Flask is a "microframework", it doesn't include database integrations nor many of the things that come by default in Django.

This simplicity and flexibility allow doing things like using NoSQL databases as the main data storage system.

As it is very simple, it's relatively intuitive to learn, although the documentation gets somewhat technical at some points.

  // it never skips the policy.
  //
  // For example, to run the webhook on any objects whose namespace is not
  // associated with "runlevel" of "0" or "1";  you will set the selector as
  // follows:
  // "namespaceSelector": {
  //   "matchExpressions": [
  //     {
  //       "key": "runlevel",
  //       "operator": "NotIn",
  //       "values": [
  //         "0",
  //         "1"

        }
    }

    /**
     * Ensures the last updated timestamp of the specified metadata does not refer to the future and fixes the local
     * metadata if necessary to allow proper merging/updating of metadata during deployment.
     */
    private void fixTimestamp(File metadataFile, Metadata metadata, Metadata reference) {
        boolean changed = false;

	// If format.json is available and request sent the right disk-id, we allow the request
	return true
}

// checkID - check if the disk-id in the request corresponds to the underlying disk.
func (s *storageRESTServer) checkID(wantID string) bool {
	if s.getStorage() == nil {
		return false
	}
	if wantID == "" {
		// Request sent empty disk-id, we allow the request

     * during metadata retrieval.
     */
    int VALIDATION_LEVEL_MINIMAL = 0;

    /**
     * Denotes validation as performed by Maven 2.0. This validation level is meant as a compatibility mode to allow
     * users to migrate their projects.
     */
    int VALIDATION_LEVEL_MAVEN_2_0 = 20;

    /**
     * Denotes validation as performed by Maven 3.0. This validation level is meant for existing projects.
     */

  // e.g. ["ro", "soft"]. Not validated -
  // mount of the PVs will simply fail if one is invalid.
  // +optional
  repeated string mountOptions = 5;

  // allowVolumeExpansion shows whether the storage class allow volume expand
  // +optional
  optional bool allowVolumeExpansion = 6;

  // volumeBindingMode indicates how PersistentVolumeClaims should be
  // provisioned and bound.  When unset, VolumeBindingImmediate is used.

	xlVersionMajor = 1

	// Non breaking changes.
	// Bumping this is informational, but should be done
	// if any change is made to the data stored, bumping this
	// will allow to detect the exact version later.
	xlVersionMinor = 1
)

func init() {
	binary.LittleEndian.PutUint16(xlVersionCurrent[0:2], xlVersionMajor)
	binary.LittleEndian.PutUint16(xlVersionCurrent[2:4], xlVersionMinor)

* Validate **complex structures**:
    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.
    * And validators allow complex data schemas to be clearly and easily defined, checked and documented as JSON Schema.
    * You can have deeply **nested JSON** objects and have them all validated and annotated.
* **Extensible**:

* GCI: Add two GCI specific metadata pairs ([#25105](https://github.com/kubernetes/kubernetes/pull/25105), [@andyzheng0831](https://github.com/andyzheng0831))
* Add an entry to the salt config to allow Debian jessie on GCE. ([#25123](https://github.com/kubernetes/kubernetes/pull/25123), [@jlewi](https://github.com/jlewi))
    * As with the existing Wheezy image on GCE, docker is expected to already be installed in the image.

	"http://dbflute.org/meta/lastadi10.dtd">
<components>
	<component name="searchEngineClient" class="org.codelibs.fess.es.client.SearchEngineClient">
		<property name="settings">
			{"http.cors.enabled":"true",
			 "http.cors.allow-origin":"*",
			 "discovery.type":"single-node",
			 "cluster.allocator.existing_shards_allocator.batch_enabled":"true",
			 <!--
			 "node.name":"search_engine",
			 "discovery.seed_hosts":"search_engine",