Overhaul the pipeline configuration logic by collapsing all dynamic
configuration options, both for analyses and pipes into a single
dictionary. Change all the interfaces so that there is no longer
distinction between the configuration of an analysis and of pipes.
Expose these options to the command line via `--{name}-configuration`
options for each pipe/analysis that is applicable to the command-line
invocation.
Add an additional piece of metadata that states which pipes are used to
compute a specific artifact. This can be used to derive which
configuration options influence the creation of an artifact.
Add two additional fields to `Artifact`: `defined_locations` and
`preferred_artifacts`. These are pieces of metadata that allow
navigation between multiple PTML-enabled documents.
Add categories in the pipeline, allow an artifact to have a category
specified which allows it to be shown or hidden by default. Adapt the
CLI tools to hide artifacts of the category that don't
`show_by_default=True`.
Rework which information is transmitted in the pipeline metadata,
avoiding redundancy and moving some information there instead of
returning it every time a request is made.
Change the `get_model` and `set_model` interface of `StorageProvider` so
that it is responsibility of the `StorageProvider` to
serialize/deserialize the model before returning to the caller.
This is in preparation to the model migration being implemented, since
it's now a responsibility of the storage provider to deserialize it it
can trivially re-save it to disk if it is migrated.
Add the functionality the the pipeline infrastructure and CLI to run
individual pipe and analyses as subcommands instead of in-process. This
allow better debuggability of individual pipes.
Convert the `RuntimeError`s emitted by the pipebox (e.g. when checking
preconditions or running analyses) into `PypelineError`s and have the
pypeline cli infrastructure handle them gracefully, without emitting
stacktraces.
Overload the `get` function of `Requests` so that, in addition to the
usual `Mapping` behavior, will return an empty `ObjectSet` if no default
is specified.
Improve the `schedule` in the `Pipeline` class by introducing two
optimizations:
* Prune all the `ContainerDeclarations` that are not actually used.
* Skip all tasks that have no outgoing elements that would have been
written by them.
Now the pype command has a `--verbose` argument that to enable debug
logging in the pypelien code.
Adapted the codebase to use this new logging format but replacing
`logging` with `revng.pypeline.utils.logger`, this is done in
preparation of debug-log.
Add implementation of the generic pype daemon.
It's implementation is split into `daemon.py` where we implement an
http framework agnostic interface, and `app.py` that uses it to serve
them using starlette.
Now pype has an `autocomplete` command usable to enable autocompletion
and revng2 now is based on `pype`, modifying its defalults and
injecting new commands.
Giacomo Vercesi