@Override
  public String toString() {
    long nanos = elapsedNanos();

    TimeUnit unit = chooseUnit(nanos);
    double value = (double) nanos / NANOSECONDS.convert(1, unit);

    // Too bad this functionality is not exposed as a regular method call
    return Platform.formatCompact4Digits(value) + " " + abbreviate(unit);
  }

  private static TimeUnit chooseUnit(long nanos) {
    if (DAYS.convert(nanos, NANOSECONDS) > 0) {

     * to decide between a method that takes int and a
     * method that takes java.lang.Integer as a parameter.
     * <p>
     * This turns out to be a relatively rare case
     * where this is needed - however, functionality
     * like this is needed.
     *
     * @param methodName name of method
     * @param args       the actual arguments with which the method is called
     * @return the most specific applicable method, or null if no

`FastAPI` is actually a sub-class of `Starlette`. So, if you already know or use Starlette, most of the functionality will work the same way.

With **FastAPI** you get all of **Starlette**'s features (as FastAPI is just Starlette on steroids):

application monitoring made easy - author: John Philip author_link: https://medium.com/@amjohnphilip link: https://python.plainenglish.io/building-a-restful-api-with-fastapi-secure-signup-and-login-functionality-included-45cdbcb36106 title: "Building a RESTful API with FastAPI: Secure Signup and Login Functionality Included" - author: Keshav Malik author_link: https://theinfosecguy.xyz/ link: https://blog.theinfosecguy.xyz/building-a-crud-api-with-fastapi-and-supabase-a-step-by-step-guide title: Building...

                                              TF_Status* out_status);

// Sets the attribute attr_name to be a function specified by 'function'.
//
// TODO(ashankar,iga): Add this functionality to the C API for graph
// construction. Perhaps we want an AttrValueMap equivalent in the C API?
TF_CAPI_EXPORT extern void TFE_OpSetAttrFunction(TFE_Op* op,

## Hash and verify the passwords

Import the tools we need from `passlib`.

Create a PassLib "context". This is what will be used to hash and verify passwords.

/// tip

The PassLib context also has functionality to use different hashing algorithms, including deprecated old ones only to allow verifying them, etc.

---> 100%
```

</div>

/// info

In Pydantic v1 it came included with the main package. Now it is distributed as this independent package so that you can choose to install it or not if you don't need that functionality.

///

### Create the `Settings` object

Import `BaseSettings` from Pydantic and create a sub-class, very much like with a Pydantic model.

                                          TF_Status* status) {
#if defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
  status->status = tensorflow::errors::Unimplemented(
      "PluggableDevice plugin functionality is not supported on mobile");
  return nullptr;
#else
  TF_Library* lib_handle = new TF_Library;
  static tensorflow::mutex mu(tensorflow::LINKER_INITIALIZED);

import org.junit.After;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.junit.runners.JUnit4;

/** Tests for {@link StandardMutableValueGraph} and related functionality. */
// TODO(user): Expand coverage and move to proper test suite.
@RunWith(JUnit4.class)
public final class ValueGraphTest {
  private static final String DEFAULT = "default";

                        TF_Status* status) {
#if defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
  status->status = tensorflow::errors::Unimplemented(
      "Server functionality is not supported on mobile");
  return nullptr;
#else
  tensorflow::ServerDef server_def;
  if (!server_def.ParseFromArray(proto, static_cast<int>(proto_len))) {
    status->status = InvalidArgument(