* Parce que les structures de données de pydantic consistent seulement en une instance de classe que vous définissez; l'auto-complétion, le linting, mypy et votre intuition devrait être largement suffisante pour valider vos données.
* Valide les **structures complexes**:
    * Utilise les modèles hiérarchique de Pydantic, le `typage` Python pour les `Lists`, `Dict`, etc.

   * code would be responsible for populating a "real" {@code T} (which might still be the value
   * {@code null}!) before returning it to callers. Depending on how the code is structured, a
   * nullness analysis might not understand that the field has been populated. To avoid that problem
   * without having to add {@code @SuppressWarnings}, the code can call this method.
   *

   * code would be responsible for populating a "real" {@code T} (which might still be the value
   * {@code null}!) before returning it to callers. Depending on how the code is structured, a
   * nullness analysis might not understand that the field has been populated. To avoid that problem
   * without having to add {@code @SuppressWarnings}, the code can call this method.
   *

    Arrays.fill(result, oldSize, newSize, ABSENT);
    return result;
  }

  @Override
  public int size() {
    return size;
  }

  /**
   * Ensures that all of the internal structures in the HashBiMap are ready for this many elements.
   */
  private void ensureCapacity(int minCapacity) {
    if (nextInBucketKToV.length < minCapacity) {
      int oldCapacity = nextInBucketKToV.length;

A execution command of Generate task
which generates classes corresponding your tables,
for example, entities, condition-beans to specified
directories by DBFlute properties on "dfprop" directory.

Generated structures (directories and classes) are like this:
/- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
allcommon : classes bridging to DBFlute Runtime
bsbhv     : base behaviors
bsentity  : base entities

import com.google.common.annotations.Beta;
import com.google.errorprone.annotations.DoNotMock;

/**
 * A functional interface for <a
 * href="https://en.wikipedia.org/wiki/Graph_(discrete_mathematics)">graph</a>-structured data.
 *
 * <p>This interface is meant to be used as the type of a parameter to graph algorithms (such as
 * breadth first traversal) that only need a way of accessing the successors of a node in a graph.
 *

import com.google.common.annotations.Beta;
import com.google.errorprone.annotations.DoNotMock;

/**
 * A functional interface for <a
 * href="https://en.wikipedia.org/wiki/Graph_(discrete_mathematics)">graph</a>-structured data.
 *
 * <p>This interface is meant to be used as the type of a parameter to graph algorithms (such as
 * topological sort) that only need a way of accessing the predecessors of a node in a graph.
 *
 * <h3>Usage</h3>

   * code would be responsible for populating a "real" {@code T} (which might still be the value
   * {@code null}!) before returning it to callers. Depending on how the code is structured, a
   * nullness analysis might not understand that the field has been populated. To avoid that problem
   * without having to add {@code @SuppressWarnings}, the code can call this method.
   *

  // Get theta shape and store in theta_dims.
  int num_dims = TF_NumDims(theta_tensor);
  vector<int64_t> theta_dims(num_dims);
  GetDims(theta_tensor, theta_dims.data());

  // Initialize auxilary data structures.
  vector<float> thetaPlus_data(num_elems);
  vector<float> thetaMinus_data(num_elems);
  AbstractTensorHandle* f_outputs[1];

  // Numerical Grad Check
  for (int i = 0; i < num_elems; i++) {

import com.google.common.annotations.Beta;
import com.google.errorprone.annotations.DoNotMock;

/**
 * A functional interface for <a
 * href="https://en.wikipedia.org/wiki/Graph_(discrete_mathematics)">graph</a>-structured data.
 *
 * <p>This interface is meant to be used as the type of a parameter to graph algorithms (such as
 * topological sort) that only need a way of accessing the predecessors of a node in a graph.
 *
 * <h3>Usage</h3>