* spread over each second. When the incoming request rate exceeds {@code permitsPerSecond} the
   * rate limiter will release one permit every {@code (1.0 / permitsPerSecond)} seconds. When the
   * rate limiter is unused, bursts of up to {@code permitsPerSecond} permits will be allowed, with

If you have an API that does a comparable amount of computations every time and you have a lot of clients, then the **CPU utilization** will probably *also be stable* (instead of constantly going up and down quickly).

### Examples of Replication Tools and Strategies

   * the underlying collection.
   *
   * <p>The returned collection isn't threadsafe or serializable, even if {@code unfiltered} is.
   *
   * <p>Many of the filtered collection's methods, such as {@code size()}, iterate across every
   * element in the underlying collection and determine which elements satisfy the filter. When a
   * live view is <i>not</i> needed, it may be faster to copy {@code Iterables.filter(unfiltered,
   * predicate)} and use the copy.

They are, more or less, at opposite ends, complementing each other.

Requests has a very simple and intuitive design, it's very easy to use, with sensible defaults. But at the same time, it's very powerful and customizable.

That's why, as said in the official website:

> Requests is one of the most downloaded Python packages of all time

The way you use it is very simple. For example, to do a `GET` request, you would write:

```Python

      } catch (Throwable e) {
        throw sanityError(classToTest, NULL_TEST_METHOD_NAMES, "nulls test", e);
      }
    }
  }

  /**
   * Tests {@code equals()} and {@code hashCode()} implementations for every top-level class in the
   * package, that explicitly implements {@link Object#equals}. For a class {@code C}:
   *
   * <ul>
   *   <li>The visible constructor or visible static factory method with the most parameters is used

 * than {@code size()}. Furthermore, this structure only depends on a fixed number of arrays; {@code
 * add(x)} operations <i>do not</i> create objects for the garbage collector to deal with, and for
 * every element added, the garbage collector will have to traverse {@code 1.5} references on
 * average, in the marking phase, not {@code 5.0} as in {@code java.util.HashSet}.
 *

      }
    }
  }

  @GwtIncompatible // DoubleMath.roundToLong(double, RoundingMode)
  public void testRoundExactIntegralDoubleToLong() {
    for (double d : INTEGRAL_DOUBLE_CANDIDATES) {
      // every mode except UNNECESSARY
      BigDecimal expected = new BigDecimal(d).setScale(0, UNNECESSARY);
      boolean isInBounds =
          expected.compareTo(MAX_LONG_AS_BIG_DECIMAL) <= 0

     of any Contributor. You must make it absolutely clear that any such
     warranty, support, indemnity, or liability obligation is offered by You
     alone, and You hereby agree to indemnify every Contributor for any
     liability incurred by such Contributor as a result of warranty, support,
     indemnity or liability terms You offer. You may include additional

     behalf of any Contributor. You must make it absolutely clear that any
     such warranty, support, indemnity, or liability obligation is offered by
     You alone, and You hereby agree to indemnify every Contributor for any
     liability incurred by such Contributor as a result of warranty, support,
     indemnity or liability terms You offer. You may include additional

     * StringUtils.isAsciiPrintable("Ceki G\u00fclc\u00fc") = false
     * </pre>
     *
     * @param cs the CharSequence to check, may be null
     * @return {@code true} if every character is in the range 32 thru 126
     */
    public static boolean isAsciiPrintable(final CharSequence cs) {
        if (cs == null) {
            return false;
        }
        final int sz = cs.length();