Schema Name capitalization for custom entities/fields in Dynamics CRM 365 - dynamics-crm

MS recommends Pascal-case for the Schema Names, but then they don't obey the rule themselves. The custom entities and the primary fields are created by default with all-lowercase schema names, while the custom fields are Pascal-case by default. Even more, the built-in statuscode and statecode for the custom entities are all-lowercase.
Questions:
are the schema names important down the road? There are quite a lot of external integrations coming for our CRM (C#, likely early-bound). For now I'm trying to keep it as clean as possible just to avoid potential future issues, but some colleagues think I'm over-worried and it's not worth the time.
do you know any good reason why MS doesn't obey their own rules in some cases?

I reject the pascal case advice. In my opinion, scheme name should be all lower case. This way it matches to the logical name. It prevents a lot of confusion and mistyped names, in the future.

As you decided to use C# Early bound classes, you will be using crmsvcutil or some Early Bound Generator which will pull all the schema name as it is from CRM Metadata.
If the schema name changes (like on drop & recreate with different datatype) the next class file will fetch it & build error will notify you.
By seeing the revisions nothing is going to change in near future & MS not even worrying about the rule-break.
To mention, next generation web api expects Schema Name in certain things like Navigation Properties whereas if you are going with Late binding, flat system converted lowercase Name (Logical Name) will be used.

