private NameServiceClientImpl nameServiceClient;

    @BeforeEach
    void setUp() throws UnknownHostException {
        // Configure mock context with fast timeouts
        when(mockContext.getConfig()).thenReturn(mockConfig);

        // Setup configuration with minimal timeouts for fast testing
        when(mockConfig.getNetbiosSoTimeout()).thenReturn(100); // Very short timeout

fs.s3a.committer.threads=2048 # Number of threads writing to MinIO
fs.s3a.connection.maximum=8192 # Maximum number of concurrent conns
fs.s3a.fast.upload.active.blocks=2048 # Number of parallel uploads
fs.s3a.fast.upload.buffer=disk # Use disk as the buffer for uploads
fs.s3a.fast.upload=true # Turn on fast upload mode
fs.s3a.max.total.tasks=2048 # Maximum number of parallel tasks
fs.s3a.multipart.size=512M # Size of each multipart chunk

        NetworkInterfaceInfo basic = new NetworkInterfaceInfo(testAddress, 1000);
        assertEquals(1000, basic.getScore()); // Base score is link speed

        NetworkInterfaceInfo fast = new NetworkInterfaceInfo(testAddress, 10000);
        assertTrue(fast.getScore() > basic.getScore());
    }

    @Test
    void testCapabilitySettings() {
        NetworkInterfaceInfo info = new NetworkInterfaceInfo(testAddress, 1000);

Anyway, in any of the cases above, FastAPI will still work asynchronously and be extremely fast.

But by following the steps above, it will be able to do some performance optimizations.

## Technical Details { #technical-details }

    RDMA_WRITE,

    /**
     * Traditional send/receive with RDMA
     */
    RDMA_SEND_RECEIVE,

    /**
     * Dynamic memory registration
     */
    MEMORY_REGISTRATION,

    /**
     * Fast memory region registration
     */
    FAST_REGISTRATION

---

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python based on standard Python type hints.

The key features are:

* **Fast**: Very high performance, on par with **NodeJS** and **Go** (thanks to Starlette and Pydantic). [One of the fastest Python frameworks available](#performance).
* **Fast to code**: Increase the speed to develop features by about 200% to 300%. *

        System.out.printf("  Avg allocation time: %.2f ns%n", avgAllocTimeNs);
        System.out.printf("  Avg release time: %.2f ns%n", avgReleaseTimeNs);

        // Verify O(1) performance - should be reasonably fast (allowing for JVM overhead)
        assertTrue(avgAllocTimeNs < 10000, "Average allocation should be under 10000ns (O(1) performance)");

Le fast-food a 8 processeurs (serveurs/cuisiniers) 👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳. Alors que le fast-food de burgers concurrents en avait 2 (un serveur et un cuisinier).

Et pourtant l'expérience finale n'est pas meilleure 😞.

---

   * @return this for the builder pattern
   */
  @CanIgnoreReturnValue
  public ThreadFactoryBuilder setNameFormat(String nameFormat) {
    String unused = format(nameFormat, 0); // fail fast if the format is bad or null
    this.nameFormat = nameFormat;
    return this;
  }

  /**
   * Sets daemon or not for new threads created with this ThreadFactory.
   *

        python-version:
          - "3.13"
          - "3.12"
          - "3.11"
          - "3.10"
          - "3.9"
          - "3.8"
        pydantic-version: ["pydantic-v1", "pydantic-v2"]
      fail-fast: false
    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"
      - uses: actions/checkout@v5
      - name: Set up Python