IOBlock example — a custom .npy loader

LoadNpy (block.py) reads a NumPy .npy file into an Array. Loaders and savers are how data gets in and out of a workflow.

The simple helpers

You almost never subclass IOBlock directly. Use the two helper bases from scistudio.blocks.io:

• SimpleLoader — reads a file → a DataObject. You implement load_file(self, path, config).
• SimpleSaver — writes a DataObject → a file. You implement save_file(self, obj, path, config).

A loader needs three class attributes plus the one method:

class LoadNpy(SimpleLoader):
    output_type = Array              # the type you produce
    extensions  = (".npy",)          # the file extensions you claim
    format_id   = "numpy_npy"        # a short stable id for this format

    def load_file(self, path, config) -> Array:
        ...

That is all SciStudio needs to register your loader, route .npy files to it, and show it in the palette. The file path the user picks arrives for you — read it from path.

A matching saver

The mirror image writes a file. For example, saving a DataFrame to CSV:

import pyarrow.csv as pcsv
from scistudio.blocks.io import SimpleSaver
from scistudio.core.types import DataFrame

class SaveCsv(SimpleSaver):
    input_type = DataFrame
    extensions = (".csv",)
    format_id  = "csv"

    def save_file(self, obj: DataFrame, path, config) -> None:
        pcsv.write_csv(obj.to_memory(), str(path))   # to_memory() -> pyarrow.Table

Beyond the basics

SimpleLoader/SimpleSaver synthesise a conservative format capability for you (which type, which direction, which extensions). When you need finer control — several formats in one block, declaring exactly which metadata survives the round-trip — declare format_capabilities and a MetadataFidelity explicitly, or subclass IOBlock and override load() / save(). See scistudio.blocks.io in the API reference (FormatCapability, MetadataFidelity).