},...

 *
 * @author shinsuke
 *
 */
public class EmlExtractor extends AbstractExtractor {
    /** Array of day of week abbreviations used for parsing received dates */
    private static final String[] DAY_OF_WEEK = { "Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun" };

    /** Logger instance for this class */
    private static final Logger logger = LogManager.getLogger(EmlExtractor.class);

    /** Properties used for mail processing */

tsuruta.aomori.jp
tsushima.aichi.jp
tsushima.nagasaki.jp
tsuwano.shimane.jp
tsuyama.okayama.jp
tt
tt.im
tube
tucker.replit.dev
tui
tula.su
tuleap-partners.com
tunes
tunk.org
tur.ar
tur.br
turek.pl
turin.it
turystyka.pl
tuscany.it
tushu
tuva.su
tuxfamily.org
tuyenquang.vn
tv
tv.bb
tv.bo
tv.br
tv.im
tv.in
tv.it
tv.jo

	// type of i is int
	// type of s is string
	// s == a[i]
	g(i, s)
}

var key string
var val interface{}  // element type of m is assignable to val
m := map[string]int{"mon":0, "tue":1, "wed":2, "thu":3, "fri":4, "sat":5, "sun":6}
for key, val = range m {
	h(key, val)
}
// key == last map key encountered in iteration
// val == map[key]

var ch chan Work = producer()

    *   Add `tf.contrib.data.prefetch_to_device`, which enables prefetching
        dataset elements to GPU memory.
    *   Add `tf.contrib.data.AUTOTUNE`, which allows the tf.data runtime to
        automatically tune the prefetch buffer sizes based on your system and
        environment.
    *   Add `tf.contrib.data.make_csv_dataset` for building datasets of CSV
        files.
*   Eager Execution: