# Lazy-load Keras v1.
_tf_uses_legacy_keras = (
    _os.environ.get("TF_USE_LEGACY_KERAS", None) in ("true", "True", "1"))
setattr(_current_module, "keras", _KerasLazyLoader(globals(), mode="v1"))
_module_dir = _module_util.get_parent_dir_for_name("keras._tf_keras.keras")
_current_module.__path__ = [_module_dir] + _current_module.__path__
if _tf_uses_legacy_keras:

CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80"]
```

1. Inicie a partir da imagem base oficial do Python.

2. Defina o diretório de trabalho atual para `/code`.

    Esse é o diretório onde colocaremos o arquivo `requirements.txt` e o diretório `app`.

3. Copie o arquivo com os requisitos para o diretório `/code`.

    Copie **somente** o arquivo com os requisitos primeiro, não o resto do código.

    }

    /*
     * static class SynInfo { final String src; final int offset, length; final String[] synonyms; Mode mode; int count;
     * SynInfo(String src, int offset, int length, String[] synonyms){ this.src = src; this.offset = offset; this.length
     * = length; this.synonyms = synonyms; }
     *
     * static enum Mode { PREV, SYN, AFTER; } }
     */

    static class MyTokensComparator implements Comparator<MyToken> {

fs.s3a.block.size=512M
fs.s3a.buffer.dir=${hadoop.tmp.dir}/s3a
fs.s3a.committer.magic.enabled=false
fs.s3a.committer.name=directory
fs.s3a.committer.staging.abort.pending.uploads=true
fs.s3a.committer.staging.conflict-mode=append
fs.s3a.committer.staging.tmp.path=/tmp/staging
fs.s3a.committer.staging.unique-filenames=true
fs.s3a.connection.establish.timeout=5000
fs.s3a.connection.ssl.enabled=false
fs.s3a.connection.timeout=200000

                  "calculation": {
                     "xBuckets": {
                        "mode": "size",
                        "value": "1min"
                     }
                  },
                  "cellGap": 2,
                  "color": {
                     "mode": "scheme",
                     "scheme": "Spectral",
                     "steps": 128
                  },

from typing import Union

from fastapi import BackgroundTasks, Depends, FastAPI

app = FastAPI()


def write_log(message: str):
    with open("log.txt", mode="a") as log:
        log.write(message)


def get_query(background_tasks: BackgroundTasks, q: Union[str, None] = None):
    if q:
        message = f"found query: {q}\n"
        background_tasks.add_task(write_log, message)
    return q

MinIO in distributed mode lets you pool multiple drives (even on different machines) into a single object storage server. As drives are distributed across several nodes, distributed MinIO can withstand multiple node failures and yet ensure full data protection.

## Why distributed MinIO?

from fastapi import BackgroundTasks, FastAPI

app = FastAPI()


def write_notification(email: str, message=""):
    with open("log.txt", mode="w") as email_file:
        content = f"notification for {email}: {message}"
        email_file.write(content)


@app.post("/send-notification/{email}")
async def send_notification(email: str, background_tasks: BackgroundTasks):

 */

package com.google.common.io;

import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;

/**
 * Modes for opening a file for writing. The default when mode when none is specified is to truncate
 * the file before writing.
 *
 * @author Colin Decker
 */
@J2ktIncompatible
@GwtIncompatible
@ElementTypesAreNonnullByDefault
public enum FileWriteMode {

      - uses: actions/setup-java@v4
        with:
          java-version: 17
          distribution: 'temurin'
          cache: 'maven'

      - name: Set up Maven
        run:
          mvn --errors --batch-mode --show-version org.apache.maven.plugins:maven-wrapper-plugin:3.3.2:wrapper "-Dmaven=3.9.7"

      - name: Build with Maven
        run: ./mvnw verify -e -B -V -DdistributionFileName=apache-maven