* Any program, any code, **can only do things** when it is being **executed**. So, when there's a **process running**.
* The process can be **terminated** (or "killed") by you, or by the operating system. At that point, it stops running/being executed, and it can **no longer do things**.

    once you get into the running container so `bazel` can find the `tensorflow`
    workspace).

    you can do this by using the following command. As an example-

    ```bash
    docker run -it --rm -v $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10
    ```

    Once you have the packages installed, you can run a specific unit test in
    bazel by doing as follows:

    ```bash

# ==============================================================================
cat <<EOF
IMPORTANT: These tests ran under docker. This script does not clean up the
container for you! You can delete the container with:

$ docker rm -f tf

You can also execute more commands within the container with e.g.:

$ docker exec tf bazel clean
$ docker exec -it tf bash
EOF

- Once object lock configuration is set to a bucket
  - New objects inherit the retention settings of the bucket object lock configuration automatically
  - Retention headers can be optionally set while uploading objects
  - Once objects are uploaded PutObjectRetention API can be called to change retention settings

	// value of true indicates that the list was truncated. The list can be truncated
	// if the number of objects exceeds the limit allowed or specified
	// by max keys.
	IsTruncated bool

	// When response is truncated (the IsTruncated element value in the response is true),
	// you can use the key name in this field as marker in the subsequent
	// request to get next set of objects.
	//

goes offline and replays it when the broker comes back online. The event store can be configured by setting the directory path in `queue_dir` field and the maximum limit of events in the queue_dir in `queue_limit` field. For eg, the `queue_dir` can be `/home/events` and `queue_limit` can be `1000`. By default, the `queue_limit` is set to 100000.

If Elasticsearch has authentication enabled, the credentials can be supplied to MinIO via the `url` parameter formatted as `PROTO://USERNAME:P...

# Templating - `Jinja2Templates`

You can use the `Jinja2Templates` class to render Jinja templates.

Read more about it in the [FastAPI docs for Templates](https://fastapi.tiangolo.com/advanced/templates/).

You can import it directly from `fastapi.templating`:

```python
from fastapi.templating import Jinja2Templates
```

# `UploadFile` class

You can define *path operation function* parameters to be of the type `UploadFile` to receive files from the request.

You can import it directly from `fastapi`:

```python
from fastapi import UploadFile
```

::: fastapi.UploadFile
    options:
        members:
            - file
            - filename
            - size
            - headers
            - content_type
            - read

We could do better.

We can declare a `UserBase` model that serves as a base for our other models. And then we can make subclasses of that model that inherit its attributes (type declarations, validation, etc).

All the data conversion, validation, documentation, etc. will still work as normally.

import com.google.errorprone.annotations.CanIgnoreReturnValue;
import org.jspecify.annotations.Nullable;

/**
 * A {@link ListenableFuture} whose result can be set by a {@link #set(Object)}, {@link
 * #setException(Throwable)} or {@link #setFuture(ListenableFuture)} call. It can also, like any
 * other {@code Future}, be {@linkplain #cancel cancelled}.
 *