Before this commit, we would always show the 'declared form' of type aliases, with their generic, non-instantiated parameters. This now tries to unify the annotation with the underlying inferred type to provide even better alias pretty printing.
Also, this commit makes `apply_term` automatically re-intern the
program since it isn't safe to apply any term onto a UPLC program. In
particular, terms that introduce new let-bindings (via lambdas) will
mess with the already generated DeBruijn indices.
The problem doesn't occur for pure constant terms like Data. So we
still have a safe and fast version 'apply_data' when needed.
This was a mess to say to the least. The mess started when we wanted
to make all definitions in codegen use immutable maps of references --
which was and still is a good idea. Yet, the population of the data
types and functions definitions was done somehow in a separate step,
in a rather ad-hoc manner.
This commit changes that to ensure the project's data_types and
functions are populated while type checking the AST such that we need
not to redo it after.
The code for registering the data type definitions and function
definitions was also duplicated in at least 3 places. It is now a
method of the TypedModule.
Note: this change isn't only just cosmetic, it's also necessary for
the commit that follows which aims at adding tests to the set of
available function definitions, thus allowing to make property tests
callable.
We cannot enforce internal invariants on opaque types from only structural checks on Data. Thus, it is forbidden to find an opaque type in an outward-facing interface. Instead, users should rely on intermediate representations and lift them into opaque types using constructors and methods provided by the type (e.g. Dict.from_list, Rational.from_int, Rational.new, ...)
This commit allows Data to be optionally annotated with a
phantom-type. This doesn't change anything in codegen but we can now
leverage this information to generate better blueprint schemas.
Computes the policy ID of a minting policy; added guards for blueprint address to check that it's not a minting policy; Wasn't 100% sure where the errors should live, so I'm happy to move them if there's objections
closes#569
* added new methods to Definitions
it doesn't use expect
* lookup was failing for the special map/pair case
when resolving list generics
Co-authored-by: Pi <pi@sundaeswap.finance>
The apply command now works only from a serialized CBOR data (instead of a UPLC syntax). So it is no longer possible to specify arbitrary cbor terms through the CLI. I believe it to be an acceptable limitation for now; especially given that Aiken will never generate blueprints with non-data terms at the interface boundary.
These were needed before as a way to _partially deserialize_
blueprints. Indeed, some commands required accessing information of
the blueprint, but not necessarily the schema. So out of laziness (or
cleverness?), we only deserialized validators as serde::Value and
achieved that through the use of generics.
Now that validators and schemas have proper deserialisers, we can
simply deserialize a blueprint.
TODO: Our serialisation/deserialisation is safe with regards to
itself; i.e. it roundtrips. However, we only supports a subset of the
specified blueprint format. For example, we would fail to deserialize
blueprints that have inline data-schemas (we only use references).
This is needed in order to deserialize a JSON blueprint and use it to perform validation.
Still TODO:
- [ ] Write JSON deserializer for 'Schema'
Which should now be relatively straightforward.
* move uplc::ast::builder to uplc::builder
* rename aiken_lang::uplc to aiken_lang::gen_uplc
* move aiken_lang::air and aiken_lang::builder to aiken_lang::gen_uplc
as submodules
Co-authored-by: Kasey White <kwhitemsg@gmail.com>
* rename force_wrap to force
* add a bunch of builder methods to Term<Name>
* refactor one tiny location to show off builder methods
* split generate into `generate` and `generate_test`
* create wrap_as_multi_validator function
Co-authored-by: Kasey White <kwhitemsg@gmail.com>
This was a bit tricky and I ended up breaking things down a lot and
trying different path. This commit is the result of the most
satisfying one.
It introduces a new 'concept' and types: Definitions and Reference.
These elements are meant to reflect JSON pointers and JSON-schema
definitions which we now use for pretty much all user-defined
data-types.
In fact, Schemas are no longer inlined, but are always referencing
some schema under "definitions".
This indirection is necessary in order to cope with recursive types.
And while it's only truly necessary for recursive types, using it
consistently makes it both easier to produce and easier to consume.
---
The blueprint generation for recursive types here also works thanks to
the 'Definitions' data-structure wrapper around a BTreeMap. This uses
a strategy where:
(1) schemas are only generated if they haven't been seen before
(2) schemas are marked as seen BEFORE actually being generated (to
effectively stop a recursive generation).
This relies on one important aspect: the key must be uniquely
identifying a given schema. Which means that we have to monomorphize
data-types with generic parameters also here, and use keys that are
specialized in one data-type.
---
In this large overhaul we've also lost one thing which I didn't bother
re-introducing yet to keep the work manageable: title for record
fields. Before, we use to pull those from record constructor when
available, yet now, every record constructor has been replaced by a
`$ref`. We could theoritically attach a title to the reference. I'll
try to quickly add that in a later commit.
Having the data's schema be optional at the level of the 'Schema' did not allow to represent cases where there would be an opaque data at an arbitrary nesting. So I introduced a new variant 'Opaque' on 'Data' to fill that gap.
This has been removed from the CIP-0057 specification since validators
are often re-used for multiple purposes (especially validators with
arity 2). It's misleading to assign a validator a purpose since the
purpose distinction actually happens _within_ the validator itself.
This caused me some trouble. In my first approach, I ended up having
multiple traces because nested values would be evaluated twice; once
as condition, and once as part of the continuation.
To prevent this, we can simply evaluate the condition once, and return
plain True / False boolean as outcome. So this effectively transforms any
expression:
```
expr
```
as
```
if expr { True } else { trace("...", False) }
```
We want the lookup to yield a result when there's only a single
validator; and no title is provided. So that users can simply do
'aiken address' in their project if it's unambiguous. The validator's
name is only required to disambiguate between multiple validators.
I also noticed that the order of arguments in with_validator was
wrong. Somehow.
rvcas