return ItemOut(name=item.name, value=item.value, dep=dep)


@app.post("/sync/large-receive")
def sync_large_receive(payload: LargeIn):
    return {"received": len(payload.items)}


@app.post("/async/large-receive")
async def async_large_receive(payload: LargeIn):
    return {"received": len(payload.items)}


@app.get("/sync/large-dict-no-response-model")
def sync_large_dict_no_response_model():

        searchBody.put("size", 100);
        searchBody.put("q", NAME_PREFIX + "large_*");

        String response = checkMethodBase(searchBody).get(SEARCHLIST_API_PATH + "/docs").asString();
        List<Map<String, Object>> docs = JsonPath.from(response).getList("response.docs");

        logger.info("Created large set of documents: {} documents", docs.size());

        }
    }

    @Test
    public void test_execute_withVeryLargeBoost() {
        // Test executing BoostQuery with very large boost value
        Term term = new Term("field", "large");
        TermQuery termQuery = new TermQuery(term);
        BoostQuery boostQuery = new BoostQuery(termQuery, Float.MAX_VALUE);

        QueryContext context = new QueryContext("test", false);

from fastapi import FastAPI
from fastapi.responses import StreamingResponse

some_file_path = "large-video-file.mp4"
app = FastAPI()


@app.get("/")
def main():
    def iterfile():  # (1)
        with open(some_file_path, mode="rb") as file_like:  # (2)
            yield from file_like  # (3)

        String result3 = aggregateLogJob.execute();
        assertEquals("", result3);
    }

    @Test
    public void test_execute_performanceWithLargeErrorMessage() {
        // Test with very large error message
        final StringBuilder largeMessage = new StringBuilder();
        for (int i = 0; i < 1000; i++) {
            largeMessage.append("Error detail ").append(i).append(" ");
        }

	opReadRune4 readOp = 4  // Read rune of size 4.
)

// ErrTooLarge is passed to panic if memory cannot be allocated to store data in a buffer.
var ErrTooLarge = errors.New("bytes.Buffer: too large")
var errNegativeRead = errors.New("bytes.Buffer: reader returned negative count from Read")

const maxInt = int(^uint(0) >> 1)

// Bytes returns a slice of length b.Len() holding the unread portion of the buffer.

* It uses a "spooled" file:
    * A file stored in memory up to a maximum size limit, and after passing this limit it will be stored in disk.
* This means that it will work well for large files like images, videos, large binaries, etc. without consuming all the memory.
* You can get metadata from the uploaded file.
* It has a [file-like](https://docs.python.org/3/glossary.html#term-file-like-object) `async` interface.

from fastapi import FastAPI
from fastapi.responses import FileResponse

some_file_path = "large-video-file.mp4"
app = FastAPI()


@app.get("/")
async def main():

from fastapi import FastAPI
from fastapi.responses import FileResponse

some_file_path = "large-video-file.mp4"
app = FastAPI()


@app.get("/", response_class=FileResponse)
async def main():

  "durations" : [ {
    "testProject" : "excludeRuleMergingBuild",
    "linux" : 233
  } ]
}, {
  "scenario" : "org.gradle.performance.regression.corefeature.LargeDependencyGraphPerformanceTest.resolve large dependency graph (parallel = false, locking = true)",
  "durations" : [ {