// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License
// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package main

import (
	"bytes"
	"context"
	"crypto/tls"
	"encoding/json"
	"flag"
	"fmt"
	"log"
	"net/http"
	"net/url"
	"strings"

	minio "github.com/minio/minio-go/v7"

# (1)
COPY ./main.py /code/

# (2)
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "80"]
```

1. Скопируйте непосредственно файл `main.py` в директорию `/code` (не указывайте `./app`).

2. При запуске Uvicorn укажите ему, что объект `app` нужно импортировать из файла `main` (вместо импортирования из `app.main`).

      .assertNoMoreLogs()
  }

  private fun request(): Request.Builder = Request.Builder().url(url)

  companion object {
    private val PLAIN = "text/plain".toMediaType()
  }

import okhttp3.MediaType
import okhttp3.MediaType.Companion.toMediaTypeOrNull
import okhttp3.Request
import okhttp3.RequestBody.Companion.toRequestBody
import okhttp3.curl.Main
import okhttp3.internal.http.StatusLine
import okio.sink

internal fun Main.commonCreateRequest(): Request {
  val request = Request.Builder()

  val requestMethod = method ?: if (data != null) "POST" else "GET"

    requestBodySuccess(
      "Hello".toRequestBody("text/plain".toMediaType()),
      CoreMatchers.equalTo(5L),
      CoreMatchers.equalTo(19L),
    )
  }

  @Test
  fun requestBodySuccessHttp() {
    requestBodySuccess(
      "Hello".toRequestBody("text/plain".toMediaType()),
      CoreMatchers.equalTo(5L),
      CoreMatchers.equalTo(19L),
    )
  }

```

</div>

<details markdown="1">
<summary>Про команди <code>uvicorn main:app --reload</code>...</summary>

Команда `uvicorn main:app` посилається на:

* `main`: файл `main.py` ("Модуль" Python).
* `app`: об’єкт створений усередині `main.py` рядком `app = FastAPI()`.
* `--reload`: перезапускає сервер після зміни коду. Використовуйте виключно для розробки.

</details>

### Перевірте

        announceRandom()
        setInterval(announceRandom, timeInterval
        )
    }
}

async function main() {
    setupTermynal();
    showRandomAnnouncement('announce-left', 5000)
    showRandomAnnouncement('announce-right', 10000)
}
document$.subscribe(() => {
    main()

With **FastAPI** you can take advantage of concurrency that is very common for web development (the same main attraction of NodeJS).

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.

image/x-xwindowdump            xwd              #
text/css                       css              # Cascading Style Sheet
text/html                      html htm         # HTML Document
text/plain                     txt ini log in cfg m4 sh     # Plain Text File
text/richtext                  rtx              # Rich Text File
text/tab-separated-values      tsv              #
text/x-setext                  etx              #

  </expression>
  <expression>
    <syntax>project.attachedArtifacts</syntax>
    <description>
      <![CDATA[
      This is a list of attachments to the main artifact produced by building the current POM.
      Attachments are derived works, based on the main build process, such as an ejb-client jar,
      project sources jar, etc.
    ]]></description>
  </expression>
</expressions>