//go:build darwin || dragonfly || freebsd || illumos || linux || netbsd || openbsd

// This program can be used as go_android_GOARCH_exec by the Go tool.
// It executes binaries on an android device using adb.
package main

import (
	"bytes"
	"errors"
	"fmt"
	"io"
	"log"
	"os"
	"os/exec"
	"os/signal"
	"path"
	"path/filepath"
	"regexp"
	"runtime"
	"strconv"
	"strings"
	"sync"
	"syscall"
)

// 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"
	"crypto/md5"
	"encoding/base64"
	"encoding/binary"
	"encoding/hex"
	"encoding/json"
	"errors"
	"fmt"
	"io"
	"log"
	"os"
	"path/filepath"
	"regexp"
	"slices"

Klaus Post <******@****.***> 1756435188 +0200

jiuker <******@****.***> 1748359116 +0800

Production'da nasıl oldugunu görmek için şu bölüme bakın [Deployment](deployment/index.md){.internal-link target=_blank}.

## `async` ve `await`

 [AccessHeadersJava]: https://github.com/square/okhttp/blob/master/samples/guide/src/main/java/okhttp3/recipes/AccessHeaders.java
 [AccessHeadersKotlin]: https://github.com/square/okhttp/blob/master/samples/guide/src/main/java/okhttp3/recipes/kt/AccessHeaders.kt
 [PostStringJava]: https://github.com/square/okhttp/blob/master/samples/guide/src/main/java/okhttp3/recipes/PostString.java

You can use simple tools like `htop` to see the CPU and RAM used in your server or the amount used by each process. Or you can use more complex monitoring tools, which may be distributed across servers, etc.

## Recap { #recap }

---

"_We hebben de **FastAPI** library gebruikt om een **REST** server te maken die bevraagd kan worden om **voorspellingen** te maken. [voor Ludwig]_"

RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

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

# (2)!
CMD ["fastapi", "run", "main.py", "--port", "80"]
```

1. Copy the `main.py` file to the `/code` directory directly (without any `./app` directory).

2. Use `fastapi run` to serve your application in the single file `main.py`.

Given the simplicity of Flask, it seemed like a good match for building APIs. The next thing to find was a "Django REST Framework" for Flask.

/// check | Inspired **FastAPI** to

Be a micro-framework. Making it easy to mix and match the tools and parts needed.

Have a simple and easy to use routing system.

///

### <a href="https://requests.readthedocs.io" class="external-link" target="_blank">Requests</a> { #requests }