Related

DDD - Life cycle of Value Objects: Validation & Persistence

I understand what is VO (immutable, no-identity, ...). But I have several questions that are from discussion with my co-workers.
A) Validation - How precise should it be?
What types of validation should I put into VO? Only basic ones or all? Good example of VO is Email with some regexp validation. I've seen it many times. I've worked on several big/medium-size applications and regexp wasn't good enough because:
system-A: Domain name of email was validated, eg test#gmali.com in invalid email because domain gmali.com doesn't exist
system-B: We had list (service) of banned domains of "temporary email services" because we wanted to avoid of "fake accounts"
I cannot imagine to put validation of this kind into VO, because it require network communication and VO will be complicated (and slow).
B) Validation: Names, Titles, Strings... is length part of VO?
Programmer can use old-good string data type. I can image VO as NotEmptyString, but is it good approach to create value objects as:
FirstName (non-empty string with length limitation)
Surname (non-empty string with length limitation)
StreetName(non-empty string with length limitation)
There is no difference between FirstName and Surname, because in application we cannot find out if some one swap first name and surname in form. Robert can be first name and it can be also surname...
class Person
{
private string $firstName; // no VO for firstName
// or
private FirstName $firstName; // VO just for firstName & length validation
// or
private NotEmptyString $firstName; // VO - no max length validation
// or
private StringLength50 $firstName; // same as FirstName, different name for sharing
}
Which approach is the best and why?
C) Copy of VO: Providing "Type-Safety" for entity arguments?
This point is similar to previous one.
Is it good practice to create classes like this:
class Surname extends Name
{
}
class FirstName extends Name
{
}
just "to alias" VO?
D) Persistence: Reading stored VO
This point is closely related to first one: A) Validation - How precise should it be?. I strongly believe what is stored in my "storage engine" (DB) is valid - no questions. I don't see any reason why I should validate VO again when everything was validated during "persistence step". Even complex/poorly-written regexp could be performance killer - listing of N-hundreds on user emails.
I'm lost here... should I validate only basic stuff and use same VO during persist and read or should I have 2 separate VO for these cases?
E) Persistence/Admin: Something like "god" in the system.
From my experience: In real-word system user with higher privileges can sometimes by-pass validation rules and this is again related to point A) Example:
you (as regular user of system) can make online reservation up to 30 days from today
admin user can make online reservation to any date
Should I use only Date / FutureDate VO or what?
F) Persistence: Mapping to DB data-types
Is it good practice to closely bound VO and DB (storage engine) data types?
If FirstName can have only 50 chars should it be defined / mapped to VAR_CHAR(50)?
Thanks.
A) Validation - How precise should it be?
It's not about precision, it's about invariants & responsibility. A value object (VO) can't possibly have authority on whether or not an email address exists. That's a fact that varies and can't be controlled by the VO. Even if you had code such as the following:
var emailAddress = EmailAddress.of('some#email.com', emailValidityChecker);
The address may not exist a few minutes later, the user may have lost his account password forever, etc.
So what does EmailAddress should represent? It should ensure the "format" of the address makes it a usable & useful address in your domain.
For instance, in a system responsible for delivering tax reminders, I had a limitation where I had to use Exchange and it couldn't support certain email formats like addresses with "leading, trailing or consecutive dots in the local-part" (took the exact comment I had put).
Even though that's a technical concern in theory, that means our system couldn't ingest such email addresses and they were completely useless to us so the ValidEmailAddress VO did not accept those to fail early (otherwise it was generating false positives down the chain).
B) Validation: Names, Titles, Strings... is length part of VO?
I would, even though such lengths might sometimes feel somewhat arbitrary or infrastructure-driven. However, I think it's safe to say that a name with 500 characters is certainly a mistake. Furthermore, validating with reasonable ranges can protect against attacks (e.g. a 1GB name???). Some may argue that it's purely an infrastructure concern and would put the validation at another layer, but I disagree and I think the distinction is unhelpful.
The length rules aren't always arbitrary, for instance a TweetMessage that can't be longer than 280 chars, that's a domain rule.
Does that mean you must have a VO for every possible strings in the system? Honestly I pushed backed being scared to overuse VOs and edge towards a VO-obsession rather than primitive obsession, but in almost every scenario I wished I just took the time to wrap that damn string.
Be pragmatic, but I see more harm in underusing than overusing VOs.
C) Copy of VO: Providing "Type-Safety" for entity arguments?
I most likely wouldn't extend Name just for the sake of reuse here. There's most likely no place where you'd want to interchange a Surename with a FirstName so polymorphism is pretty useless too. However, the explicit types may help to interchange "surename" for "first name" and vice-versa.
Independently of whether or not the explicit types are useful, something more useful here might be to aggregate both under a FullName VO that creates increases cohesion.
Please beware that overly restrictive name policies has been a huge pain point for many international systems though...
D) Persistence: Reading stored VO
