class WoRMSCurator(object):
"""
Class for accessing the WoRMS taxonomic name database via the AphiaNameService.
"""
def __init__(self):
""" Initialize a SOAP client using the WSDL for the WoRMS Aphia names service"""
self._worms = WoRMSService()
def curate_taxon_name_and_author(self, input_record):
# look up aphia record for input taxon name in WoRMS taxonomic database
is_exact_match, aphia_record = (
self._worms.aphia_record_by_taxon_name(input_record['TaxonName']))
if aphia_record is not None:
# save taxon name and author values from input record in new fields
input_record['OriginalName'] = input_record['TaxonName']
input_record['OriginalAuthor'] = input_record['Author']
# replace taxon name and author fields in input record with values in aphia record
input_record['TaxonName'] = aphia_record['scientificname']
input_record['Author'] = aphia_record['authority']
# add new fields
input_record['WoRMsExactMatch'] = is_exact_match
input_record['lsid'] = aphia_record['lsid']
else:
input_record['OriginalName'] = None
input_record['OriginalAuthor'] = None
input_record['WoRMsExactMatch'] = None
input_record['lsid'] = None
return input_record
def clean_data_using_worms(input_data_file_name,
cleaned_data_file_name,
rejected_data_file_name,
input_field_delimiter=',',
output_field_delimiter=','):
worms = WoRMSService()
accepted_record_count = 0
rejected_record_count = 0
##############################################################################################
# @BEGIN read_input_data_records
# @PARAM input_data_file_name
# @PARAM input_field_delimiter
# @IN input_data @FILE file:{input_data_file_name}
# @OUT original_record
# create CSV reader for input records
timestamp("Reading input records from '{0}'.".format(input_data_file_name))
input_data = csv.DictReader(open(input_data_file_name, 'r'),
delimiter=input_field_delimiter)
# iterate over input data records
record_num = 0
for original_record in input_data:
record_num += 1
print
timestamp('Reading input record {0:03d}.'.format(record_num))
# @END read_input_data_records
##############################################################################################
# @BEGIN extract_record_fields
# @IN original_record
# @OUT original_scientific_name
# @OUT original_authorship
# extract values of fields to be validated
original_scientific_name = original_record['scientificName']
original_authorship = original_record['scientificNameAuthorship']
# @END extract_record_fields
##############################################################################################
# @BEGIN find_matching_worms_record
# @IN original_scientific_name
# @OUT matching_worms_record
# @OUT worms_lsid
worms_match_result = None
worms_lsid = None
# first try exact match of the scientific name against WoRMs
timestamp(
"Trying WoRMs EXACT match for scientific name: '{0}'.".format(
original_scientific_name))
matching_worms_record = worms.aphia_record_by_exact_taxon_name(
original_scientific_name)
if matching_worms_record is not None:
timestamp('WoRMs EXACT match was SUCCESSFUL.')
worms_match_result = 'exact'
# otherwise try a fuzzy match
else:
timestamp('EXACT match FAILED.')
timestamp(
"Trying WoRMs FUZZY match for scientific name: '{0}'.".format(
original_scientific_name))
matching_worms_record = worms.aphia_record_by_fuzzy_taxon_name(
original_scientific_name)
if matching_worms_record is not None:
timestamp('WoRMs FUZZY match was SUCCESSFUL.')
worms_match_result = 'fuzzy'
else:
timestamp('WoRMs FUZZY match FAILED.')
# if either match succeeds extract the LSID for the taxon
if matching_worms_record is not None:
worms_lsid = matching_worms_record['lsid']
# @END find_matching_worms_record
##############################################################################################
# @BEGIN reject_records_not_in_worms
# @IN original_record
# @IN matching_worms_record
# @PARAM rejected_data_file_name
# @PARAM output_field_delimiter
# @OUT rejected_data @FILE file:{rejected_data_file_name}
# reject the currect record if not matched successfully against WoRMs
if worms_match_result is None:
# open file for storing rejected data if not already open
if 'rejected_data' not in locals():
rejected_data = csv.DictWriter(
open(rejected_data_file_name, 'w'),
input_data.fieldnames,
delimiter=output_field_delimiter)
rejected_data.writeheader()
# write current record to rejects file
timestamp('REJECTED record {0:03d}.'.format(record_num))
rejected_data.writerow(original_record)
rejected_record_count += 1
# skip to processing of next record in input file
continue
# @END reject_records_not_in_worms
##############################################################################################
# @BEGIN update_scientific_name
# @IN original_scientific_name
# @IN matching_worms_record
# @OUT updated_scientific_name
updated_scientific_name = None
# get scientific name from WoRMs record if the taxon name match was fuzzy
if worms_match_result == 'fuzzy':
updated_scientific_name = matching_worms_record['scientificname']
# @END update_scientific_name
##############################################################################################
# @BEGIN update_authorship
# @IN matching_worms_record
# @IN original_authorship
# @OUT updated_authorship
updated_authorship = None
# get the scientific name authorship from the WoRMS record if different from input record
worms_name_authorship = matching_worms_record['authority']
if worms_name_authorship != original_authorship:
updated_authorship = worms_name_authorship
# @END update_authorship
##############################################################################################
# @BEGIN compose_cleaned_record
# @IN original_record
# @IN worms_lsid
# @IN updated_scientific_name
# @IN original_scientific_name
# @IN updated_authorship
# @IN original_authorship
# @OUT cleaned_record
cleaned_record = original_record
cleaned_record['LSID'] = worms_lsid
cleaned_record['WoRMsMatchResult'] = worms_match_result
if updated_scientific_name is not None:
timestamp("UPDATING scientific name from '{0}' to '{1}'.".format(
original_scientific_name, updated_scientific_name))
cleaned_record['scientificName'] = updated_scientific_name
cleaned_record['originalScientificName'] = original_scientific_name
if updated_authorship is not None:
timestamp(
"UPDATING scientific name authorship from '{0}' to '{1}'.".
