"aliases" : { },
    "mappings" : {
      "data_config" : {
        "properties" : {
          "available" : {
            "type" : "boolean"
          },
          "boost" : {
            "type" : "float"
          },
          "createdBy" : {
            "type" : "keyword"
          },
          "createdTime" : {
            "type" : "long"
          },
          "description" : {
            "type" : "text"

# `auditlog-echo`: A tool to view MinIO Audit logs on the console

1. Run the tool with:

```
go run docs/auditlog/auditlog-echo.go
```

The listen port has a default value (8080), but can be set with the `-port` flag.

2. Configure audit logging in MinIO with for example:

```
mc admin config set myminio audit_webhook enable=on endpoint=http://localhost:8080
```

    }

    public void setBoost_Equal(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Equal(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {
        setBoost_Term(boost, opLambda);
    }

    public void setBoost_Term(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Term(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {

    /** The total number of pages based on the page size and total record count. */
    protected int allPageCount;

    /** Flag indicating whether there is a next page available. */
    protected boolean existNextPage;

    /** Flag indicating whether there is a previous page available. */
    protected boolean existPrevPage;

    /** The record number of the first record on the current page (1-based). */

from fastapi import FastAPI
from fastapi.sse import EventSourceResponse, ServerSentEvent
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float


items = [
    Item(name="Plumbus", price=32.99),
    Item(name="Portal Gun", price=999.99),
    Item(name="Meeseeks Box", price=49.99),
]


@app.get("/items/stream", response_class=EventSourceResponse)

* Data conversion
* Data validation
* Automatic documentation

## Special types and validation { #special-types-and-validation }

Apart from normal singular types like `str`, `int`, `float`, etc. you can use more complex singular types that inherit from `str`.

from fastapi import FastAPI
from fastapi.temp_pydantic_v1_params import Body
from pydantic.v1 import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None
    size: float


app = FastAPI()


@app.post("/items/")
async def create_item(item: Annotated[Item, Body(embed=True)]) -> Item:

    assertThat(primitives)
        .containsExactly(
            boolean.class,
            byte.class,
            char.class,
            double.class,
            float.class,
            int.class,
            long.class,
            short.class,
            void.class);

    assertThrows(UnsupportedOperationException.class, () -> primitives.remove(boolean.class));
  }

    private static final int MAX_LOOP_COUNT = 10;

    /** The thread being monitored. */
    protected Thread runningThread;

    /** Flag indicating if the thread is still running. */
    protected AtomicBoolean running = new AtomicBoolean();

    /**
     * Constructs an AccessTimeoutTarget with the specified thread.
     * @param thread The thread to monitor.

}

unsigned char TF_GetXlaAutoJitEnabled() {
  tensorflow::XlaAutoJitFlag flag =
      tensorflow::GetMarkForCompilationPassFlags()->xla_auto_jit_flag;
  return static_cast<unsigned char>(flag.optimization_level_single_gpu > 0 ||
                                    flag.optimization_level_general > 0);
}

unsigned char TF_GetXlaConstantFoldingDisabled() {
  return static_cast<unsigned char>(