{"a/b/c/", 159},
		{"/a/b/c", 96},
		{string([]byte{0xff, 0xfe, 0xfd}), 147},
	}

	// Tests hashing order to be consistent.
	for i, testCase := range testCases {
		if sipHashElement := hashKey("SIPMOD", testCase.objectName, 200, testUUID); sipHashElement != testCase.sipHash {
			t.Errorf("Test case %d: Expected \"%v\" but failed \"%v\"", i+1, testCase.sipHash, sipHashElement)
		}
	}

        }
        if (!bits.get(combinedHash % bitSize)) {
          return false;
        }
      }
      return true;
    }
  },
  /**
   * This strategy uses all 128 bits of {@link Hashing#murmur3_128} when hashing. It looks different
   * from the implementation in MURMUR128_MITZ_32 because we're avoiding the multiplication in the
   * loop and doing a (much simpler) += hash2. We're also changing the index to a positive number by

  }

  public void testHash_hashesCorrectly() throws Exception {
    byte[] buf = new byte[] {'y', 'a', 'm', 's'};
    HashCode expectedHash = Hashing.md5().hashBytes(buf);
    HashingOutputStream out = new HashingOutputStream(Hashing.md5(), buffer);

    out.write(buf);

    assertEquals(expectedHash, out.hash());
  }

  public void testChecksForNull() throws Exception {

   * double the index of the entry in entrySet.asList.)
   *
   * The basic data structure is described in https://en.wikipedia.org/wiki/Open_addressing.
   * The pointer to a key is stored in hashTable[Hashing.smear(key.hashCode()) % table.length],
   * save that if that location is already full, we try the next index, and the next, until we
   * find an empty table position.  Since the table has a power-of-two size, we use

/* HMACT64 keyed hashing algorithm
 * Copyright (C) 2003 "Eric Glass" <jcifs at samba dot org>
 *
 * This library is free software; you can redistribute it and/or
 * modify it under the terms of the GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful,

/* HMACT64 keyed hashing algorithm
 * Copyright (C) 2003 "Eric Glass" <jcifs at samba dot org>
 *
 * This library is free software; you can redistribute it and/or
 * modify it under the terms of the GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful,

# OAuth2 mit Password (und Hashing), Bearer mit JWT-Tokens

Da wir nun über den gesamten Sicherheitsablauf verfügen, machen wir die Anwendung tatsächlich sicher, indem wir <abbr title="JSON Web Tokens">JWT</abbr>-Tokens und sicheres Passwort-Hashing verwenden.

Diesen Code können Sie tatsächlich in Ihrer Anwendung verwenden, die Passwort-Hashes in Ihrer Datenbank speichern, usw.

Wir bauen auf dem vorherigen Kapitel auf.

## Über JWT

///

## Password hashing

"Hashing" means converting some content (a password in this case) into a sequence of bytes (just a string) that looks like gibberish.

Whenever you pass exactly the same content (exactly the same password) you get exactly the same gibberish.

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

### Why use password hashing

Let's put that data in the Pydantic `UserInDB` model first.

You should never save plaintext passwords, so, we'll use the (fake) password hashing system.

If the passwords don't match, we return the same error.

#### Password hashing

"Hashing" means: converting some content (a password in this case) into a sequence of bytes (just a string) that looks like gibberish.

Sie sollten niemals Klartext-Passwörter speichern, daher verwenden wir ein (gefaktes) Passwort-Hashing-System.

Wenn die Passwörter nicht übereinstimmen, geben wir denselben Fehler zurück.

#### Passwort-Hashing

„Hashing“ bedeutet: Konvertieren eines Inhalts (in diesem Fall eines Passworts) in eine Folge von Bytes (ein schlichter String), die wie Kauderwelsch aussieht.