# Virtual Environments

When you work in Python projects you probably should use a **virtual environment** (or a similar mechanism) to isolate the packages you install for each project.

/// info

If you already know about virtual environments, how to create them and use them, you might want to skip this section. 🤓

///

/// tip

A **virtual environment** is different than an **environment variable**.

Por exemplo:

* <a href="https://code.visualstudio.com/docs/python/environments#_select-and-activate-an-environment" class="external-link" target="_blank">VS Code</a>
* <a href="https://www.jetbrains.com/help/pycharm/creating-virtual-environment.html" class="external-link" target="_blank">PyCharm</a>

/// tip | "Dica"

## Conclusion

With this you should have a basic understanding of what **environment variables** are and how to use them in Python.

You can also read more about them in the <a href="https://en.wikipedia.org/wiki/Environment_variable" class="external-link" target="_blank">Wikipedia for Environment Variable</a>.

/install/                                                        @istio/wg-environments-maintainers
/istioctl/                                                       @istio/wg-user-experience-maintainers @istio/wg-networking-maintainers
Makefile*                                                        @istio/wg-test-and-release-maintainers
/manifests/                                                      @istio/wg-environments-maintainers

The install is organized in 'environments' - each environment consists of a set of components
in different namespaces that are configured to work together. Regardless of 'environment',
workloads can talk with each other and obey the Istio configuration resources, but each environment
can use different Istio versions and different configuration defaults.

<div class="termy">

```console
$ C:\opt\custompython\bin\python
```

</div>

////

Эта информация будет полезна при изучении [Виртуальных окружений](virtual-environments.md){.internal-link target=_blank}.

## Вывод

Благодаря этому вы должны иметь базовое представление о том, что такое **переменные окружения** и как использовать их в Python.

<div class="termy">

```console
$ C:\opt\custompython\bin\python
```

</div>

////

Deze informatie is handig wanneer je meer wilt weten over [virtuele omgevingen](virtual-environments.md){.internal-link target=_blank}.

## Conclusion

Hiermee heb je basiskennis van wat **omgevingsvariabelen** zijn en hoe je ze in Python kunt gebruiken.

about just retrofitting monolithic applications onto modern container based compute environment. A cloud-native application is portable and resilient by design, and can scale horizontally by simply replicating. Modern orchestration platforms like Kubernetes, DC/OS make replicating and managing containers in huge clusters easier than ever.

While containers provide isolated application execution environment, orchestration platforms allow seamless scaling by helping replicate and manage containers....

docs/_build/

# PyBuilder
target/

# Jupyter Notebook
.ipynb_checkpoints

# pyenv
.python-version

# celery beat schedule file
celerybeat-schedule

# SageMath parsed files
*.sage.py

# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/

# Spyder project settings
.spyderproject
.spyproject

# Rope project settings
.ropeproject

# mkdocs documentation
/site

## Using `TestClient`

/// info

To use `TestClient`, first install <a href="https://www.python-httpx.org" class="external-link" target="_blank">`httpx`</a>.

Make sure you create a [virtual environment](../virtual-environments.md){.internal-link target=_blank}, activate it, and then install it, for example:

```console
$ pip install httpx
```

///

Import `TestClient`.