Requirements
------------

OkHttp works on Android 5.0+ (API level 21+) and Java 8+.

OkHttp depends on [Okio][okio] for high-performance I/O and the [Kotlin standard library][kotlin]. Both are small libraries with strong backward-compatibility.

We highly recommend you keep OkHttp up-to-date. As with auto-updating web browsers, staying current
with HTTPS clients is an important defense against potential security problems. [We

# Guava: Google Core Libraries for Java

[![Latest release](https://img.shields.io/github/release/google/guava.svg)](https://github.com/google/guava/releases/latest)
[![Build Status](https://github.com/google/guava/workflows/CI/badge.svg?branch=master)](https://github.com/google/guava/actions)
[![OpenSSF Best Practices](https://bestpractices.coreinfrastructure.org/projects/7197/badge)](https://bestpractices.coreinfrastructure.org/projects/7197)

* [Building Java Libraries](https://docs.gradle.org/current/samples/sample_building_java_libraries.html)
* [Building Groovy Applications](https://docs.gradle.org/current/samples/sample_building_groovy_applications.html)
* [Building Groovy Libraries](https://docs.gradle.org/current/samples/sample_building_groovy_libraries.html)

# Guava Testlib: Google Testing Libraries for Java

Guava testlib is a set of Java classes for more convenient
unit testing.

## Adding Guava Testlib to your build

Guava testlib's Maven group ID is `com.google.guava` and its artifact ID is `guava-testlib`.

To add a dependency on Guava testlib using Maven, use the following:

```xml
<dependency>
  <groupId>com.google.guava</groupId>
  <artifactId>guava-testlib</artifactId>

[TensorFlow](https://www.tensorflow.org/) is an end-to-end open source platform
for machine learning. It has a comprehensive, flexible ecosystem of
[tools](https://www.tensorflow.org/resources/tools),
[libraries](https://www.tensorflow.org/resources/libraries-extensions), and
[community](https://www.tensorflow.org/community) resources that lets
researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

* More advanced (but equally easy) techniques for declaring **deeply nested JSON models** (thanks to Pydantic).
* **GraphQL** integration with <a href="https://strawberry.rocks" class="external-link" target="_blank">Strawberry</a> and other libraries.
* Many extra features (thanks to Starlette) as:
    * **WebSockets**
    * extremely easy tests based on HTTPX and `pytest`
    * **CORS**
    * **Cookie Sessions**
    * ...and more.

## Performance