private void visit(MetadataGraphVertex from, List<MetadataGraphVertex> visited, MetadataGraph graph) {
        if (visited.contains(from)) {
            return;
        }

        visited.add(from);

        List<MetadataGraphEdge> exitList = graph.getExcidentEdges(from);
        // String s = "|---> "+from.getMd().toString()+" - "+(exitList == null ? -1 : exitList.size()) + " exit links";

        return Traversal.inGraph(graph);
      }
    };
  }

  /**
   * Creates a new traverser for a directed acyclic graph that has at most one path from the start
   * node(s) to any node reachable from the start node(s), and has no paths from any start node to
   * any other start node, such as a tree or forest.
   *
   * <p>{@code forTree()} is especially useful (versus {@code forGraph()}) in cases where the data

import warnings
from collections.abc import Callable, Sequence
from dataclasses import dataclass
from enum import Enum
from typing import Annotated, Any, Literal

from fastapi.exceptions import FastAPIDeprecationWarning
from fastapi.openapi.models import Example
from pydantic import AliasChoices, AliasPath
from pydantic.fields import FieldInfo
from typing_extensions import deprecated

from ._compat import (
    Undefined,
)

import pytest
from dirty_equals import HasRepr
from fastapi import Depends, FastAPI
from fastapi.exceptions import ResponseValidationError
from fastapi.testclient import TestClient
from inline_snapshot import snapshot


@pytest.fixture(name="client")
def get_client():
    from pydantic import BaseModel, ValidationInfo, field_validator

    app = FastAPI()

    class ModelB(BaseModel):
        username: str

    class ModelC(ModelB):

	for x := 0; x < b.N; x++ {
		DB.Raw("select * from users where id = ?", user.ID).Scan(&u)
	}
}

func BenchmarkScanSlice(b *testing.B) {
	DB.Exec("delete from users")
	for i := 0; i < 10_000; i++ {
		user := *GetUser(fmt.Sprintf("scan-%d", i), Config{})
		DB.Create(&user)
	}

	var u []User
	b.ResetTimer()
	for x := 0; x < b.N; x++ {
		DB.Raw("select * from users").Scan(&u)
	}
}

    // Owner is subclassed
    assertHasTypeVariable(new From<Integer>() {}.new To<String>().type());
    assertHasTypeVariable(new From<T>() {}.new To<String>().type());

    // Inner is subclassed
    assertNoTypeVariable(new From<Integer>().new To<String>() {}.type());
    assertHasTypeVariable(new From<Integer>().new To<T>() {}.type());

from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles

app = FastAPI()

    *   Upgrade Flatbuffers v2.0.5 from v1.12.0

*   `tf.keras`:

    *   `EinsumDense` layer is moved from experimental to core. Its import path
        is moved from `tf.keras.layers.experimental.EinsumDense` to
        `tf.keras.layers.EinsumDense`.
    *   Added `tf.keras.utils.audio_dataset_from_directory` utility to easily
        generate audio classification datasets from directories of `.wav` files.

from typing import Any

from fastapi import FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel, ConfigDict


def test_read_with_orm_mode() -> None:
    class PersonBase(BaseModel):
        name: str
        lastname: str

    class Person(PersonBase):
        @property
        def full_name(self) -> str:
            return f"{self.name} {self.lastname}"

# -*- coding: utf-8 -*-
from xml.etree import cElementTree
from xml.etree.cElementTree import ParseError

if hasattr(cElementTree, 'ParseError'):
    _ETREE_EXCEPTIONS = (ParseError, AttributeError, ValueError, TypeError)
else:
    _ETREE_EXCEPTIONS = (SyntaxError, AttributeError, ValueError, TypeError)

_STS_NS = {'sts': 'https://sts.amazonaws.com/doc/2011-06-15/'}


class STSElement(object):