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.
Tracing is now turn OFF by default when:
- building project
- building documentation
- building dependencies
It can be turned ON only when building project using `--keep-traces`.
That means it's not possible to build dependencies with traces. The
address `--rebuild` flag will also rebuild without traces.
Tracing is however turn ON by default when:
- checking the project (and running tests).
In this scenario, tracing can be disabled using `--no-traces` (if for
example, one want to analyze the execution units of specific functions
without having to manually remove traces from code).
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.
This is still a bit clunky as the interface is expecting parameters in UPLC form and we don't do any kind of verification. So it is easy to shoot oneself in the foot at the moment (for example, to apply an integer into something that should have received a data). To be improved later.
Without that, we have no way to distinguish between fully applied
validators and those that still require some hard-coded parameters.
Next steps is to make it easier to apply parameters to those, as well
as forbid the creation of addresses of validators that aren't fully
qualified.
This calculates a validator's address from validators found in a blueprint. It also provides a convenient way to attach a delegation part to the validator if needs be. The command is meant to provide a nice user experience and works 'out of the box' for projects that have only a single validator. Just call 'aiken address' to get the validator's address.
Note that the command-line doesn't provide any option to configure the target network. This automatically assumes testnet, and will until we deem the project ready for mainnet. Those brave enough to run an Aiken's program on mainnet will find a way anyway.
Here's a trick though: I got lazy (a bit) and did not write a full deserializer for Schema because this is busywork and not at all necessary at this stage. Instead, I've made the blueprint parameterized by a generic type <T>; which represents the type of the underlying blueprint's schema. When deserializing from JSON, we can default to 'Value' to get a free deserializer. Since all we're interested about is the program and the metadata (purpose and title) of a validator, it works nicely.
Serialization however expects a Blueprint<Schema>, and most of the functions operates over a Blueprint<Schema> anyway.
In an ideal world, I should have handlded that directly at the conflicting commit in the rebase, but this would have bubbled up through all commits... which I wasn't really quite keen on going through. So here's an extra ugly commit that comes and 'fix the rebase'.
This is quite something, because now we have a testing pipeline that
can also be used for testing other compiler-related stuff such as the
type-checker or the code generator.
This also now introduce two levels of representable types (because it's needed at least for tuples):
Plutus Data (a.k.a Data) and UPLC primitives / constants (a.k.a Schema).
In practice, we don't want to specify blueprints that use direct UPLC primitives because there's little support for producing those in the ecosystem. So we should aim for producing only Data whenever we can. Yet we don't want to forbid it either in case people know what they're doing. Which means that we need to capture that difference well in the type modelling (in Rust and in the CIP-0057 specification).
I've also simplified the error type for now, just to provide some degree of feedback while working on this. I'll refine it later with proper errors.
The blueprint is generated at the root of the repository and is
intended to be versioned with the rest. It acts as a business card
that contains many practical information. There's a variety of tools
we can then build on top of open-source contracts. And, quite
importantly, the blueprint is language-agnostic; it isn't specific to
Aiken. So it is really meant as an interop format within the
ecosystem.
Far less verbose than defining classes by hand, plus, it allows to have everything about a single error be co-located. And finally, it allows to use 'related', 'label' and so on more easily.
- Display function's signature next to the function name
(instead of being repeated below the function documentation).
- Same for module constants
- Display record constructors in a more concise manner, with
constructors fields next to constructors.
- Display generic parameters, if any, next to the type
- Plus some minor color and icon rework.
There are restrictions regarding how modules are called, but given that packages are tight to repositories anyway; there's no way someone can publish and use an aiken package on 'aiken-lang' without being part of the organization. So the restriction on the command-line is pointless. Plus, it prevents us from using 'aiken-lang' as a placeholder name for tutorials.
This makes it easier to add new dependencies, without having to
manually edit the `aiken.toml` file.
The command is accessible via two different paths:
- aiken deps add
or simply
- aiken add
for this is quite common to find at the top-level of the command-line,
and, we still want to keep commands for managing dependencies grouped
under a command sub-group and not all at the top-level. So we're
merely promoting that one for visibility.
This is a bit cleaner, as the 'cmd/new' had many on-the-fly functions
which are better scoped inside this module.
Plus, it plays nicely with the std::str::FromStr trait definition.
Aiken's build system uses an internal global cache system to avoid
downloading the same packages over and over across projects. However,
prior to this commit, the cache key would be based of the dependency
version which can be either:
- A commit hash
- A branch or tag name
However, in the latter case, it means that the very first time we end
up fetching a dependency will lock its version forever (or until the
cache is cleared). This was inconvenient.
This commit changes that so that we use not only a branch name as
cache key, but additionally, the etag returned by the GitHub API
server. The etag is part of the HTTP headers, so it can be fetched
quickly using a simple HEAD request. It changes whenever the content
behind the endpoint changes -- which happens to be exactly what we
want. With this, we can quickly check whether an upstream package has
been updated and download the latest version should users have
specified a branch name as a version number.
For example, my current cache now looks as follow:
```
/Users/ktorz/Library/Caches/aiken/packages/
├── aiken-lang-stdlib-1cedbe85b7c7e9c4036d63d45cad4ced27b0d50b.zip
├── aiken-lang-stdlib-6b482fa00ec37fe936c93155e8c670f32288a686.zip
├── aiken-lang-stdlib-7ca9e659688ea88e1cfdc439b6c20c4c7fae9985.zip
└── aiken-lang-stdlib-main@04eb45df3c77f6611bbdff842a0e311be2c56390f0fa01f020d69c93ff567fe5.zip
```
## Before
```
× Checking
╰─▶ Unknown variable
Finite
╭─[../stdlib/validators/tmp.ak:10:1]
10 │ let now = when context.transaction.validity_range.lower_bound.bound_type is {
11 │ Finite { t } -> t
· ────────────
12 │ NegativeInfinity -> 0
╰────
```
## After
```
× Type-checking
╰─▶ Unknown data-type constructor 'Finite'
╭─[../stdlib/validators/tmp.ak:10:1]
10 │ let now = when context.transaction.validity_range.lower_bound.bound_type is {
11 │ Finite { t } -> t
· ────────────
12 │ NegativeInfinity -> 0
╰────
help: Did you forget to import it?
Data-type constructors are not automatically imported, even if their type is
imported. So, if a module `aiken/pet` defines the following type:
┍━ aiken/pet.ak ━━━━━━━━
│ pub type Pet {
│ Cat
│ Dog
│ }
You must import its constructors explicitly to use them, or prefix them
with the module's name.
┍━ foo.ak ━━━━━━━━
│ use aiken/pet.{Pet, Dog}
│
│ fn foo(pet : Pet) {
│ when pet is {
│ pet.Cat -> // ...
│ Dog -> // ...
│ }
│ }
```
KtorZ