```gradle
dependencies {
  // Pick one:

  // 1. Use Guava in your implementation only:
  implementation("com.google.guava:guava:33.4.8-jre")

  // 2. Use Guava types in your public API:
  api("com.google.guava:guava:33.4.8-jre")

  // 3. Android - Use Guava in your implementation only:
  implementation("com.google.guava:guava:33.4.8-android")

  // 4. Android - Use Guava types in your public API:
  api("com.google.guava:guava:33.4.8-android")

- To run `make test` and `make build` completes.

### Commit changes

After verification, commit your changes. This is a [great post](https://chris.beams.io/posts/git-commit/) on how to write useful commit messages

```
git commit -am 'Add some feature'
```

### Push to the branch

Push your locally committed changes to the remote origin (your fork)

```

After authenticating in the system, you will see it like:

<img src="/img/tutorial/security/image05.png">

### Get your own user data { #get-your-own-user-data }

Now use the operation `GET` with the path `/users/me`.

You will get your user's data, like:

```JSON
{
  "username": "johndoe",
  "email": "******@****.***",
  "full_name": "John Doe",
  "disabled": false,

to take away your freedom to share and change the works.  By contrast,
our General Public Licenses are intended to guarantee your freedom to
share and change all versions of a program--to make sure it remains free
software for all its users.

  When we speak of free software, we are referring to freedom, not
price.  Our General Public Licenses are designed to make sure that you

## Pin your `fastapi` version { #pin-your-fastapi-version }

The first thing you should do is to "pin" the version of **FastAPI** you are using to the specific latest version that you know works correctly for your application.

For example, let's say you are using version `0.112.0` in your app.

  recent activity. It will be closed after 15 days if no further activity
  occurs. Thank you for your contributions.
# Comment to post when removing the stale label.
# unmarkComment: >
#   Your comment here.

# Comment to post when closing a stale Issue or Pull Request.
# closeComment: >
#   Your comment here.

# Limit the number of actions per hour, from 1-30. Default is 30
limitPerRun: 1

# Limit to only `issues` or `pulls`

Because we are using a relative URL, if your API was located at `https://example.com/`, then it would refer to `https://example.com/token`. But if your API was located at `https://example.com/api/v1/`, then it would refer to `https://example.com/api/v1/token`.

///

## Run your code with your debugger { #run-your-code-with-your-debugger }

Because you are running the Uvicorn server directly from your code, you can call your Python program (your FastAPI application) directly from the debugger.

---

For example, in Visual Studio Code, you can:

* Go to the "Debug" panel.

### Server Memory { #server-memory }

For example, if your code loads a Machine Learning model with **1 GB in size**, when you run one process with your API, it will consume at least 1 GB of RAM. And if you start **4 processes** (4 workers), each will consume 1 GB of RAM. So in total, your API will consume **4 GB of RAM**.

If you have improvements to TensorFlow, send us your pull requests! For those
just getting started, GitHub has a
[how-to](https://help.github.com/articles/using-pull-requests/).

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are