Es el framework más popular de Python y es ampliamente confiable. Se utiliza para construir sistemas como Instagram.

Está relativamente acoplado con bases de datos relacionales (como MySQL o PostgreSQL), por lo que tener una base de datos NoSQL (como Couchbase, MongoDB, Cassandra, etc) como motor de almacenamiento principal no es muy fácil.

        </field>
        <field>
          <name>version</name>
          <version>1.0.0+</version>
          <type>String</type>
          <description>The base version (i.e. ending in {@code -SNAPSHOT}) when this directory represents a "groupId/artifactId/version" for a SNAPSHOT.</description>
        </field>
        <field xdoc.separator="blank">
          <name>plugins</name>

package jcifs;

import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.extension.ExtendWith;
import org.mockito.junit.jupiter.MockitoExtension;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * Base test class providing common test infrastructure and utilities.
 * All test classes should extend this to ensure consistent test setup.
 */
@ExtendWith(MockitoExtension.class)
public abstract class BaseTest {

 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
 */

package jcifs.spnego;

import java.io.IOException;

/**
 * Abstract base class for SPNEGO authentication tokens used in GSS-API negotiation
 */
public abstract class SpnegoToken {

    /**
     * Protected constructor for SPNEGO token implementations.
     */
    protected SpnegoToken() {

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.crawler.transformer.impl;

import org.codelibs.fess.crawler.transformer.Transformer;

/**
 * An abstract base class for transformers.
 * Provides basic implementation for managing the transformer's name.
 *
 */
public abstract class AbstractTransformer implements Transformer {

    /**

Por ejemplo, podrías querer **devolver un diccionario** u objeto de base de datos, pero **declararlo como un modelo de Pydantic**. De esta manera el modelo de Pydantic haría toda la documentación de datos, validación, etc. para el objeto que devolviste (por ejemplo, un diccionario u objeto de base de datos).

			t.Errorf("fitsInBase256(%d, %d): got %v, want %v", v.in, v.width, ok, v.ok)
		}
	}
}

func TestParseNumeric(t *testing.T) {
	vectors := []struct {
		in   string
		want int64
		ok   bool
	}{
		// Test base-256 (binary) encoded values.
		{"", 0, true},
		{"\x80", 0, true},
		{"\x80\x00", 0, true},
		{"\x80\x00\x00", 0, true},
		{"\xbf", (1 << 6) - 1, true},
		{"\xbf\xff", (1 << 14) - 1, true},

# Testando a Base de Dados

Você pode estudar sobre bases de dados, SQL e SQLModel na <a href="https://sqlmodel.tiangolo.com/" class="external-link" target="_blank">documentação de SQLModel</a>. 🤓

Aqui tem um mini <a href="https://sqlmodel.tiangolo.com/tutorial/fastapi/" class="external-link" target="_blank">tutorial de como usar SQLModel com FastAPI</a>. ✨

/**
 * Unit tests for DirectoryLeaseState
 */
public class DirectoryLeaseStateTest {

    @Test
    public void testDirectoryLeaseConstants() {
        // Test that directory lease states use correct base values
        assertEquals(Smb2LeaseState.SMB2_LEASE_READ_CACHING | Smb2LeaseState.SMB2_LEASE_HANDLE_CACHING,
                DirectoryLeaseState.DIRECTORY_READ_HANDLE);

                    "-Porg.gradle.java.installations.auto-download=false",
                ).joinToString(" "),
        )

        artifactRules =
            """$artifactRules
platforms/core-runtime/base-services/build/generated-resources/build-receipt/org/gradle/build-receipt.properties
"""
    }) {
    companion object {
        fun buildTypeId(model: CIBuildModel) = buildTypeId(model.projectId)