import json
from collections import OrderedDict
import warnings

def create_dataset_description_json(path, 
                                    name, 
                                    bids_version, 
                                    hed_version=None, 
                                    dataset_links=None, 
                                    dataset_type=None, 
                                    data_license=None,
                                    authors=None, 
                                    acknowledgements=None,
                                    how_to_acknowledge=None, 
                                    funding=None,
                                    ethics_approvals=None, 
                                    references_and_links=None,
                                    doi=None, 
                                    generated_by=None, 
                                    source_datasets=None):
    """Create a dataset_description.json file for a BIDS dataset.

    Parameters
    ----------
    path : str
        Path to the dataset_description.json file.
    name : str
        Name of the dataset.
    bids_version : str
        The BIDS version that was used.

    Recommended Parameters
    ----------
    hed_version : str or array of strings, recommended
        The HED version that was used.
    dataset_links : list, required if BIDS URIs are used
        List of links to other datasets.
    dataset_type : str, recommended
        Type of the dataset. Can be "raw" or "derivative".
    data_license : str, recommended
        License of the dataset.
    authors : list, recommended
        List of individuals who contributed to the creation/curation of the dataset.
    generated_by : list, recommended
        Used to specify provenance of the dataset.
    source_datasets : list, recommended
        Used to specify the locations and relevant attributes of all source datasets. Valid values are "URL", "DOI" or "Version".
    
    Optional Parameters
    ----------
    acknowledgements : str, optional
        Text acknowledging contributions of individuals or institutions beyond those listed in Authors or Funding.
    how_to_acknowledge : str, optional
        How to acknowledge the dataset.
    funding : list, optional
        List of funding sources.
    ethics_approvals : list, optional
        List of ethics approvals.
    references_and_links : list, optional
        List of references to publication that contain information on the dataset, or links.
    doi : str, optional
        DOI of the dataset (not the paper).
    """
    
    # Check if values are of correct type
    if (dataset_type not in ['raw', 'derivative']):
        raise ValueError('dataset_type must be either "raw" or "derivative"')
    if (source_datasets not in ['URL', 'DOI', 'Version', None]):
        raise ValueError('source_datasets must be either "URL", "DOI" or "Version"')
    if isinstance(doi, str):
        if not doi.startswith('doi:'):
            warnings.warn('DOI should start with "doi:"')
    
    # Check if required fields are filled in
    if (name is None):
        raise ValueError('name is required')
    if (bids_version is None):
        raise ValueError('bids_version is required')
    
        # Prepare dataset_description.json
    description = OrderedDict([
    ('Name', name),
    ('BIDSVersion', bids_version),
    ('HEDVersion', hed_version),
    ('DatasetType', dataset_type),
    ('DatasetLinks', dataset_links),
    ('License', data_license),
    ('Authors', authors),
    ('Acknowledgements', acknowledgements),
    ('HowToAcknowledge', how_to_acknowledge),
    ('Funding', funding),
    ('EthicsApprovals', ethics_approvals),
    ('ReferencesAndLinks', references_and_links),
    ('DatasetDOI', doi),
    ('GeneratedBy', generated_by),
    ('SourceDatasets', source_datasets)])

    # Remove None values
    pop_keys = [key for key, val in description.items() if val is None]
    for key in pop_keys:
        description.pop(key)

    # Only write data that is not None
    with open(path, 'w') as outfile:
        json.dump(description, outfile, indent=4)