2012-12-01

## Context

In Gradle we often need to serialize in-memory objects for caching, or to transmit them across process barriers, etc.
Java serialization is one way to implement this, however, despite its simplicity of implementation, it has several drawbacks:

- **Performance:**
Java's built-in serialization mechanism is often slower compared to other serialization solutions.

mapreduce.task.io.sort.factor=999 # Threshold before writing to disk
mapreduce.task.sort.spill.percent=0.9 # Minimum % before spilling to disk
```

      error_msg='Invalid gcc path. %s cannot be found.',
  )

  write_action_env_to_bazelrc('GCC_HOST_COMPILER_PATH', gcc_host_compiler_path)


def choose_compiler(environ_cp):
  question = 'Do you want to use Clang to build TensorFlow?'
  yes_reply = 'Clang will be used to compile TensorFlow.'
  no_reply = 'GCC will be used to compile TensorFlow.'
  var = int(
      get_var(

  // value.  Setting to 1 means that parallelism is limited to 1 and the success of that
  // pod signals the success of the job.
  // More info: https://kubernetes.io/docs/concepts/workloads/controllers/jobs-run-to-completion/
  // +optional
  optional int32 completions = 2;

  // Specifies the duration in seconds relative to the startTime that the job

/**
 * A map, each entry of which maps a {@link TypeToken} to an instance of that type. In addition to
 * implementing {@code Map}, the additional type-safe operations {@link #putInstance} and {@link
 * #getInstance} are available.
 *
 * <p>Generally, implementations don't support {@link #put} and {@link #putAll} because there is no
 * way to check an object at runtime to be an instance of a {@link TypeToken}. Instead, caller

* Convert the copied model to something that can be stored in your DB (for example, using the `jsonable_encoder`).
    * This is comparable to using the model's `.model_dump()` method again, but it makes sure (and converts) the values to data types that can be converted to JSON, for example, `datetime` to `str`.
* Save the data to your DB.
* Return the updated model.

=== "Python 3.10+"

/**
 * A container for data that is specific to a session.
 * All components may use this storage to associate arbitrary data with a session.
 * <p>
 * Unlike a cache, this session data is not subject to purging. For this same reason, session data should also not be
 * abused as a cache (i.e. for storing values that can be re-calculated) to avoid memory exhaustion.
 * <p>

        listen       9000;
        listen  [::]:9000;
        server_name  localhost;

        # To allow special characters in headers
        ignore_invalid_headers off;
        # Allow any size file to be uploaded.
        # Set to a value such as 1000m; to restrict file size to a specific value
        client_max_body_size 0;
        # To disable buffering
        proxy_buffering off;
        proxy_request_buffering off;

        Any,
        Doc(
            """
            The input object to convert to JSON.
            """
        ),
    ],
    include: Annotated[
        Optional[IncEx],
        Doc(
            """
            Pydantic's `include` parameter, passed to Pydantic models to set the
            fields to include.
            """
        ),
    ] = None,
    exclude: Annotated[

   * first one specified is included.
   *
   * <p>Despite the method name, this method attempts to avoid actually copying the data when it is
   * safe to do so. The exact circumstances under which a copy will or will not be performed are
   * undocumented and subject to change.
   *