Flask is a "microframework", it doesn't include database integrations nor many of the things that come by default in Django.

This simplicity and flexibility allow doing things like using NoSQL databases as the main data storage system.

As it is very simple, it's relatively intuitive to learn, although the documentation gets somewhat technical at some points.

						}
					}
				}
			})
		}
	}
}

// Baseline:
//   - ~150us via agent if cached for A/AAAA
//   - ~300us via agent when doing the cname redirect
//   - 5-6ms to upstream resolver directly
//   - 6-7ms via agent to upstream resolver (cache miss)
//
// Also useful for load testing is using dnsperf. This can be run with:
//

         * than a handful of exceptions. But it seems prudent to set a cap on how many we'll cache.
         * This avoids out-of-control memory consumption, and it keeps the cache from growing so
         * large that doing the lookup is noticeably slower than redoing the work would be.
         *
         * Ideally we'd have a real eviction policy, but until we see a problem in practice, I hope

			g := st.Resource.Goroutine()
			if inGC[g] || bgMark[g] {
				if !old.Executing() && new.Executing() {
					// Started running while doing GC things.
					ps[ev.Proc()].gc++
				} else if old.Executing() && !new.Executing() {
					// Stopped running while doing GC things.
					ps[ev.Proc()].gc--
				}
			}
			states[g] = new
		case EventLabel:
			l := ev.Label()

}

// podRequests is a simplified version of pkg/api/v1/resource/PodRequests that operates against the core version of
// pod. Any changes to that calculation should be reflected here.
// TODO: Maybe we can consider doing a partial conversion of the pod to a v1
// type and then using the pkg/api/v1/resource/PodRequests.
func podRequests(pod *api.Pod, opts podResourcesOptions) api.ResourceList {
	reqs := api.ResourceList{}

	badLocalRevRE *lazyregexp.Regexp                                                                  // regexp of names that must not be served out of local cache without doing fetch first
	statLocal     func(rev, remote string) []string                                                   // cmd to stat local rev

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

  }

  /*
   * TODO(cpovirk): It would be great to run all these tests (including class unloading) in an
   * environment that forces Futures.getChecked to its fallback WeakSetValidator. One awful way of
   * doing so would be to derive a separate test library by using remove_from_jar to strip out
   * ClassValueValidator.
   *
   * Fortunately, we get pretty good coverage "by accident": We run all these tests against the

  }

  /*
   * TODO(cpovirk): It would be great to run all these tests (including class unloading) in an
   * environment that forces Futures.getChecked to its fallback WeakSetValidator. One awful way of
   * doing so would be to derive a separate test library by using remove_from_jar to strip out
   * ClassValueValidator.
   *
   * Fortunately, we get pretty good coverage "by accident": We run all these tests against the

// json output (the trace viewer can hardly handle more).
func splitTrace(parsed *parsedTrace) ([]traceviewer.Range, error) {
	// TODO(mknyszek): Split traces by generation by doing a quick first pass over the
	// trace to identify all the generation boundaries.
	s, c := traceviewer.SplittingTraceConsumer(100 << 20) // 100 MiB
	if err := generateTrace(parsed, defaultGenOpts(), c); err != nil {