mapreduce.reduce.shuffle.merge.percent=0.9 # Minimum % merges in RAM
mapreduce.reduce.speculative=false # Disable speculation for reducing
mapreduce.task.io.sort.factor=999 # Threshold before writing to disk
mapreduce.task.sort.spill.percent=0.9 # Minimum % before spilling to disk
```

could discard <code>i</code> without saving a copy and then reload
<code>i = *p</code> just before
<code>funcs[i]()</code>.
A Go compiler must not, because the value of <code>*p</code> may have changed.
(Instead, the compiler could spill <code>i</code> to the stack.)
</p>

<p>
Not allowing a single write to write multiple values also means not using
the memory where a local variable will be written as temporary storage before the write.

            }
        }, "Multiple close operations should not cause issues");

        // Verify iterator still works after multiple closes
        assertFalse(emptyIterator.hasNext(), "Iterator should still work after multiple closes");
        assertNull(emptyIterator.next(), "Iterator should still return null after multiple closes");
    }

    @Test

        // Test additional acquire
        session.acquire();
        assertTrue(session.isInUse(), "Session should still be in use after additional acquire");

        // Test release (still in use because of initial transport acquire)
        session.release();
        assertTrue(session.isInUse(), "Session should still be in use after one release");

        // Test final release
        session.release();

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

{* ../../docs_src/dataclasses/tutorial003.py hl[1,5,8:11,14:17,23:25,28] *}

1. We still import `field` from standard `dataclasses`.

            // Execute
            TimeZone result = newProvider.getRequestedTimeZone(requestManager);

            // Verify that the provider still returns the static centralTimeZone
            assertNotNull(result);
            assertEquals(FessUserTimeZoneProcessProvider.centralTimeZone, result);
            assertNotSame(newTimeZone, result);
        } finally {

**FastAPI** is already being used in production in many applications and systems. And the test coverage is kept at 100%. But its development is still moving quickly.

New features are added frequently, bugs are fixed regularly, and the code is still continuously improving.

        request.addHeader("Host", "example.com");
        key = virtualHostHelper.getVirtualHostKey();
        assertEquals("", key); // Still empty due to caching

        // Test caching by calling again - should return cached value
        key = virtualHostHelper.getVirtualHostKey();
        assertEquals("", key); // Still cached value
    }

    public void test_getVirtualHostKey_withCaching() {

For example, imagine that you want to return an HTTP status code of "OK" `200` by default.

But if the data didn't exist, you want to create it, and return an HTTP status code of "CREATED" `201`.

But you still want to be able to filter and convert the data you return with a `response_model`.

For those cases, you can use a `Response` parameter.

## Use a `Response` parameter { #use-a-response-parameter }

## Why is Erasure Code useful?