Types

A primary objective of our framework is to simplify its usage for those who wish to employ it without delving into development. We aim to offer them a straightforward and effortless setup process, minimizing the complexities and initializations associated with numerous classes. This approach reduces potential bugs and allows users to focus on their primary task: developing an application using our framework. To ensure uniformity throughout the framework and to effectively manage new Data Pipes while avoiding incorrect class initializations, we have introduced Types identifiers. These identifiers, at a high level, determine the specific type of datapipe required. Consequently, CHA users are relieved from the intricate details of initializing DataPipe objects, integrating them into the CHA, and handling setups.

Datapipe Types

This enumeration class defines different types of datapipe. This ensures consistency in case the datapipe developer decides to change the name of their datapipe, the end user need not to change their code cause they use the keys. It inherits from the str class and the Enum class in Python’s enum module. Each value in this enumeration represents a specific type of datapipe. The key naming convention should be all uppercase with underscore, and the value naming convention should be underscore_case: NAME_OF_DATAPIP = this_is_a_sample_datapipe_name

from enum import Enum


class DatapipeType(str, Enum):
    MEMORY = "memory"

Types

This dictionary is used to map each DatapipeType value to its corresponding DataPipe class. It allows for easy retrieval of the appropriate class based on the datapipe type.

from typing import Dict
from typing import Type

from datapipes.datapipe import DataPipe
from datapipes.datapipe_types import DatapipeType
from datapipes.memory import Memory


DATAPIPE_TO_CLASS: Dict[DatapipeType, Type[DataPipe]] = {
    DatapipeType.MEMORY: Memory
}