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.
Rework the artifact endpoint, making it similar to the CLI invocation.
It now works on a single artifact and can be made to return both `json`
and `tar` as formats.
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.
Instead of executing `chdir` when using the `-C` option, which is
fragile when other paths are involved, store the option in the click
context and propagate it to the required code paths that require knowing
what the base directory is.
Move the epoch inside the storage_provider, this allows us to make the
storage_provider_factory to return an async context manager.
This way we can simplify the locking for the daemon, but forces the
CLI project commands to deal with async code.
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.