client it will error out if you have any **mismatch** in the data used.

So, you would **detect many errors** very early in the development cycle instead of having to wait for the errors to show up to your final users in production and then trying to debug where the problem is. ✨...

And if your remote server or virtual machine only has 3 GB of RAM, trying to load more than 4 GB of RAM will cause problems. 🚨

### Multiple Processes - An Example

In this example, there's a **Manager Process** that starts and controls two **Worker Processes**.

### Upgrades

* 📌 Update minimum version of Pydantic to >=1.7.4. This fixes an issue when trying to use an old version of Pydantic. PR [#9567](https://github.com/tiangolo/fastapi/pull/9567) by [@Kludex](https://github.com/Kludex).

### Refactors

* In many cases, it's better to understand their **underlying problem or use case**, because there might be a better way to solve it than what they are trying to do.

### Ask to close

If they reply, there's a high chance you would have solved their problem, congrats, **you're a hero**! 🦸

* Now, if that solved their problem, you can ask them to:

And then it just returns a `dict` containing those values.

!!! info
    FastAPI added support for `Annotated` (and started recommending it) in version 0.95.0.

    If you have an older version, you would get errors when trying to use `Annotated`.

    Make sure you [Upgrade the FastAPI version](../../deployment/versions.md#upgrading-the-fastapi-versions){.internal-link target=_blank} to at least 0.95.1 before using `Annotated`.

### Import `Depends`

It would take the same amount of time to finish with or without turns (concurrency) and you would have done the same amount of work.

But in this case, if you could bring the 8 ex-cashier/cooks/now-cleaners, and each one of them (plus you) could take a zone of the house to clean it, you could do all the work in **parallel**, with the extra help, and finish much sooner.

Pydantic's `orm_mode` will tell the Pydantic *model* to read the data even if it is not a `dict`, but an ORM model (or any other arbitrary object with attributes).

This way, instead of only trying to get the `id` value from a `dict`, as in:

```Python
id = data["id"]
```

it will also try to get it from an attribute, as in:

```Python
id = data.id
```

So, if your application consumes a lot of memory (for example with machine learning models), and your server has a lot of CPU cores **but little memory**, then your container could end up trying to use more memory than what is available, and degrading performance a lot (or even crashing). 🚨

### Create a `Dockerfile`

Here's how you would create a `Dockerfile` based on this image:

```Dockerfile