* authentication and authorization systems
* API usage monitoring systems
* response data injection systems
* etc.

## Simple and Powerful { #simple-and-powerful }

Although the hierarchical dependency injection system is very simple to define and use, it's still very powerful.

You can define dependencies that in turn can define dependencies themselves.

 * <p>
 * This package provides a set of annotations that control how objects are created,
 * managed and injected throughout Maven's execution lifecycle. The framework is designed
 * to be lightweight yet powerful, supporting various scopes of object lifecycle from
 * singleton instances to mojo-execution-scoped beans.
 * <p>
 * Key features include:
 * <ul>
 *   <li>Constructor, method, and field injection</li>

Upgrading to OkHttp 4
=====================

OkHttp 4.x upgrades our implementation language from Java to Kotlin and keeps everything else the
same. We’ve chosen Kotlin because it gives us powerful new capabilities while integrating closely
with Java.

We spent a lot of time and energy on retaining strict compatibility with OkHttp 3.x. We’re even
keeping the package name the same: `okhttp3`!

There are three kinds of compatibility we’re tracking:

////

## Recap { #recap }

Apart from all the fancy words used here, the **Dependency Injection** system is quite simple.

Just functions that look the same as the *path operation functions*.

But still, it is very powerful, and allows you to declare arbitrarily deeply nested dependency "graphs" (trees).

/// tip

All this might not seem as useful with these simple examples.

Interceptors
============

Interceptors are a powerful mechanism that can monitor, rewrite, and retry calls. Here's a simple interceptor that logs the outgoing request and the incoming response.

```java
class LoggingInterceptor implements Interceptor {
  @Override public Response intercept(Interceptor.Chain chain) throws IOException {
    Request request = chain.request();

    long t1 = System.nanoTime();

        users indicates that they really appreciate Guava's high power-to-weight ratio. It's
        important to us to keep Guava as easy to use and understand as we can. That means boiling
        features down to compact but powerful abstractions, and controlling feature bloat carefully.

  - type: textarea
    attributes:
      label: API(s)
      description: Which existing classes or methods do you want to improve?

 * [PersistentCookieJar](https://github.com/franmontiel/PersistentCookieJar): A persistent `CookieJar`.
 * ⬜️ [Picasso](https://github.com/square/picasso): A powerful image downloading and caching library for Android.
 * ⬜️ [Retrofit](https://github.com/square/retrofit): Type-safe HTTP client for Android and Java by Square.

They are, more or less, at opposite ends, complementing each other.

Requests has a very simple and intuitive design, it's very easy to use, with sensible defaults. But at the same time, it's very powerful and customizable.

That's why, as said in the official website:

> Requests is one of the most downloaded Python packages of all time

        users indicates that they really appreciate Guava's high power-to-weight ratio. It's
        important to us to keep Guava as easy to use and understand as we can. That means boiling
        features down to compact but powerful abstractions, and controlling feature bloat carefully.


        Guava's main yardstick for evaluating proposed features can be summed up as [utility times

### Saved graphs and checkpoints

When loading untrusted serialized computation graphs (in form of a `GraphDef`,
`SavedModel`, or equivalent on-disk format), the set of computation primitives
available to TensorFlow is powerful enough that you should assume that the
TensorFlow process effectively executes arbitrary code.

The risk of loading untrusted checkpoints depends on the code or graph that you