this.allowsSelfLoops = builder.allowsSelfLoops;
    this.nodeOrder = builder.nodeOrder.cast();
    this.edgeOrder = builder.edgeOrder.cast();
    // Prefer the heavier "MapRetrievalCache" for nodes if lookup is expensive. This optimizes
    // methods that access the same node(s) repeatedly, such as Graphs.removeEdgesConnecting().
    this.nodeConnections =
        (nodeConnections instanceof TreeMap)

    this.isDirected = builder.directed;
    this.allowsSelfLoops = builder.allowsSelfLoops;
    this.nodeOrder = builder.nodeOrder.cast();
    // Prefer the heavier "MapRetrievalCache" for nodes if lookup is expensive.
    this.nodeConnections =
        (nodeConnections instanceof TreeMap)
            ? new MapRetrievalCache<>(nodeConnections)
            : new MapIteratorCache<>(nodeConnections);

Let's start with an example and then see it in detail.

We create an async function `lifespan()` with `yield` like this:

{* ../../docs_src/events/tutorial003_py310.py hl[16,19] *}

    testBytes(3, EXPECTED_THREE_BYTE_ROUNDTRIPPABLE_COUNT);
  }

  /**
   * Tests that round tripping of a sample of four byte permutations work. All permutations are
   * prohibitively expensive to test for automated runs. This method tests specific four-byte cases.
   */
  public void testIsWellFormed_4BytesSamples() {
    // Valid 4 byte.
    assertWellFormed(0xF0, 0xA4, 0xAD, 0xA2);
    // Bad trailing bytes

    CountingRemovalListener<Integer, Integer> removalListener = countingRemovalListener();
    IdentityLoader<Integer> loader = identityLoader();

    // Even numbers are free, odd are too expensive
    Weigher<Integer, Integer> evensOnly = (k, v) -> k % 2;

    LoadingCache<Integer, Integer> cache =
        CacheBuilder.newBuilder()
            .concurrencyLevel(1)
            .maximumWeight(0)

    CountingRemovalListener<Integer, Integer> removalListener = countingRemovalListener();
    IdentityLoader<Integer> loader = identityLoader();

    // Even numbers are free, odd are too expensive
    Weigher<Integer, Integer> evensOnly = (k, v) -> k % 2;

    LoadingCache<Integer, Integer> cache =
        CacheBuilder.newBuilder()
            .concurrencyLevel(1)
            .maximumWeight(0)

      //
      // We use two volatile reads. We could reduce this to one by
      // putting our fields into a holder class, but (at least on x86)
      // the extra memory consumption and indirection are more
      // expensive than the extra volatile reads.
      long nanos = expirationNanos;
      long now = System.nanoTime();
      if (nanos == 0 || now - nanos >= 0) {
        synchronized (lock) {

Before Let's Encrypt, these **HTTPS certificates** were sold by trusted third parties.

The process to acquire one of these certificates used to be cumbersome, require quite some paperwork and the certificates were quite expensive.

But then **[Let's Encrypt](https://letsencrypt.org/)** was created.

      //
      // We use two volatile reads. We could reduce this to one by
      // putting our fields into a holder class, but (at least on x86)
      // the extra memory consumption and indirection are more
      // expensive than the extra volatile reads.
      long nanos = expirationNanos;
      long now = System.nanoTime();
      if (nanos == 0 || now - nanos >= 0) {
        synchronized (lock) {

    int removes = frequency(asList(stimuli), remove);
    if ((!features.contains(IteratorFeature.SUPPORTS_REMOVE) && removes > 1)
        || (stimuli.length >= 5 && removes > 2)) {
      // removes are the most expensive thing to test, since they often throw exceptions with stack
      // traces, so we test them a bit less aggressively
      return;
    }