The task log API endpoint was loading the entire log into RAM, then sending
it as response. This makes display in a browser also a bit harder.
The API endpoint now returns some JSON with info about the task log,
including its size and which URL can be used to download it.
Manifest task: T99730
The generators always produce UNIX line-ends. This creates false file
modifications with Git on Windows. Convert them to DOS line-ends to avoid
this.
This was already done for the Go code; this commit just copies the approach
to the Python and JavaScript generators.
My way to get things working (I wouldn't call this a "solution" as I don't
know the root cause) was to emit two consecutive "reshuffled" events when
changing tabs in the job details, and to recalculate the table height when
the job type (so not the job itself, but its type info) is loaded.
For some reason, on Windows, creating a directory with zero permissions
still allows creating a file in there. Just skip that part of the test.
The Explorer's properties panel of the directory also shows "Read Only
(only applies to files)", so at least that seems consistent.
Add a `-pprof` CLI option to enable the profiler. It will expose profiler
info on the web interface at `/debug/pprof/`.
To have a nice view of this, including flame graphs, run:
```
go tool pprof -http localhost:8082 http://localhost:8080/debug/pprof/profile
```
Be more selective in what's saved to the database to speed some things up.
Most importantly, this avoids saving the entire job when a task status is
updated or a task is assigned.
Add a SHA256 password hasher for worker authentication. It's not used at
the moment, but can be switched to for faster API queries. Note that
switching will cause authentication errors on already-existing workers,
which means they'll automatically re-register.
This is mostly useful for debugging & profiling purposes.
Move the Worker password hashing/comparison functions into a struct, and
use it via an interface. This will make it easier to switch to different
hashing algorithms.
Even with a low number of iterations, BCrypt is quite slow. That's good for
security, but not for Flamenco Worker authentication -- the password is
more as "nice check to avoid accidentally reusing the same ID" than
something for security.
Build with `make stresser`. Run with:
./stresser -worker UUID -secret ABCXYZ
The worker ID and secret can be obtained from
`flamenco-worker-credentials.yaml`. If left empty, the stresser will
register as a new worker, and log the credentials to be used on the next
invocation.
In the first-time wizard, if Blender cannot be found on $PATH but it can
be found via .blend file association, that should just be reported as a
normal sitation, and not as a `500 Internal Server Error`.
Trigger the first-time wizard on first-time runs of Flamenco, by defaulting
the storage path to the empty string.
The wizard can always be triggered with the `-wizard` CLI argument. This is
just for detection of first-time / unconfigured runs.
After saving the configuration, show a message & restart the webapp.
The restarting is done after 2 seconds, to give the Manager some time to
restart after receiving the new config.
This just updates the config and saves it to `flamenco-manager.yaml`.
Saving the configuration doesn't restart the Manager yet, that's for
another commit.
This adds a `-wizard` CLI option to the Manager, which opens a webbrowser
and shows the First-Time Wizard to aid in configuration of Flamenco.
This is work in progress. The wizard is just one page, and doesn't save
anything yet to the configuration.
Adjust the loading of BAT from a wheel file in such a way that all
submodules are loaded in one go. This ensures that they're still
isolated from the rest of Blender (so other add-ons won't find our BAT),
but not from each other (so that there is only one copy of each
submodule).
In practice, this solves an issue where calling
`blender_asset_tracer.blendfile.set_strict_pointer_mode(False)` had no
effect. This was caused by each loaded submodule having a different copy
of `blendfile`.
Also loaded modules are logged more explicitly (at INFO level) to aid in
debugging later on.
