* java.util.LinkedHashSet}. Generally speaking, this class reduces object allocation and memory
 * consumption at the price of moderately increased constant factors of CPU. Only use this class
 * when there is a specific reason to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 */
@GwtIncompatible // not worth using in GWT for now
@ElementTypesAreNonnullByDefault

instance/
.webassets-cache

# Scrapy stuff:
.scrapy

# Sphinx documentation
docs/_build/

# PyBuilder
target/

# Jupyter Notebook
.ipynb_checkpoints

# pyenv
.python-version

# celery beat schedule file
celerybeat-schedule

# SageMath parsed files
*.sage.py

# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/

# Spyder project settings
.spyderproject

FESS_LOG_PATH=${packaging.fess.log.dir}
FESS_CONF_PATH=${packaging.fess.conf.dir}
FESS_VAR_PATH=${packaging.fess.var.dir}

FESS_DICTIONARY_PATH=/var/lib/opensearch/config/

# Port
FESS_PORT=8080

# Heap Memory
FESS_HEAP_SIZE=512m

# Elasticsearch Path
SEARCH_ENGINE_HOME=/usr/share/opensearch/

# Elasticsearch URL

* 403: `status.HTTP_403_FORBIDDEN`
* etc.

It can be convenient to quickly access HTTP (and WebSocket) status codes in your app, using autocompletion for the name without having to remember the integer status codes by memory.

Read more about it in the [FastAPI docs about Response Status Code](https://fastapi.tiangolo.com/tutorial/response-status-code/).

## Example

```python
from fastapi import FastAPI, status

app = FastAPI()

* Modelos **SQLAlchemy** (independente de extensões Flask, para que eles possam ser usados com _workers_ Celery diretamente).
* Modelos básicos para usuários (modifique e remova conforme suas necessidades).
* Migrações **Alembic**.
* **CORS** (_Cross Origin Resource Sharing_ - Compartilhamento de Recursos Entre Origens).
* _Worker_ **Celery** que pode importar e usar modelos e códigos do resto do _backend_ seletivamente.

- Reduced server startup time. For IAM encryption with the root credentials, MinIO had
   to use a memory-hard function (Argon2) that (on purpose) consumes a lot of memory and CPU.
   The new KMS-based approach can use a key derivation function that is orders of magnitudes
   cheaper w.r.t. memory and CPU.
- Root credentials can now be changed easily. Before, a two-step process was required to

        "//tensorflow/core/distributed_runtime/rpc:rpc_rendezvous_mgr",
        "//tensorflow/core/distributed_runtime/rpc/eager:grpc_eager_client",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/strings:str_format",
        "@local_xla//xla/tsl/c:tsl_status_internal",
    ],
    alwayslink = 1,
)

filegroup(
    name = "pywrap_required_hdrs",
    srcs = [

    // we pad because the dummy hash function we use to test this, merely copies the input into
    // the output, so the input must be at least 32 bits, since the output has to be that long
    assertPutString(new char[] {'p', HashTestUtils.randomLowSurrogate(new Random())});
  }

  public void testPutStringWithHighSurrogate() {
    // we pad because the dummy hash function we use to test this, merely copies the input into

 */
package org.apache.maven.model.building;

import org.apache.maven.building.Source;

/**
 * Provides access to the contents of a POM independently of the backing store (e.g. file system, database, memory).
 * <p>
 * This interface does not support loading of parent POM(s) from the same backing store, integrators are strongly
 * encouraged to implement {@link ModelSource2} instead of implementing this interface directly.
 *

               "legendFormat": "Heap (Allocated) ({{pod}})"
            }
         ],
         "title": "Memory Usage",
         "type": "timeseries"
      },
      {
         "datasource": {
            "type": "datasource",
            "uid": "-- Mixed --"
         },
         "description": "Details about memory allocations",
         "fieldConfig": {
            "defaults": {
               "custom": {