import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.OutputStream;
import java.net.URI;
import java.net.URISyntaxException;
import java.time.Duration;
import java.util.HashSet;
import java.util.Queue;
import java.util.Set;
import java.util.concurrent.ConcurrentLinkedQueue;

import org.apache.commons.lang3.StringUtils;
import org.apache.commons.net.ftp.FTP;

import java.io.Serializable;
import java.util.Arrays;
import java.util.Collection;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.LinkedHashSet;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.NavigableSet;

        assertEquals("DOMAIN", auth.getDomain());
        assertEquals("user", auth.getUsername());
        assertNotNull(auth.getPassword()); // Should fall back to default
    }

    // Test constructor with external hashes
    @Test
    void testConstructorWithExternalHashes() {
        byte[] challenge = new byte[8];
        byte[] ansiHash = new byte[24];
        byte[] unicodeHash = new byte[24];

            .createTestSuite());

    suite.addTest(
        SetTestSuiteBuilder.using(new ImmutableSetWithBadHashesGenerator())
            .named(ImmutableSetTest.class.getName() + ", with bad hashes")
            .withFeatures(
                CollectionSize.ANY,
                CollectionFeature.KNOWN_ORDER,
                CollectionFeature.ALLOWS_NULL_QUERIES)
            .createTestSuite());

 * amortized since some operations can trigger a hash table resize.
 *
 * <p>This implementation consumes significantly less memory than {@code java.util.LinkedHashSet} or
 * even {@code java.util.HashSet}, and places considerably less load on the garbage collector. Like
 * {@code java.util.LinkedHashSet}, it offers insertion-order iteration, with identical behavior.
 *

 * amortized since some operations can trigger a hash table resize.
 *
 * <p>This implementation consumes significantly less memory than {@code java.util.LinkedHashSet} or
 * even {@code java.util.HashSet}, and places considerably less load on the garbage collector. Like
 * {@code java.util.LinkedHashSet}, it offers insertion-order iteration, with identical behavior.
 *

        // This test uses a real MD5 instance to verify the HMAC calculation logic
        // HMACT64 is a modified HMAC-MD5 where the key is truncated at 64 bytes
        // instead of being hashed when it exceeds the block size.

        byte[] key = { (byte) 0x0b, (byte) 0x0b, (byte) 0x0b, (byte) 0x0b, (byte) 0x0b, (byte) 0x0b, (byte) 0x0b, (byte) 0x0b, (byte) 0x0b,

##### Warum Passwort-Hashing verwenden? { #why-use-password-hashing }

Wenn Ihre Datenbank gestohlen wird, hat der Dieb nicht die Klartext-Passwörter Ihrer Benutzer, sondern nur die Hashes.

Der Dieb kann also nicht versuchen, die gleichen Passwörter in einem anderen System zu verwenden (da viele Benutzer überall das gleiche Passwort verwenden, wäre dies gefährlich).

But you cannot convert from the gibberish back to the password.

##### Why use password hashing { #why-use-password-hashing }

If your database is stolen, the thief won't have your users' plaintext passwords, only the hashes.

So, the thief won't be able to try to use those same passwords in another system (as many users use the same password everywhere, this would be dangerous).

{* ../../docs_src/security/tutorial003_an_py310.py hl[82:85] *}

Pero no puedes convertir del galimatías al password.

##### Por qué usar hashing de passwords { #why-use-password-hashing }

Si tu base de datos es robada, el ladrón no tendrá los passwords en texto plano de tus usuarios, solo los hashes.

Entonces, el ladrón no podrá intentar usar esos mismos passwords en otro sistema (como muchos usuarios usan el mismo password en todas partes, esto sería peligroso).