# runs after the job (and after the default post-filter)
from galaxy.jobs.handler import JOB_ERROR
from galaxy.tools.parameters import DataToolParameter

# Older py compatibility
try:
    set()
except:
    from sets import Set as set


def validate_input( trans, error_map, param_values, page_param_map ):
    dbkeys = set()
    data_param_names = set()
    data_params = 0
    for name, param in page_param_map.items():
        if isinstance( param, DataToolParameter ):
            # for each dataset parameter
            if param_values.get(name, None) is not None:
                dbkeys.add( param_values[name].dbkey )
                data_params += 1
                # check meta data
                try:
                    param = param_values[name]
                    if isinstance( param.datatype, trans.app.datatypes_registry.get_datatype_by_extension( 'gff' ).__class__ ):
                        # TODO: currently cannot validate GFF inputs b/c they are not derived from interval.
                        pass
                    else:  # Validate interval datatype.
                        int( param.metadata.startCol )
                        int( param.metadata.endCol )
                        int( param.metadata.chromCol )
                        if param.metadata.strandCol is not None:
                            int( param.metadata.strandCol )
                except:
                    error_msg = "The attributes of this dataset are not properly set. " + \
                        "Click the pencil icon in the history item to set the chrom, start, end and strand columns."
                    error_map[name] = error_msg
            data_param_names.add( name )
    if len( dbkeys ) > 1:
        for name in data_param_names:
            error_map[name] = "All datasets must belong to same genomic build, " \
                "this dataset is linked to build '%s'" % param_values[name].dbkey
    if data_params != len(data_param_names):
        for name in data_param_names:
            error_map[name] = "A dataset of the appropriate type is required"


def exec_after_merge(app, inp_data, out_data, param_dict, tool=None, stdout=None, stderr=None):
    # strip strand column if clusters were merged
    for data in out_data.values():
        if param_dict['returntype'] is True:
            data.metadata.chromCol = 1
            data.metadata.startCol = 2
            data.metadata.endCol = 3
        # merge always clobbers strand
        data.metadata.strandCol = None


def exec_after_cluster(app, inp_data, out_data, param_dict, tool=None, stdout=None, stderr=None):
    # strip strand column if clusters were merged
    if param_dict["returntype"] == '1':
        for data in out_data.values():
            data.metadata.strandCol = None