* test with reference to the same "lock-like object", and then their interactions with that object
 * are choreographed via the various methods on this class.
 *
 * <p>A "lock-like object" is really any object that may be used for concurrency control. If the
 * {@link #callAndAssertBlocks} method is ever called in a test, the lock-like object must have a

    When implementing the callback yourself, you could use something like <a href="https://www.python-httpx.org" class="external-link" target="_blank">HTTPX</a> or <a href="https://requests.readthedocs.io/" class="external-link" target="_blank">Requests</a>.

## Write the callback documentation code

This code won't be executed in your app, we only need it to *document* how that *external API* should look like.

	Gt(lte).Build(builder)
}

// Like whether string matches regular expression
type Like Eq

func (like Like) Build(builder Builder) {
	builder.WriteQuoted(like.Column)
	builder.WriteString(" LIKE ")
	builder.AddVar(builder, like.Value)
}

func (like Like) NegationBuild(builder Builder) {
	builder.WriteQuoted(like.Column)
	builder.WriteString(" NOT LIKE ")
	builder.AddVar(builder, like.Value)
}

   * http://android.com/foo HTTP/1.1") or only the path (like "GET /foo HTTP/1.1").
   */
  private fun includeAuthorityInRequestLine(
    request: Request,
    proxyType: Proxy.Type,
  ): Boolean {
    return !request.isHttps && proxyType == Proxy.Type.HTTP
  }

  /**
   * Returns the path to request, like the '/' in 'GET / HTTP/1.1'. Never empty, even if the request

		t.Fatalf("errors happened when create users: %v", err)
	}

	var names []string
	DB.Table("users").Where("name like ?", "distinct%").Order("name").Pluck("name", &names)
	AssertEqual(t, names, []string{"distinct", "distinct", "distinct", "distinct-2", "distinct-3"})

	var names1 []string
	DB.Model(&User{}).Where("name like ?", "distinct%").Distinct().Order("name").Pluck("Name", &names1)

It's relatively tightly coupled with relational databases (like MySQL or PostgreSQL), so, having a NoSQL database (like Couchbase, MongoDB, Cassandra, etc) as the main store engine is not very easy.

    For example, you could use it to read and verify passwords generated by another system (like Django) but hash any new passwords with a different algorithm like Bcrypt.

    And be compatible with all of them at the same time.

Create a utility function to hash a password coming from the user.

# JSON Compatible Encoder

There are some cases where you might need to convert a data type (like a Pydantic model) to something compatible with JSON (like a `dict`, `list`, etc).

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder`

Let's imagine that you have a database `fake_db` that only receives JSON compatible data.

	cases := []string{
		`select * from s3object where Name like 'abcd'`,
		`select Name like 'abc' from s3object`,
		`select * from s3object where Name not like 'abc'`,
		`select * from s3object where Name like 'abc' escape 't'`,
		`select * from s3object where Name like 'a\%' escape '?'`,
		`select * from s3object where Name not like 'abc\' escape '?'`,
		`select * from s3object where Name like 'a\%' escape LOWER('?')`,

 Features like transitive dependencies and the new parent specification mechanism. The problem we run into is
 that currently we have information about a project scattered across the project.xml and the
 various properties files. What needs to be done is to encapsulate all of this in the POM.

 Typically users parameterize the use of plugins, or have custom values like ${user.name}