"keywords": ["sample"]
        },
        "finnish_stop": {
          "type":       "stop",

}

type JoinBuilder interface {
	Select(...string) JoinBuilder
	Omit(...string) JoinBuilder
	Where(query interface{}, args ...interface{}) JoinBuilder
	Not(query interface{}, args ...interface{}) JoinBuilder
	Or(query interface{}, args ...interface{}) JoinBuilder
}

type PreloadBuilder interface {
	Select(...string) PreloadBuilder
	Omit(...string) PreloadBuilder
	Where(query interface{}, args ...interface{}) PreloadBuilder

    body.close()
  }

  @Test
  fun unicodeText() {
    val text = "eile oli oliiviõli"
    val body = text.toResponseBody()
    assertThat(body.string()).isEqualTo(text)
  }

  @Test
  fun unicodeTextWithCharset() {
    val text = "eile oli oliiviõli"
    val body = text.toResponseBody("text/plain; charset=UTF-8".toMediaType())
    assertThat(body.string()).isEqualTo(text)
  }

  static final String LOREM_IPSUM =
      "Lorem ipsum dolor sit amet, consectetur adipiscing "
          + "elit. Cras fringilla elit ac ipsum adipiscing vulputate. Maecenas in lorem nulla, ac "
          + "sollicitudin quam. Praesent neque elit, sodales quis vestibulum vel, pellentesque nec "
          + "erat. Proin cursus commodo lacus eget congue. Aliquam erat volutpat. Fusce ut leo sed "

	DB.Save(&user)

	results := make([]*User, 0)

	if err := DB.Table("users").Omit("name").Where("users.name = ?", "joins_with_omit").Joins("left join pets on pets.user_id = users.id").Find(&results).Error; err != nil {
		return
	}

	if len(results) != 2 || results[0].Name != "" || results[1].Name != "" {
		t.Errorf("Should find all two pets with Join omit and should not find user's name, got %+v", results)
		return
	}
}

			columnName := matches[3]
			if star != "" {
				return table, star
			}
			return table, columnName
		}
		return "", ""
	}
}()

// SelectAndOmitColumns get select and omit columns, select -> true, omit -> false
func (stmt *Statement) SelectAndOmitColumns(requireCreate, requireUpdate bool) (map[string]bool, bool) {
	results := map[string]bool{}
	notRestricted := false

 * certificate is signed by the certificate that follows, and the last certificate is a trusted CA
 * certificate.
 *
 * Use of the chain cleaner is necessary to omit unexpected certificates that aren't relevant to
 * the TLS handshake and to extract the trusted CA certificate for the benefit of certificate
 * pinning.
 */
abstract class CertificateChainCleaner {

		tx = tx.Set("gorm:update_track_time", true)
	}

	if len(selects) > 0 {
		tx = tx.Select(selects)
	} else if restricted && len(omits) == 0 {
		tx = tx.Omit(clause.Associations)
	}

	if len(omits) > 0 {
		tx = tx.Omit(omits...)
	}

	return db.AddError(tx.Create(values).Error)
}

// check association values has been saved
// if values kind is Struct, check it has been saved

# Requirements for NumPy 1.x
numpy ~= 1.26.0
wheel ~= 0.41.2
h5py >= 3.11.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version

# Note that numpy 2.1.0 does not support python 3.9
numpy >= 2.0.0, < 2.2.0
wheel ~= 0.41.2
h5py >= 3.11.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras