public void testSlice_constrainedRange() throws IOException {
    long size = source.read().length;
    if (size >= 2) {
      ByteSource sliced = source.slice(1, size - 2);
      assertEquals(size - 2, sliced.read().length);
      ByteSource resliced = sliced.slice(0, size - 1);
      assertTrue(sliced.contentEquals(resliced));
    }
  }

    }

    /**
     * Get the maximum size for RDMA read/write operations
     *
     * @return maximum read/write size in bytes
     */
    public int getMaxReadWriteSize() {
        return maxReadWriteSize;
    }

    /**
     * Set the maximum size for RDMA read/write operations
     *
     * @param maxReadWriteSize maximum read/write size in bytes
     */

You could use this if you want to stream pure strings, for example directly from the output of an **AI LLM** service.

You could also use it to stream **large binary files**, where you stream each chunk of data as you read it, without having to read it all in memory at once.

You could also stream **video** or **audio** this way, it could even be generated as you process and send it.

## A `StreamingResponse` with `yield` { #a-streamingresponse-with-yield }

from inline_snapshot import snapshot
from pydantic import BaseModel

app = FastAPI()

reusable_oauth2 = OAuth2(
    flows={
        "password": {
            "tokenUrl": "token",
            "scopes": {"read:users": "Read the users", "write:users": "Create users"},
        }
    }
)


class User(BaseModel):
    username: str


# Here we use string annotations to test them

from inline_snapshot import snapshot
from pydantic import BaseModel

app = FastAPI()

reusable_oauth2 = OAuth2(
    flows={
        "password": {
            "tokenUrl": "token",
            "scopes": {"read:users": "Read the users", "write:users": "Create users"},
        }
    },
    description="OAuth2 security scheme",
    auto_error=False,
)


class User(BaseModel):
    username: str

            if (cur == null) {
                break;
            }
            cur.decode(buffer, bufferIndex, bufferLength);
            infos.add(cur);
            final int nextEntryOffset = cur.getNextEntryOffset();
            if (nextEntryOffset <= 0) {
                break;
            }
            bufferIndex += nextEntryOffset;

				Object: object,
			}
			break
		}
		err = BucketNotFound{Bucket: bucket}
	case "conflict":
		if message == "You already own this bucket. Please select another name." {
			err = BucketAlreadyOwnedByYou{Bucket: bucket}
			break
		}
		if message == "Sorry, that name is not available. Please try a different one." {
			err = BucketAlreadyExists{Bucket: bucket}
			break
		}
		err = BucketNotEmpty{Bucket: bucket}

import org.jspecify.annotations.NullMarked;

/**
 * A Ticker whose value can be advanced programmatically in test.
 *
 * <p>The ticker can be configured so that the time is incremented whenever {@link #read} is called:
 * see {@link #setAutoIncrementStep}.
 *
 * <p>This class is thread-safe.
 *
 * @author Jige Yu
 * @since 10.0
 */
@NullMarked
@GwtCompatible
public class FakeTicker extends Ticker {

password_hash = PasswordHash.recommended()

DUMMY_HASH = password_hash.hash("dummypassword")

oauth2_scheme = OAuth2PasswordBearer(
    tokenUrl="token",
    scopes={"me": "Read information about the current user.", "items": "Read items."},
)

app = FastAPI()


def verify_password(plain_password, hashed_password):
    return password_hash.verify(plain_password, hashed_password)

 * <p>{@link #processLine} will be called for each line that is read, and should return {@code
 * false} when you want to stop processing.
 *
 * @author Miles Barr
 * @since 1.0
 */
@J2ktIncompatible
@GwtIncompatible
public interface LineProcessor<T extends @Nullable Object> {

  /**
   * This method will be called once for each line.
   *
   * @param line the line read from the input, without delimiter