_operation_chg
i_operation_upd ).
workorder->delete_operation( i_operation_id ).
Option 2:
workorder->add_operation( ).
operation = workorder->get_operation(i_operation_chg->get_id())
operation->update( i_operation_chg
i_operation_upd ).
operation->delete_operation( i_operation_id ).
The simplest solution is always the best (KISS and YAGNI principles). It doesn't really matter if you create 1 or 3 RFC-enabled function module, so if you can achieve your goal with one function module, then do it with one.
I think you need to have two RFC-enabled function modules. One to validate the maintained operations (do the validations as far as possible), but that should not save anything to the database, and another one called after the user clicks the SAVE button, to save the whole "WorkOrder", including the maintained operations (at this time, there will be the complete validation also).
If you don't need to define an "operation" class for something else, right now, then keep it simple, no need to instantiate an object. Note that you may create an "operation" class with private static methods, and being a friend of the "workorder" class (only this class can use the operation class), just to organize better your code.
PS: although I don't know what is "Domain-Driven Design", I don't see how your question is related to it, because it just looks like simple program design.
We also work with DDD, although luckily not with RFCs but instead Gateway/OData. Since REST by defintion is stateless we always commit in our application service layer.
What we do is have three "DDD" entities
app_Service, domain_service, repository (and also some data containers like aggregates), where the app_service in your case would expose the methods create, update and delete, and possibly also validate.
Then I would write four thin RFCs (crud + validate) that basically passes the data to the app service.
As for being able to handle multiple updates in each save, we always model our OData (your RFC) after the UI requirements, then it's the app_service task to make sense of the data from a system point of view.
We make heavy use of Abap Clean Code (it's even part of our ATC check), and they clearly state that you should have seperate methods, which is also OO best practices.
https://github.com/SAP/styleguides/blob/master/clean-abap/CleanABAP.md#split-methods-instead-of-adding-optional-parameters
A finite state machine can transition into multiple next states. So e.g. from State1, the machine will transition into State2 given input A, or transition into State2 given input B, and so on. Is this possible with django-viewflow?
NB1 I'm aware that it is possible to 'split' workflows. This is an excellent feature but it isn't what I'm looking for. Split workflows provide multiple concurrent workflows, all proceeding individually. I'm looking for a way to choose between different individual workflows, where only one workflow will be chosen and executed, depending on input received.
NB2 It may be possible to achieve what I want using If gateways. Presumably one can store a flag somewhere depending on user input, which the If node then checks and uses to determine which branch to activate. Is this the recommended way of proceeding? If so, are there any specific code examples demonstrating how to do this? Ideally, I don't want to store this sort of workflow information as a flag in my main models - indeed, I don't want to store this ephemeral choice long term at all. So are there other ways of achieving what I want?
One of the advantages of BPMN that it forces to program flow in such a way, that every process decisions are stored permanently and available for further process performance analysis. Skipping a decision store is the antipattern. In the cases where there are a lot of such decisions, In django, it's pretty easy to implement by adding a JSON field to a process model.
But viewflow customize everything. A transition selection could be implemented by overriding activation class done/activate_next methods.
I'm learning DDD and Hexagonal architecture, I think I got the basics. However, there's one thing I'm not sure how to solve: how am I showing data to the user?
So, for example, I got a simple domain with a Worker entity with some functionality (some methods cause the entity to change) and a WorkerRepository so I can persist Workers. I got an application layer with some commands and command bus to manipulate the domain (like creating Workers and updating their work hours, persisting the changes), and an infrastructure layer which has the implementation of the WorkerRepository and a GUI application.
In this application I want to show all workers with some of their data, and be abe to modify them. How do I show the data?
I could give it a reference to the implementation of WorkerRepository.
I think it's not a good solution because this way I could insert new Workers in the repository skipping the command bus. I want all changes going through the command bus.
Okay then, I'd split the WorkerRepository into WorkerQueryRepository and WorkerCommandRepository (as per CQRS), and give reference only to the WorkerQueryRepository. It's still not a good solution because the repo gives back Worker entities which have methods that change them, and how are these changes will be persisted?
Should I create two type of Repositories? One would be used in the domain and application layer, and the other would be used only for providing data to the outside world. The second one wouldn't return full-fledged Worker entities, only WorkerDTOs containing only the data the GUI needs. This way, the GUI has no other way to change Workers, only through the command bus.
Is the third approach the right way? Or am I wrong forcing that the changes must go through the command bus?
Should I create two type of Repositories? One would be used in the domain and application layer, and the other would be used only for providing data to the outside world. The second one wouldn't return full-fledged Worker entities, only WorkerDTOs containing only the data the GUI needs.
That's the CQRS approach; it works pretty well.
Greg Young (2010)
CQRS is simply the creation of two objects where there was previously only one. The separation occurs based upon whether the methods are a command or a query (the same definition that is used by Meyer in Command and Query Separation, a command is any method that mutates state and a query is any method that returns a value).
The current term for the WorkerDTO you propose is "Projection". You'll often have more than one; that is to say, you can have a separate projection for each view of a worker in the GUI. (That has the neat side effect of making the view easier -- it doesn't need to think about the data that it is given, because the data is already formatted usefully).
Another way of thinking of this, is that you have a "write-only" representation (the aggregate) and "read-only" representations (the projections). In both cases, you are reading the current state from the book of record (via the repository), and then using that state to construct the representation you need.
As the read models don't need to be saved, you are probably better off thinking factory, rather than repository, on the read side. (In 2009, Greg Young used "provider", for this same reason.)
Once you've taken the first step of separating the two objects, you can start to address their different use cases independently.
