// Confirm that when Reader panics, the empty buffer remains empty
	var buf2 Buffer
	defer func() {
		recover()
		check(t, "TestReadFromPanicReader (2)", &buf2, "")
	}()
	buf2.ReadFrom(panicReader{panic: true})
}

func TestReadFromNegativeReader(t *testing.T) {
	var b Buffer
	defer func() {
		switch err := recover().(type) {
		case nil:
			t.Fatal("bytes.Buffer.ReadFrom didn't panic")
		case error:

 * if (forceCacheResponse.code() != 504) {
 *   // The resource was cached! Show it.
 * } else {
 *   // The resource was not cached.
 * }
 * ```
 *
 * This technique works even better in situations where a stale response is better than no response.
 * To permit stale cached responses, use the `max-stale` directive with the maximum staleness in
 * seconds:
 *
 * ```java
 * Request request = new Request.Builder()

* Then check if the question (the vast majority are questions) is **clear**.

* In many cases the question asked is about an imaginary solution from the user, but there might be a **better** one. If you can understand the problem and use case better, you might be able to suggest a better **alternative solution**.

* If you can't understand the question, ask for more **details**.

### Reproduce the problem

        } else {
          var buffer = Buffer()
          requestBody.writeTo(buffer)

          var gzippedLength: Long? = null
          if ("gzip".equals(headers["Content-Encoding"], ignoreCase = true)) {
            gzippedLength = buffer.size
            GzipSource(buffer).use { gzippedResponseBody ->
              buffer = Buffer()
              buffer.writeAll(gzippedResponseBody)
            }

    byteCount: Int,
    inFinished: Boolean,
  ) {
    val buffer = Buffer()
    source.require(byteCount.toLong()) // Eagerly read the frame before firing client thread.
    source.read(buffer, byteCount.toLong())
    pushQueue.execute("$connectionName[$streamId] onData") {
      ignoreIoExceptions {
        val cancel = pushObserver.onData(streamId, buffer, byteCount, inFinished)

### Is concurrency better than parallelism?

Nope! That's not the moral of the story.

Concurrency is different than parallelism. And it is better on **specific** scenarios that involve a lot of waiting. Because of that, it generally is a lot better than parallelism for web application development. But not for everything.

  private fun sourceReader(source: Source?): Callable<ByteString> {
    return Callable {
      val buffer = Buffer()
      while (source!!.read(buffer, 16384) != -1L) {
      }
      source.close()
      buffer.readByteString()
    }
  }

  private fun assertFile(
    prefix: ByteString,
    upstreamSize: Long,
    metadataSize: Int,

Specifically, to see Uvicorn, Starlette and FastAPI compared together (among many other tools).

The simpler the problem solved by the tool, the better performance it will get. And most of the benchmarks don't test the additional features provided by the tool.

The hierarchy is like:

* **Uvicorn**: an ASGI server
    * **Starlette**: (uses Uvicorn) a web microframework

        if (problem.getLineNumber() > 0) {
            if (!buffer.isEmpty()) {
                buffer.append(", ");
            }
            buffer.append("line ").append(problem.getLineNumber());
        }

        if (problem.getColumnNumber() > 0) {
            if (!buffer.isEmpty()) {
                buffer.append(", ");
            }
            buffer.append("column ").append(problem.getColumnNumber());
        }

func NewBytePoolCap(maxSize uint64, width int, capwidth int) (bp *BytePoolCap) {
	if capwidth > 0 && capwidth < 64 {
		panic("buffer capped with smaller than 64 bytes is not supported")
	}
	if capwidth > 0 && width > capwidth {
		panic("buffer length cannot be > capacity of the buffer")
	}
	return &BytePoolCap{
		c:    make(chan []byte, maxSize),
		w:    width,
		wcap: capwidth,
	}
}