How to Quickly Validate an Existing Project

Note

Currently validation is only available through the Python API.

The function datashuttle.quick_validate_project can be used to quickly validate a project fully conforms to theNeuroBlueprint standard. This does not require setting up a full datashuttle project, only the filepath to the project.

For example, if you have an existing project at /mydrive/path/to/project/project_name you can validate with:

from datashuttle import quick_validate_project

quick_validate_project(
    project_path="/mydrive/path/to/project/project_name",
    display_mode="error",
)

In this case, display_mode=error will result in an error on the first encountered validation issue. Otherwise "warn" will show a python warning for all detected issues, while "print" will print directly to console.

By default, both "rawdata" and "derivatives" folders will be checked (assuming they exist). Otherwise, one can be specified with the a top_level_folder argument.

See datashuttle.quick_validate_project for a full list of arguments.