For instance, if you need to scale out read performance, you have the option to replicate the book of record to a bunch of slave copies, and have your projection factory load from the slaves, instead of the master. Or to start exploring whether a different persistence store (key value store, graph database, full text indexer) is more appropriate. Udi Dahan reviews a number of these ideas in CQRS - but different (2015).
"read models don't need to be saved" Is not correct.
It is correct; but it isn't perhaps as clear and specific as it could be.
We don't need to create a durable representation of a read model, because all of the information that describes the variance between instances of the read model has already been captured by our writes.
We will often want to cache the read model (or a representation of it), so that we can amortize the work of creating the read model across many queries. And various trade offs may indicate that the cached representations should be stored durably.
But if a meteor comes along and destroys our cache of read models, we lose a work investment, but we don't lose information.
Background
Udi Dahan suggests a fetching strategy as a useful pattern to use for data access. I agree.
The concept is to make roles explicit. For example I have an Aggregate Root - Customer. I want customer in several parts of my application - a list of customers to select from, a view of the customer's details, and I want a button to deactivate a customer.
It seems Udi would suggest an interface for each of these roles. So I have ICustomerInList with very basic details, ICustomerDetail which includes the latest 10 products purchased, and IDeactivateCustomer which has a method to deactivate the customer. Each interface exposes just enough of my Customer Aggregate Root to get the job done in each situation. My Customer Aggregate Root implements all these interfaces.
Now I want to implement a fetching strategy for each of these roles. Each strategy can load a different amount of data into my Aggregate Root because it will be behind an interface exposing only the bits of information needed.
The general method to implement this part is to ask a Service Locator or some other style of dependency injection. This code will take the interface you are wanting, for example ICustomerInList, and find a fetching strategy to load it (IStrategyForFetching<ICustomerInList>). This strategy is implemented by a class that knows to only load a Customer with the bits of information needed for the ICustomerInList interface.
So far so good.
Question
What you pass to the Service Locator, or the IStrategyForFetching<ICustomerInList>. All of the examples I see are only selecting one object by a known id. This case is easy, the calling code passes this id through and will get back the specific interface.
What if I want to search? Or I want page 2 of the list of customers? Now I want to pass in more terms that the Fetching Strategy needs.
Possible solutions
Some of the examples I've seen use a predicate - an expression that returns true or false if a particular Aggregate Root should be part of the result set. This works fine for conditions but what about getting back the first n customers and no more? Or getting page 2 of the search results? Or how the results are sorted?
My first reaction is to start adding generic parameters to my IStrategyForFetching<ICustomerInList> It now becomes IStrategyForFetching<TAggregateRoot, TStrategyForSelecting, TStrategyForOrdering>. This quickly becomes complex and ugly. It's further complicated by different repositories. Some repositories only supply data when using a particular strategy for selecting, some only certain types of ordering. I would like to have the flexibility to implement general repositories that can take sorting functions along with specialised repositories that only return Aggregate Roots sorted in a particular fashion.
It sounds like I should apply the same pattern used at the start - How do I make roles explicit? Should I implement a strategy for fetching X (Aggregate Root) using the payload Y (search / ordering parameters)?
Edit (2012-03-05)
This is all still valid if I'm not returning the Aggregate Root each time. If each interface is implemented by a different DTO I can still use IStrategyForFetching. This is why this pattern is powerful - what does the fetching and what is returned doesn't have to map in any way to the aggregate root.
I've ended up using IStrategyForFetching<TEntity, TSpecification>. TEntity is the thing I want to get, TSpecification is how I want to get it.
Have you come across CQRS? Udi is a big proponent of it, and its purpose is to solve this exact issue.
The concept in its most basic form is to separate the domain model from querying. This means that the domain model only comes into play when you want to execute a command / commit a transaction. You don't use data from your aggregates & entities to display information on the screen. Instead, you create a separate data access service (or bunch of them) that contain methods that provide the exact data required for each screen. These methods can accept criteria objects as parameters and therefore do searching with whatever criteria you desire.
A quick sequence of how this works:
A screen shows a list of customers that have made orders in the last week.
The UI calls the CustomerQueryService passing a date as criteria.
The CustomerQueryService executes a query that returns only the fields required for this screen, including the aggregate id of each customer.
The user chooses a customer in the list, and chooses perform the 'Make Important Customer' action /command.
The UI sends a MakeImportantCommand to the Command Service (or Application Service in DDD terms) containing the ID of the customer.
The command service fetches the Customer aggregate from the repository using the ID passed in the command, calls the necessary methods and updates the database.
Building your app using the CQRS architecture opens you up to lot of possibilities regarding performance and scalability. You can take this simple example further by creating separate query databases that contain denormalised tables for every view, eventual consistency & event sourcing. There is a lot of videos/examples/blogs about CQRS that I think would really interest you.
I know your question was regarding 'fetching strategy' but I notice that he wrote this article in 2007, and it's likely that he considers CQRS its sucessor.
To summarise my answer:
Don't try and project cut down DTO's from your domain aggregates. Instead, just create separate query services that give you a tailored query for your needs.
Read up on CQRS (if you haven't already).
To add to the response by David Masters, I think all the fetching strategy interfaces are adding needless complexity. Having the Customer AR implement the various interfaces which are modeled after a UI is a needless constraint on the AR class and you will spend far to much effort trying to enforce it. Moreover, it is a brittle solution. What if a view requires data that while related to Customer, does not belong on the customer class? Does one then coerce the customer class and the corresponding ORM mappings to contain that data? Why not just have a separate set of classes for query purposes and be done with it? This allows you to deal with fetching strategies at the place where they belong - in the repository. Furthermore, what value does the fetching strategy interface abstraction really add? It may be an appropriate model of what is happening in the application, it doesn't help in implementing it.