7 Composing choices¶
It’s time to put everything you’ve learnt so far together into a complete and secure DAML model for asset issuance, management, transfer, and trading. This application will have capabilities similar to the one in Quickstart guide. In the process you will learn about a few more concepts:
- DAML projects, packages and modules
- Composition of transactions
- Observers and stakeholders
- DAML’s execution model
The model in this section is not a single DAML file, but a DAML project consisting of several files that depend on each other.
DAML is organized in packages and modules. A DAML project is specified using a single
daml.yaml file, and compiles into a package. Each DAML file within a project becomes a DAML module. You can start a new project with a skeleton structure using
daml new project_name in the terminal.
Each DAML project has a main source file, which is the entry point for the compiler. A common pattern is to have a main file called
LibraryModules.daml, which simply lists all the other modules to include.
A minimal project would contain just two files:
daml/LibraryModules.daml. Take a look at the
daml.yaml for this project:
sdk-version: __VERSION__ name: __PROJECT_NAME__ source: daml/LibraryModules.daml version: 1.0.0 dependencies: - daml-prim - daml-stdlib
You can generally set
version freely to describe your project.
dependencies lists package dependencies: you should always include
daml-stdlib gives access to the DAML standard library.
You compile a DAML project by running
daml build from the project root directory. This creates a
dar package in
dar file is DAML’s equivalent of a
JAR file in Java: it’s the artifact that gets deployed to a ledger to load the contract model.
This project contains an asset holding model for transferrable, fungible assets and a separate trade workflow. The templates are structured in three modules:
In addition, there are tests in modules
All but the last
.-separated segment in module names correspond to paths, and the last one to a file name. The folder structure therefore looks like this:
. ├── daml │ ├── Intro │ │ ├── Asset │ │ │ ├── Role.daml │ │ │ └── Trade.daml │ │ └── Asset.daml │ ├── LibraryModules.daml │ └── Test │ └── Intro │ ├── Asset │ │ ├── Role.daml │ │ └── Trade.daml │ └── Asset.daml └── daml.yaml
Each file contains the DAML pragma and module header. For example,
daml 1.2 module Intro.Asset.Role where
You can import one module into another using the
import keyword. The
LibraryModules module imports all six modules:
import Intro.Asset () import Intro.Asset.Role () import Intro.Asset.Trade () import Test.Intro.Asset () import Test.Intro.Asset.Role () import Test.Intro.Asset.Trade ()
Imports always have to appear just below the module declaration. The
() behind each
import above is optional, and lets you only import selected names.
In this case, it suppresses an “unused import” warning.
LibraryModules is not actually using any of the imports in
() tells the compiler that this is intentional.
A more typical import statement is
import Intro.Asset as found in
The project both changes and adds to the
Iou model presented in 6 Parties and authority:
Assets are fungible in the sense that they have
Splitchoices that allow the
ownerto manage their holdings.
Transfer proposals now need the authorities of both
newOwnerto accept. This makes
Ioufrom the issuer’s point of view.
issuercould end up owing cash to anyone as transfers were authorized by just
newOwner. In this project, only parties having an
AssetHoldercontract can end up owning assets. This allows the
issuerto determine which parties may own their assets.
Tradetemplate adds a swap of two assets to the model.
Composed choices and scenarios¶
This project showcases how you can put the
Scenario actions you learnt about in 6 Parties and authority to good use. For example, the
Split choices each perform several actions in their consequences.
- Two create actions in case of
- One create and one archive action in case of
Split : SplitResult with splitQuantity : Decimal do splitAsset <- create this with quantity = splitQuantity remainder <- create this with quantity = quantity - splitQuantity return SplitResult with splitAsset remainder Merge : ContractId Asset with otherCid : ContractId Asset do other <- fetch otherCid assertMsg "Merge failed: issuer does not match" (issuer == other.issuer) assertMsg "Merge failed: owner does not match" (owner == other.owner) assertMsg "Merge failed: symbol does not match" (symbol == other.symbol) archive otherCid create this with quantity = quantity + other.quantity
return function used in
Split is available in any
Action context. The result of
return x is a no-op containing the value
x. It has an alias
pure, indicating that it’s a pure value, as opposed to a value with side-effects. The
return name makes sense when it’s used as the last statement in a
do block as its argument is indeed the “return”-value of the
do block in that case.