Persisted data lives on the "safe" side and should NOT be validated again when loaded into memory. You should be able to circumvent the validation path when hydrating our VOs.
E) Persistence/Admin: Something like "god" in the system.
VOs are great to enforce their "invariants". An invariant by definition doesn't vary given the context. That's actually something many misunderstood when saying "always-valid" approach doesn't work.
That said, even system admins most likely can't make new reservations in the past, so perhaps that can be an invariant of a ReservationDate. Ultimately you would most likely extract the other rules in the context to which they belong.
F) Persistence: Mapping to DB data-types
I think it's more important to reflect the DB limitation in the domain than inversely, reflect the domain limitation in the DB. If your DB only accepts 50 chars and you exceed that some systems will just crash with a very cryptic error message not even telling you which column overflowed. Validating in the domain would help debugging much more quickly. However, you do not necessarily have to match the domain rule in the DB.
DDD, like any other design, is a matter of drawing lines and making abstract rules. Some rules may be very strict, while others may be fluent to some extent. The important thing is to keep consistency as much as possible, rather than striving to build the ultimate-undefeatable domain.
Validation - How precise should it be?
"Heavy" validations should not occur inside VO. A VO is not very
different in its nature from the primitive it encapsulates, therefore
validations should be independent of external factors. Please recall that
even primitives such as byte may be internally validated: an exception (sometimes even a compile error) occurs when a byte variable is assigned with value greater than 255.
Advanced validations, on the other hand, belong to the flow part (use-case / interactor / command-handler), since they involve operations beyond the scope of the VO's primitive, such as querying databases or invoking APIs. You can, for example, query a list of valid email providers from database, check if VO's provider contained in list, and throw exception if not. This is simply flow.
You may, of course, decide to have an in-memory static list of email providers, in which case it will be perfectly valid to keep it inside VO and check its primitive against that list. No need to communicate with external world, everything is "local". Would it be scalable? probably not. But it follows a DDD rule stating that VO should not "speak" with external resources.
Validation: Names, Titles, Strings... is length part of VO?
VOs, much like other DDD concepts, should "speak out loud" your business domain, meaning that they should express business semantics. This is why FirstName, Surname and StreetName are good names, while NotEmptyString is less preferable due to the fact it communicates technical rather than business details.
If, for example, your business states that customers with a more-than-50-characters-length name are to be addressed differently than customers with a less-than-50-characters-length name, then you probably should have two VOs, e.g. LongFirstName, ShortFirstName.
True, several VOs may require exactly the same validations, e.g. both StreetName and CityName must start with a capital and length cannot exceed 100. Does this mean we have to make great effort to avoid duplications in the name of "reusability"? I would say no, especially if avoiding duplications means having a single VO named CapitalHeadStringUpTo100Characters. Such name conveys no business purpose. Moreover, if CityName suddenly requires additional validations, breaking CapitalHeadStringUpTo100Characters into two VOs may require much work.
Copy of VO: Providing "Type-Safety" for entity arguments?
Inheritance is a tool provided by development platform, it is more than OK to use it, but only to the point where things get messy or too abstract. Remember, VO only expresses a specific domain-approach principle. The polymorphism OOP principle, on the other hand, which of course may be applied in DDD applications, is tightly coupled with abstraction concepts (i.e. base classes), and I would say it should fit better to the entities model part.
BTW, you can find on web several implementations for a base VO class.
Persistence: Reading stored VO
System designs were to be of less importance if the same validations had occurred over and over again in different points of a single use case. Unless you have a reason to believe that your database can be altered by external components, it is sufficient to reconstitute an entity from database without re-validating. Also keep in mind that a typical entity may embed at least one VO, which is the same VO used both in "persistence step" (when entity is being constructed) and in "reading step" (when being reconstituted).
Persistence/Admin: Something like "god" in the system.
Multitenancy applications can be aware of multiple kinds of users. Software does not care if one user is more powerful than another one, it is only subjected to rules. Whether you choose to have a single general entity User with VO FutureDate allowed to be set with null, or two entities User, Admin with VOs FutureDate (not null), FutureDate (nullable) respectively, is less of our interest here. The important thing is that multitenancy can be achieved through smart usage of dependency injection: system identifies user privileges and infers what factories, services or validations are to be injected.
Persistence: Mapping to DB data-types
It really depends on level of maturity in the DDD field. Applications will always have bugs, and you should have some clue on your business's bug-tolerance level in case you choose to design a lenient database.
Aside of that, keep in mind that no matter how much effort you put into it, your database can probably never reflect the full set of business invariants: limiting a single VO to some length is easy, but setting rules involving multiple VOs (that is when one VO's validity depends another VO) is less convenient.

