* <p><b>Note:</b> in general, code should assume that the string form returned by {@code
     * ToStringHelper} for a given object may change. In particular, the list of types which are
     * checked for emptiness is subject to change. We currently check {@code CharSequence}s, {@code
     * Collection}s, {@code Map}s, optionals (including Guava's), and arrays.
     *
     * @since NEXT
     */
    @CanIgnoreReturnValue

Prefer to use the `Annotated` version if possible.

///

```Python hl_lines="3  77-79"
{!> ../../docs_src/security/tutorial003.py!}
```

////

### Check the password

At this point we have the user data from our database, but we haven't checked the password.

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.

    /*
     * Inputs are <every possible 10-character string of characters "a./">
     *
     * Expected outputs are generated by the code itself, but they've been
     * checked against the inputs under Bash in order to confirm that the two
     * forms are equivalent (though not necessarily minimal, though we hope this
     * to be the case). Thus, this test is more of a regression test.
     *

    /*
     * Inputs are <every possible 10-character string of characters "a./">
     *
     * Expected outputs are generated by the code itself, but they've been
     * checked against the inputs under Bash in order to confirm that the two
     * forms are equivalent (though not necessarily minimal, though we hope this
     * to be the case). Thus, this test is more of a regression test.
     *

| `minio_node_ilm_action_count_delete_action`                  | Total action outcome of lifecycle checks since server start for deleting object                            |

    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.
    * And validators allow complex data schemas to be clearly and easily defined, checked and documented as JSON Schema.
    * You can have deeply **nested JSON** objects and have them all validated and annotated.
* **Extensible**:

   to use a memory-hard function (Argon2) that (on purpose) consumes a lot of memory and CPU.
   The new KMS-based approach can use a key derivation function that is orders of magnitudes
   cheaper w.r.t. memory and CPU.
- Root credentials can now be changed easily. Before, a two-step process was required to
   change the cluster root credentials since they were used to en/decrypt the IAM data.

                        updateCheckManager.touch(metadata, repository, file);
                    }
                }

                // TODO should this be inside the above check?
                // touch file so that this is not checked again until interval has passed
                if (file.exists()) {
                    file.setLastModified(System.currentTimeMillis());
                }
            }
        }

		if output[0] == "" {
			// spurious blank caused by Split on "\n"
			output = output[1:]
			continue
		}
		t.Errorf("unexpected output: %q", output[0])
		output = output[1:]
	}

	// Checked printing.
	// Now check machine code layout.

	top := pList.Firstpc
	var text *obj.LSym
	ok = true
	ctxt.DiagFunc = func(format string, args ...interface{}) {
		t.Errorf(format, args...)
		ok = false
	}

    CharSource concatenated = CharSource.concat(cycle);

    String expected = "abcdabcd";

    // read the first 8 chars manually, since there's no equivalent to ByteSource.slice
    // TODO(cgdecker): Add CharSource.slice?
    StringBuilder builder = new StringBuilder();
    Reader reader = concatenated.openStream(); // no need to worry about closing
    for (int i = 0; i < 8; i++) {