<!--
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements.  See the NOTICE file
distributed with this work for additional information
regarding copyright ownership.  The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance
with the License.  You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements. See the NOTICE file distributed with this
 * work for additional information regarding copyright ownership. The ASF
 * licenses this file to You under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0

/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *

	// TX saturating, however there are situations where a RX might also saturate.
	// To avoid these problems we must split the work at scale. With 1000 node
	// setup becoming a reality we must try to shard the work properly such as
	// pick 10 nodes that precisely can send those 100 requests the first node
	// in the 10 node shard would coordinate between other 9 shards to get the

  * Deployment was Alpha in 1.1 (though it had apiVersion extensions/v1beta1) and
was disabled by default. Due to some non-backward-compatible API changes, any
Deployment objects you created in 1.1 won’t work with in the 1.2 release.
     * Before upgrading to 1.2, <strong>delete all Deployment alpha-version resources</strong>, including the Replication Controllers and Pods the Deployment manages. Then

        entry.currentEditor = Editor(entry)
      }

      secondSpace == -1 && firstSpace == READ.length && line.startsWith(READ) -> {
        // This work was already done by calling lruEntries.get().
      }

      else -> throw IOException("unexpected journal line: $line")
    }
  }

  /**

 *       significantly worse than a {@code PriorityQueue} with manual eviction above the maximum
 *       size. In many cases {@link Ordering#leastOf} may work for your use case with significantly
 *       improved (and asymptotically superior) performance.
 *   <li>The retrieval operations {@link #peek}, {@link #peekFirst}, {@link #peekLast}, {@link

    * Check that it has a required attribute `price` that has to be a `float`.
    * Check that it has an optional attribute `is_offer`, that should be a `bool`, if present.
    * All this would also work for deeply nested JSON objects.
* Convert from and to JSON automatically.
* Document everything with OpenAPI, that can be used by:
    * Interactive documentation systems.

type Buffer struct {
	buf      []byte // contents are the bytes buf[off : len(buf)]
	off      int    // read at &buf[off], write at &buf[len(buf)]
	lastRead readOp // last read operation, so that Unread* can work correctly.
}

// The readOp constants describe the last action performed on
// the buffer, so that UnreadRune and UnreadByte can check for
// invalid usage. opReadRuneX constants are chosen such that