the concept of a Project Object Model (POM), Maven can manage a project's
  build, reporting and documentation from a central piece of information.

  Documentation
  -------------

  The most up-to-date documentation can be found at https://maven.apache.org/.

  Release Notes
  -------------

  The full list of changes, system requirements and related can be found at https://maven.apache.org/docs/history.html.

* Even dependencies can have dependencies, creating a hierarchy or **"graph" of dependencies**.
* All **automatically handled** by the framework.
* All the dependencies can require data from requests and **augment the path operation** constraints and automatic documentation.

```JSON
{
  "detail": "Item not found"
}
```

/// tip

When raising an `HTTPException`, you can pass any value that can be converted to JSON as the parameter `detail`, not only `str`.

You could pass a `dict`, a `list`, etc.

They are handled automatically by **FastAPI** and converted to JSON.

///

    // merged into POM being built. Once the POM builder has this plugin information, versions can be assigned
    // by the POM builder because they will have to be defined in plugin management. Once this is setComplete then it
    // can be passed back so that the default configuration information can be populated.
    //
    // We need to know the specific version so that we can look up the right version of the plugin descriptor

   * {@code throws} clause: Some such methods can in fact throw a checked exception (e.g., by
   * calling code written in Kotlin).) Typically, we want to let a {@link Throwable} from such a
   * method propagate untouched, just as we'd typically let it do for a non-reflective call.
   * However, we can't usually write {@code throw t;} when {@code t} has a static type of {@link
   * Throwable}. But we <i>can</i> write {@code sneakyThrow(t);}.
   *

    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

We can do better...

## What makes a dependency { #what-makes-a-dependency }

Up to now you have seen dependencies declared as functions.

But that's not the only way to declare dependencies (although it would probably be the more common).

The key factor is that a dependency should be a "callable".

A "**callable**" in Python is anything that Python can "call" like a function.

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...

# Test Client - `TestClient`

You can use the `TestClient` class to test FastAPI applications without creating an actual HTTP and socket connection, just communicating directly with the FastAPI code.

Read more about it in the [FastAPI docs for Testing](https://fastapi.tiangolo.com/tutorial/testing/).

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

```python
from fastapi.testclient import TestClient
```

### Concurrency + Parallelism: Web + Machine Learning { #concurrency-parallelism-web-machine-learning }

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.