Flask est un "micro-framework", il ne comprend pas d'intégrations de bases de données ni beaucoup de choses qui sont fournies par défaut dans Django.

Cette simplicité et cette flexibilité permettent d'utiliser des bases de données NoSQL comme principal système de stockage de données.

Comme il est très simple, son apprentissage est relativement intuitif, bien que la documentation soit quelque peu

      this.cells.addAll(other.cells);
      return this;
    }

    /**
     * Returns a newly-created immutable table.
     *
     * <p>Prefer the equivalent method {@link #buildOrThrow()} to make it explicit that the method
     * will throw an exception if there are duplicate key pairs. The {@code build()} method will
     * soon be deprecated.
     *
     * @throws IllegalArgumentException if duplicate key pairs were added

    assertThrows(IllegalArgumentException.class, () -> Bytes.ensureCapacity(ARRAY1, 1, -1));
  }

  public void testToArray() {
    // need explicit type parameter to avoid javac warning!?
    List<Byte> none = Arrays.<Byte>asList();
    assertThat(Bytes.toArray(none)).isEqualTo(EMPTY);

    List<Byte> one = Arrays.asList((byte) 1);

	for _, kvsrc := range kvsrcs {
		// skip returning default config values.
		if kvsrc.Src == config.ValueSourceDef {
			if kvsrc.Key != madmin.EnableKey {
				continue
			}
			// for EnableKey we set an explicit on/off from live configuration
			// if it is present.
			if _, ok := r.ProviderCfgs[cfgName]; !ok {
				// No live config is present
				continue
			}
			if r.Enabled {
				kvsrc.Value = "on"
			} else {

# To learn more about import library (called interface library in Bazel):
#     https://docs.microsoft.com/en-us/cpp/build/linking-an-executable-to-a-dll?view=vs-2017#linking-implicitly
filegroup(
    name = "get_tensorflow_dll_import_lib",
    srcs = ["//tensorflow:tensorflow.dll"],
    output_group = "interface_library",
    visibility = ["//visibility:public"],
)

            switch (notification.getCause()) {
              case EXPIRED:
                stats[0]++;
                break;
              case EXPLICIT:
                stats[1]++;
                break;
              case REPLACED:
                stats[2]++;
                break;
              case SIZE:
                stats[3]++;

type KMS struct {
	// Type identifies the KMS implementation. Either,
	// MinKMS, MinKES or Builtin.
	Type Type

	// The default key, used for generating new data keys
	// if no explicit GenerateKeyRequest.Name is provided.
	DefaultKey string

	conn conn // Connection to the KMS

	// Metrics
	reqOK, reqErr, reqFail atomic.Uint64
	latencyBuckets         []time.Duration // expected to be sorted

   * is empty.
   *
   * <p><b>Warning:</b> Typical uses of the resulting iterator may produce an infinite loop. You
   * should use an explicit {@code break} or be certain that you will eventually remove all the
   * elements.
   *
   * <p>To cycle over the iterable {@code n} times, use the following: {@code
   * Iterables.concat(Collections.nCopies(n, iterable))}

     * including thread pool management and session-based crawling coordination.
     */
    public DataIndexHelper() {
        // Default constructor with explicit documentation
    }

    /**
     * Initiates crawling for all configured data stores.
     * This method retrieves all available data configurations and
     * starts the crawling process for each one.
     *

 * implementation considerably. The assumption is that a user of this factory wishes to eliminate
 * any cyclic acquisition ordering.
 *
 * <p><strong>Explicit Lock Acquisition Ordering</strong>
 *
 * <p>The {@link CycleDetectingLockFactory.WithExplicitOrdering} class can be used to enforce an
 * application-specific ordering in addition to performing general cycle detection.
 *