Taking transaction composition a step further, the
Trade_Settle choice on
Trade composes two
Trade_Settle : (ContractId Asset, ContractId Asset) with quoteAssetCid : ContractId Asset baseApprovalCid : ContractId TransferApproval do fetchedBaseAsset <- fetch baseAssetCid assertMsg "Base asset mismatch" (baseAsset == fetchedBaseAsset with observers = baseAsset.observers) fetchedQuoteAsset <- fetch quoteAssetCid assertMsg "Quote asset mismatch" (quoteAsset == fetchedQuoteAsset with observers = quoteAsset.observers) transferredBaseCid <- exercise baseApprovalCid TransferApproval_Transfer with assetCid = baseAssetCid transferredQuoteCid <- exercise quoteApprovalCid TransferApproval_Transfer with assetCid = quoteAssetCid return (transferredBaseCid, transferredQuoteCid)
The resulting transaction, with its two nested levels of consequences, can be seen in the
test_trade scenario in
TX #15 1970-01-01T00:00:00Z (Test.Intro.Asset.Trade:77:23) #15:0 │ known to (since): 'Alice' (#15), 'Bob' (#15) └─> 'Bob' exercises Trade_Settle on #13:1 (Intro.Asset.Trade:Trade) with quoteAssetCid = #10:1; baseApprovalCid = #14:2 children: #15:1 │ known to (since): 'Alice' (#15), 'Bob' (#15) └─> fetch #11:1 (Intro.Asset:Asset) #15:2 │ known to (since): 'Alice' (#15), 'Bob' (#15) └─> fetch #10:1 (Intro.Asset:Asset) #15:3 │ known to (since): 'USD_Bank' (#15), 'Bob' (#15), 'Alice' (#15) └─> 'Alice', 'Bob' exercises TransferApproval_Transfer on #14:2 (Intro.Asset:TransferApproval) with assetCid = #11:1 children: #15:4 │ known to (since): 'USD_Bank' (#15), 'Bob' (#15), 'Alice' (#15) └─> fetch #11:1 (Intro.Asset:Asset) #15:5 │ known to (since): 'Alice' (#15), 'USD_Bank' (#15), 'Bob' (#15) └─> 'Alice', 'USD_Bank' exercises Archive on #11:1 (Intro.Asset:Asset) #15:6 │ referenced by #17:0 │ known to (since): 'Bob' (#15), 'USD_Bank' (#15), 'Alice' (#15) └─> create Intro.Asset:Asset with issuer = 'USD_Bank'; owner = 'Bob'; symbol = "USD"; quantity = 100.0; observers =  #15:7 │ known to (since): 'EUR_Bank' (#15), 'Alice' (#15), 'Bob' (#15) └─> 'Bob', 'Alice' exercises TransferApproval_Transfer on #12:1 (Intro.Asset:TransferApproval) with assetCid = #10:1 children: #15:8 │ known to (since): 'EUR_Bank' (#15), 'Alice' (#15), 'Bob' (#15) └─> fetch #10:1 (Intro.Asset:Asset) #15:9 │ known to (since): 'Bob' (#15), 'EUR_Bank' (#15), 'Alice' (#15) └─> 'Bob', 'EUR_Bank' exercises Archive on #10:1 (Intro.Asset:Asset) #15:10 │ referenced by #16:0 │ known to (since): 'Alice' (#15), 'EUR_Bank' (#15), 'Bob' (#15) └─> create Intro.Asset:Asset with issuer = 'EUR_Bank'; owner = 'Alice'; symbol = "EUR"; quantity = 90.0; observers = 
Similar to choices, you can see how the scenarios in this project are built up from each other:
test_issuance = scenario do setupResult@(alice, bob, bank, aha, ahb) <- setupRoles assetCid <- submit bank do exercise aha Issue_Asset with symbol = "USD" quantity = 100.0 submit bank do asset <- fetch assetCid assert (asset == Asset with issuer = bank owner = alice symbol = "USD" quantity = 100.0 observers =  ) return (setupResult, assetCid)
In the above, the
test_issuance scenario in
Test.Intro.Asset.Role uses the output of the
setupRoles scenario in the same module.
The same line shows a new kind of pattern matching. Rather than writing
setupResults <- setupRoles and then accessing the components of
_2, etc., you can give them names. It’s equivalent to writing
setupResults <- setupRoles case setupResults of (alice, bob, bank, aha, ahb) -> ...
(alice, bob, bank, aha, ahb) <- setupRoles would also be legal, but
setupResults is used in the return value of
test_issuance so it makes sense to give it a name, too. The notation with
@ allows you to give both the whole value as well as its constituents names in one go.
