But as you go away from the counter and sit at the table with a number for your turn, you can switch 🔀 your attention to your crush, and "work" ⏯ 🤓 on that. Then you are again doing something very "productive" as is flirting with your crush 😍.

3. This `yield from` tells the function to iterate over that thing named `file_like`. And then, for each part iterated, yield that part as coming from this generator function.

    So, it is a generator function that transfers the "generating" work to something else internally.

    By doing it this way, we can put it in a `with` block, and that way, ensure that it is closed after finishing.

!!! tip

#### Optimizations

A naive implementation would simply regenerate all resources, of all subscribed types, for each client, on any configuration change. However, this scales poorly. As a result, we have many levels of optimizations to avoid doing this work.

import org.junit.jupiter.api.Tag
import org.junit.jupiter.api.Test

/**
 * Integration test to confirm that [TaskRunner] works with a real backend. Business logic is all
 * exercised by [TaskRunnerTest].
 *
 * This test is doing real sleeping with tolerances of 250 ms. Hopefully that's enough for even the
 * busiest of CI servers.
 */
@Tag("Slowish")
class TaskRunnerRealBackendTest {
  private val log = LinkedBlockingDeque<String>()

            startAnotherThread()
          }

          return readyTask
        }

        // Notify the coordinator of a task that's coming up soon.
        coordinatorWaiting -> {
          if (minDelayNanos < coordinatorWakeUpAt - now) {
            backend.coordinatorNotify(this@TaskRunner)
          }
          return null
        }

      if (networkResponse == null && cacheCandidate != null) {
        cacheCandidate.body.closeQuietly()
      }
    }

    // If we have a cache response too, then we're doing a conditional get.
    if (cacheResponse != null) {
      if (networkResponse?.code == HTTP_NOT_MODIFIED) {
        val response =
          cacheResponse.newBuilder()

Use `clang-tidy` to check your C/C++ changes. To install `clang-tidy` on ubuntu:16.04, do:

```bash
apt-get install -y clang-tidy
```

You can check a C/C++ file by doing:


```bash
clang-format <my_cc_file> --style=google > /tmp/my_cc_file.cc
diff <my_cc_file> /tmp/my_cc_file.cc
```

#### Python coding style

Changes to TensorFlow Python code should conform to

Of course, the attackers would not try all this by hand, they would write a program to do it, possibly with thousands or millions of tests per second. And would get just one extra correct letter at a time.

But doing that, in some minutes or hours the attackers would have guessed the correct username and password, with the "help" of our application, just using the time taken to answer.

#### Fix it with `secrets.compare_digest()`

- Erasure coding used by MinIO is [Reed-Solomon](https://github.com/klauspost/reedsolomon) erasure coding scheme, which has a total shard maximum of 256 i.e 128 data and 128 parity. MinIO design goes beyond this limitation by doing some practical architecture choices.

      timeout().deadlineNanoTime(nowNs + originalDurationNs)
    }
  }
}

/**
 * Attempts to exhaust this, returning true if successful. This is useful when reading a complete
 * source is helpful, such as when doing so completes a cache body or frees a socket connection for
 * reuse.
 */
internal fun Source.discard(
  timeout: Int,
  timeUnit: TimeUnit,
): Boolean =
  try {
    this.skipAll(timeout, timeUnit)