You would have **one single `engine` object** for all your code to connect to the same database.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[14:18] hl[14:15,17:18] *}

Using `check_same_thread=False` allows FastAPI to use the same SQLite database in different threads. This is necessary as **one single request** could use **more than one thread** (for example in dependencies).

programs whose distribution conditions are incompatible with these,
write to the author to ask for permission.  For software which is
copyrighted by the Free Software Foundation, write to the Free
Software Foundation; we sometimes make exceptions for this.  Our
decision will be guided by the two goals of preserving the free status
of all derivatives of our free software and of promoting the sharing
and reuse of software generally.

// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License

/// warning

This is a more or less advanced section. If you are just starting, you can skip it.

You don't necessarily need OAuth2 scopes, and you can handle authentication and authorization however you want.

But OAuth2 with scopes can be nicely integrated into your API (with OpenAPI) and your API docs.

	if err != nil {
		t.Fatal(err)
	}
	defer z.Close()

	for _, test := range []struct {
		name string
		want time.Time
	}{
		{
			"a",
			time.Date(2021, 4, 19, 12, 29, 56, 0, timeZone(-7*time.Hour)).UTC(),
		},
		{
			"a/b/c",
			time.Date(2021, 4, 19, 12, 29, 59, 0, timeZone(-7*time.Hour)).UTC(),
		},
	} {
		fi, err := fs.Stat(z, test.name)
		if err != nil {

If you have improvements to TensorFlow, send us your pull requests! For those
just getting started, GitHub has a
[how-to](https://help.github.com/articles/using-pull-requests/).

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are

programs whose distribution conditions are different, write to the
author to ask for permission. For software which is copyrighted by the
Free Software Foundation, write to the Free Software Foundation; we
sometimes make exceptions for this. Our decision will be guided by the
two goals of preserving the free status of all derivatives of our free
software and of promoting the sharing and reuse of software generally.

NO WARRANTY

	l := lru.NewLRU[int64, int64](8192, nil, 0)

	trace := make([]int64, b.N*2)
	for i := 0; i < b.N*2; i++ {
		if i%2 == 0 {
			trace[i] = getRand(b) % 16384
		} else {
			trace[i] = getRand(b) % 32768
		}
	}

	b.ResetTimer()

	for i := 0; i < b.N; i++ {
		l.Add(trace[i], trace[i])
	}
	var hit, miss int
	for i := 0; i < b.N; i++ {
		if _, ok := l.Get(trace[i]); ok {
			hit++
		} else {

## Quick Start

// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License