Validate a GraphQL schema against another reference schema

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.

Changing hyperledger-composer resource definition

So as a project matures it will almost certainly be necessary to modify attributes of the resource definitions to cope with additional requirements.
Let's use two trivial examples - to add a country code to a client address, or to remove a middle initial and swap in a middle name field instead.
Currently if the resource definition changes, composer won't read whatever values are extant in the repository. I didn't exhaustively try all combos, but have had to reconstitute my blockchain at least twice because of this problem.
Is there a way to mark fields either as "new" or "deprecated" to get past this that I overlooked? It will be hard to make a case to move a system that can't be changed forward to production.
In the same vein it doesn't seem to like empty or null strings much (at least for participant attributes). Having an "optional" override somewhere would save a lot of extra bounds checking in my application. Is there one of those I missed too?
So you can use the APIs or REST to expose the legacy data? You may be referring to Playground above (its not really a tool for looking at production data, its for model prototyping/sandbox/testing type stuff).
On optional question - can just add that the field is optional in the model - example here -> https://github.com/hyperledger/composer-sample-networks/blob/master/packages/pii-network/models/pii.cto#L20

Best practice with coding system values

I think this should be an easy one, but haven't found any clear answer, on what would the best practice be.
In an application, we keep current status of an order (open, canceled, shipped, closed ...).
This variables cannot change without code change, but application should meet the following criteria:
status names should be easily displayed in different languages,
application can search via freetext status names (like googling for "open")
status_id should be available to developer via enum
zero headache when adding new statuses
Possible ways we have tackled this so far:
having DB table status with PK(id, language_id) and a separate enum which represents this statuses in an application.
PROS: 1.,2.,3. work out of the box, CONS: 4. needs to run update script on every client installation, SQL selects can become large and cumbersome, when dealing with a lot of code tables
having just enum:
PROS: 3.,4. CONS: 1.,2. is a total nightmare
having enums, which populate database tables on each start of an application:
PROS: 1.,2.,3.,4. work CONS: some overhead on application start, SQL select can become large and cumbersome, when dealing a lot code tables.
What is the most common way of tackling this problem?
Sounds like you summarized it pretty good yourself, and comparing the pros/cons points towards #3. Just one comment when you implement #3 though:
Use a caching mechanism (even a simple HashMap!) plus adding the option to refresh the cache - will ease your work when you'll want to change values (without the need to restart every time!).
I would, and do, use method 3 because it is the best of the lot. You can use resource files to store the translations in and map the enum values to keys in the resource files. Your database can contain the id of the enum for the status.
1.status names should be easily displayed in different languages,
2.application can search via freetext status names (like googling for "open")
These are interfaces layer's concern, you'd better not mix them in you domain model.
I would setup a mapping between status enum and i18n codes. the mapping could be stored in a file (cached in memory) or hardcoded.
for example: if you use dto or view adatper to render your ui.
public class OrderDetailViewAdapter {
private Order order;
public String getStatus() {
return i18nMapper.to(order.getStatus());//use hardcoded switch case or file impl
}
}
Or you could done this before you populating you dtos.
You could use a similar solution for goal2. When user types text, find corresponding enum from mapping and use enum for search.
Anyway, use db tables the less the better.
Personally, I always use dedicated enum class inside domain. Only responsibility of this class is holding status name (OPEN, CANCELED, SHIPPED, ...). Status name is not visible outside codebase. Also, status could be also stored inside database field as string (varchar or similar).
For the purpose of rendering, depending of number of use cases, sometimes I implement formatting inside formatter (e.g. OrderFormatter::formatStatusName(), OrderFormatter::formatAbbreviatedStatusName(), ...). If formatting is needed often I create dedicated class with all formatting styles needed (OrderStatusFormatter::short(), OrderStatusFormatter::abbriviated()...). Of course, internal mapping is needed to map status name to status title, and this is tricky part. But if you want layering you can't avoid mapping.
Translation is not dealt so far. I translate strings inside templates so formatters are clean of that responsibility. To summarize:
enum inside domain model
formatter inside presentation layer
translation inside template
There is no need to create special table for order status translations. Better choice would be to implement generic translation mechanism, seperated from your business code.

Documenting Core Data entity attributes with User Info entries

We're looking for a way to document Core Data entities. So far the only real options I've come up with are:
Document externally using UML or some other standard
Create NSManagedObject subclasses for every entity and use code comments
Use the User Info dictionary to create a key value pair that holds a string comment
Option 1 feels like too much extra work and something that will almost certainly be out of date 99% of the time.
Option 2 feels natural and more correct than option 1. The biggest con here is that those comments could potentially be lost if this model class is regenerated using Xcode.
Option 3 feels a little less correct than option 2, but has the added advantage of adding automation possibilities with regards to meta data extraction. For instance, in one of our apps we need to keep a real close eye on what we're storing locally on the device as well as syncing to iCloud. Using the user info dictionary it's pretty easy to automate the creation of some form of artefact which can be checked both internally and externally (by the client) for compliance
So my question is whether it would be inappropriate to use the user info dictionary for this purpose? And are there any other options I'm missing?
Option 2 is what I use every time. If you look at your core data model (something.xcdatamodeld or something.xcdatamodel) you will see something like the picture below.
You can tie your entity to whatever class you want and then put the comments in there. It helps if you keep your entity name the same as your class name to make it obvious what you've done.
Additionally this also gives you the ability to add automation. You can do this by creating custom getters and setters (accessor methods) and a custom description method.
I use option 2 and categories. I'll let XCode generate the NSManagedObject subclasses and use a categorie on each of these subclasses. With the categories I do not loose my changes made in the categories, can document, make custom getter and setters and I am still able to use generated subclasses.
If we speak only about documenting (i.e. writing more or less large amounts of text which is intended to be read by humans) your classes, I'd use the option 2.
If you are concerned with the possibility of Xcode overwriting your classes in the option 2, you may consider creating two classes for each entity: one which is generated by Xcode and always could be replaced (you generally do not touch this file) and one other which inherits from the generated one and in which you put all your customizations and comments.
This two-class approach is proposed by the mogenerator.
Although if you need to store some metadata with the entities which will be processed programmatically, the userInfo is perfectly suitable for this.

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