DAML’s execution model¶
DAML’s execution model is fairly easy to understand, but has some important consequences. You can imagine the life of a transaction as follows:
- A party submits a transaction. Remember, a transaction is just a list of actions.
- The transaction is interpreted, meaning the
Updatecorresponding to each action is evaluated in the context of the ledger to calculate all consequences, including transitive ones (consequences of consequences, etc.).
- The views of the transaction that parties get to see (see Privacy) are calculated in a process called blinding, or projecting.
- The blinded views are distributed to the parties.
- The transaction is validated based on the blinded views and a consensus protocol depending on the underlying infrastructure.
- If validation succeeds, the transaction is committed.
The first important consequence of the above is that all transactions are committed atomically. Either a transaction is committed as a whole and for all participants, or it fails.
That’s important in the context of the
Trade_Settle choice shown above. The choice transfers a
baseAsset one way and a
quoteAsset the other way. Thanks to transaction atomicity, there is no chance that either party is left out of pocket.
The second consequence, due to 2., is that the submitter of a transaction knows all consequences of their submitted transaction – there are no surprises in DAML. However, it also means that the submitter must have all the information to interpret the transaction.
That’s also important in the context of
Trade. In order to allow Bob to interpret a transaction that transfers Alice’s cash to Bob, Bob needs to know both about Alice’s
Asset contract, as well as about some way for
Alice to accept a transfer – remember, accepting a transfer needs the authority of
issuer in this example.
Observers are DAML’s mechanism to disclose contracts to other parties. They are declared just like signatories, but using the
observer keyword, as shown in the
template Asset with issuer : Party owner : Party symbol : Text quantity : Decimal observers : [Party] where signatory issuer, owner ensure quantity > 0.0 observer observers
Asset template also gives the
owner a choice to set the observers, and you can see how Alice uses it to show her
Asset to Bob just before proposing the trade. You can try out what happens if she didn’t do that by removing that transaction.
usdCid <- submit alice do exercise usdCid SetObservers with newObservers = [bob]
Observers have guarantees in DAML. In particular, they are guaranteed to see actions that create and archive the contract on which they are an observer.
Since observers are calculated from the arguments of the contract, they always know about each other. That’s why, rather than adding Bob as an observer on Alice’s
AssetHolder contract, and using that to authorize the transfer in
Trade_Settle, Alice creates a one-time authorization in the form of a
TransferAuthorization. If Alice had lots of counterparties, she would otherwise end up leaking them to each other.
Controllers declared via the
controller cs can syntax are automatically made observers. Controllers declared in the
choice syntax are not, as they can only be calculated at the point in time when the choice arguments are known.
DAML’s privacy model is based on two principles:
- Parties see those actions that they have a stake in.
- Every party that sees an action sees its (transitive) consequences.
Item 2. is necessary to ensure that every party can independently verify the validity of every transaction they see.
A party has a stake in an action if
- they are a required authorizer of it
- they are a signatory of the contract on which the action is performed
- they are an observer on the contract, and the action creates or archives it
What does that mean for the
exercise tradeCid Trade_Settle action from
Alice is the signatory of
tradeCid and Bob a required authorizer of the
Trade_Settled action, so both of them see it. According to rule 2. above, that means they get to see everything in the transaction.
The consequences contain, next to some
fetch actions, two
exercise actions of the choice
Each of the two involved
TransferApproval contracts is signed by a different
issuer, which see the action on “their” contract. So the EUR_Bank sees the
TransferApproval_Transfer action for the EUR
Asset and the USD_Bank sees the
TransferApproval_Transfer action for the USD
Some DAML ledgers, like the scenario runner and the Sandbox, work on the principle of “data minimization”, meaning nothing more than the above information is distributed. That is, the “projection” of the overall transaction that gets distributed to EUR_Bank in step 4 of DAML’s execution model would consist only of the
TransferApproval_Transfer and its consequences.
Other implementations, in particular those on public blockchains, may have weaker privacy constraints.
Note that principle 2. of the privacy model means that sometimes parties see contracts that they are not signatories or observers on. If you look at the final ledger state of the
test_trade scenario, for example, you may notice that both Alice and Bob now see both assets, as indicated by the Xs in their respective columns:
This is because the
create action of these contracts are in the transitive consequences of the
Trade_Settle action both of them have a stake in. This kind of disclosure is often called “divulgence” and needs to be considered when designing DAML models for privacy sensitive applications.