loaders

The astrodata.data.loaders submodule provides a flexible and extensible framework for loading data from various file formats into the astrodata pipeline. It includes a base loader class and specialized loaders for the most common data formats in data science and astrophysics.

Abstract Class

BaseLoader is the abstract base class for all data loaders. Subclasses must implement:

• load(path): Loads data from the specified path and returns a RawData object.

This standard interface ensures that all loaders can be used interchangeably within the astrodata pipeline.

How to Use

Initializing a Loader

To load data, initialize the loader corresponding to your file format. For example, to load a CSV file:

from astrodata.data import CsvLoader

loader = CsvLoader()

Loading Data

Once initialized, use the loader’s load method to read data from disk:

raw_data = loader.load("data.csv")

The returned RawData object wraps the loaded data (typically within a pandas DataFrame) and is ready for further processing.

Available Loaders

• CsvLoader: Loads data from CSV files.

• ParquetLoader: Loads data from Parquet files.

Extensibility

The loaders module is designed for easy extension. To add support for a new format (e.g., HDF5, FITS), subclass BaseLoader and implement the load method for your format. Planned future releases will include loaders for standard astrophysics formats.