* Change demo to server
* Expose client in package.json
* Reorganize tests
We don't want unit tests but instead test how both server and clients work
together. So this merges server/client test files.
* Fill in the client implementation a bit
* Use new client in fixture
* Add Promise/Uint8Array to lint rule
I'll probably end up deleting these deps later but they're here for now.
* Add trusted types to react on client side
* Implement changes according to review
* Remove support for trusted URLs, change TrustedTypes to trustedTypes
* Add support for deprecated trusted URLs
* Apply PR suggesstions
* Warn only once, remove forgotten check, put it behind a flag
* Move comment
* Fix PR comments
* Fix html toString concatenation
* Fix forgotten else branch
* Fix PR comments
* Revert "Revert "[Scheduler] Profiling features (#16145)" (#16392)"
This reverts commit 4ba1412305.
* Fix copy paste mistake
* Remove init path dependency on ArrayBuffer
* Add a regression test for cancelling multiple tasks
* Prevent deopt from adding isQueued later
* Remove pop() calls that were added for profiling
* Verify that Suspend/Unsuspend events match up in tests
This currently breaks tests.
* Treat Suspend and Resume as exiting and entering work loop
Their definitions used to be more fuzzy. For example, Suspend didn't always fire on exit, and sometimes fired when we did _not_ exit (such as at task enqueue).
I chatted to Boone, and he's saying treating Suspend and Resume as strictly exiting and entering the loop is fine for their use case.
* Revert "Prevent deopt from adding isQueued later"
This reverts commit 9c30b0b695.
Unnecessary because GCC
* Start counter with 1
* Group exports into unstable_Profiling namespace
* No catch in PROD codepath
* No label TODO
* No null checks
* [Scheduler] Mark user-timing events
Marks when Scheduler starts and stops running a task. Also marks when
a task is initially scheduled, and when Scheduler is waiting for a
callback, which can't be inferred from a sample-based JavaScript CPU
profile alone.
The plan is to use the user-timing events to build a Scheduler profiler
that shows how the lifetime of tasks interact with each other and
with unscheduled main thread work.
The test suite works by printing an text representation of a
Scheduler flamegraph.
* Expose shared array buffer with profiling info
Array contains
- the priority Scheduler is currently running
- the size of the queue
- the id of the currently running task
* Replace user-timing calls with event log
Events are written to an array buffer using a custom instruction format.
For now, this is only meant to be used during page start up, before the
profiler worker has a chance to start up. Once the worker is ready, call
`stopLoggingProfilerEvents` to return the log up to that point, then
send the array buffer to the worker.
Then switch to the sampling based approach.
* Record the current run ID
Each synchronous block of Scheduler work is given a unique run ID. This
is different than a task ID because a single task will have more than
one run if it yields with a continuation.
* Memoize promise listeners to prevent exponential growth
Previously, React would attach a new listener every time a promise is
thrown, regardless of whether the same listener was already attached
during a previous render. Because React attempts to render every time
a promise resolves, the number of listeners grows quickly.
This was especially bad in synchronous mode because the renders that
happen when the promise pings are not batched together. So if a single
promise has multiple listeners for the same root, there will be multiple
renders, which in turn results in more listeners being added to the
remaining unresolved promises. This results in exponential growth in
the number of listeners with respect to the number of IO-bound
components in a single render.
Fixes#14220
* Memoize on the root and Suspense fiber instead of on the promise
* Add TODO to fix persistent mode tests
* BUG: ReactPartialRenderer / New Context polutes mutable global state
The new context API stores the provided values on the shared context instance. When used in a synchronous context, this is not an issue. However when used in an concurrent context this can cause a "push provider" from one react render to have an effect on an unrelated concurrent react render.
I've encountered this bug in production when using renderToNodeStream, which asks ReactPartialRenderer for bytes up to a high water mark before yielding. If two Node Streams are created and read from in parallel, the state of one can polute the other.
I wrote a failing test to illustrate the conditions under which this happens.
I'm also concerned that the experimental concurrent/async React rendering on the client could suffer from the same issue.
* Use unique thread ID for each partial render to access Context
This first adds an allocator that keeps track of a unique ThreadID index
for each currently executing partial renderer. IDs are not just growing
but are reused as streams are destroyed.
This ensures that IDs are kept nice and compact.
This lets us use an "array" for each Context object to store the current
values. The look up for these are fast because they're just looking up
an offset in a tightly packed "array".
I don't use an actual Array object to store the values. Instead, I rely
on that VMs (notably V8) treat storage of numeric index property access
as a separate "elements" allocation.
This lets us avoid an extra indirection.
However, we must ensure that these arrays are not holey to preserve this
feature.
To do that I store the _threadCount on each context (effectively it takes
the place of the .length property on an array).
This lets us first validate that the context has enough slots before we
access the slot. If not, we fill in the slots with the default value.
Kunuk Nykjær