format(original_authorship, updated_authorship))
cleaned_record['scientificNameAuthorship'] = updated_authorship
cleaned_record['originalAuthor'] = original_authorship
# @END compose_cleaned_record
##############################################################################################
# @BEGIN write_clean_data_set
# @PARAM cleaned_data_file_name
# @PARAM output_field_delimiter
# @IN cleaned_record
# @OUT cleaned_data @FILE file:{cleaned_data_file_name}
# open file for storing cleaned data if not already open
if 'cleaned_data' not in locals():
cleaned_record_field_names = input_data.fieldnames + \
['LSID', 'WoRMsMatchResult', 'originalScientificName', 'originalAuthor']
cleaned_data = csv.DictWriter(open(cleaned_data_file_name, 'w'),
cleaned_record_field_names,
delimiter=output_field_delimiter)
cleaned_data.writeheader()
timestamp('ACCEPTED record {0:03d}.'.format(record_num))
cleaned_data.writerow(cleaned_record)
accepted_record_count += 1
# @END write_clean_data_set
print
timestamp("Wrote {0} accepted records to '{1}'.".format(
accepted_record_count, cleaned_data_file_name))
timestamp("Wrote {0} rejected records to '{1}'.".format(
rejected_record_count, rejected_data_file_name))
def clean_data_using_worms(
input_data_file_name,
cleaned_data_file_name,
rejected_data_file_name,
input_field_delimiter=',',
output_field_delimiter=','
):
worms = WoRMSService()
accepted_record_count = 0
rejected_record_count = 0
##############################################################################################
# @BEGIN read_input_data_records
# @PARAM input_data_file_name
# @PARAM input_field_delimiter
# @IN input_data @FILE file:{input_data_file_name}
# @OUT original_record
# create CSV reader for input records
timestamp("Reading input records from '{0}'.".format(input_data_file_name))
input_data = csv.DictReader(open(input_data_file_name, 'r'),
delimiter=input_field_delimiter)
# iterate over input data records
record_num = 0
for original_record in input_data:
record_num += 1
print
timestamp('Reading input record {0:03d}.'.format(record_num))
# @END read_input_data_records
##############################################################################################
# @BEGIN extract_record_fields
# @IN original_record
# @OUT original_scientific_name
# @OUT original_authorship
# extract values of fields to be validated
original_scientific_name = original_record['scientificName']
original_authorship = original_record['scientificNameAuthorship']
# @END extract_record_fields
##############################################################################################
# @BEGIN find_matching_worms_record
# @IN original_scientific_name
# @OUT matching_worms_record
# @OUT worms_lsid
worms_match_result = None
worms_lsid = None
# first try exact match of the scientific name against WoRMs
timestamp("Trying WoRMs EXACT match for scientific name: '{0}'.".format(original_scientific_name))
matching_worms_record = worms.aphia_record_by_exact_taxon_name(original_scientific_name)
if matching_worms_record is not None:
timestamp('WoRMs EXACT match was SUCCESSFUL.')
worms_match_result = 'exact'
# otherwise try a fuzzy match
else:
timestamp('EXACT match FAILED.')
timestamp("Trying WoRMs FUZZY match for scientific name: '{0}'.".format(original_scientific_name))
matching_worms_record = worms.aphia_record_by_fuzzy_taxon_name(original_scientific_name)
if matching_worms_record is not None:
timestamp('WoRMs FUZZY match was SUCCESSFUL.')
worms_match_result = 'fuzzy'
else:
timestamp('WoRMs FUZZY match FAILED.')
# if either match succeeds extract the LSID for the taxon
if matching_worms_record is not None:
worms_lsid = matching_worms_record['lsid']
# @END find_matching_worms_record
##############################################################################################
# @BEGIN reject_records_not_in_worms
# @IN original_record
# @IN matching_worms_record
# @PARAM rejected_data_file_name
# @PARAM output_field_delimiter
# @OUT rejected_data @FILE file:{rejected_data_file_name}
# reject the currect record if not matched successfully against WoRMs
if worms_match_result is None:
# open file for storing rejected data if not already open
if 'rejected_data' not in locals():
rejected_data = csv.DictWriter(open(rejected_data_file_name, 'w'),
input_data.fieldnames,
delimiter=output_field_delimiter)
rejected_data.writeheader()
# write current record to rejects file
timestamp('REJECTED record {0:03d}.'.format(record_num))
rejected_data.writerow(original_record)
rejected_record_count += 1
# skip to processing of next record in input file
continue
# @END reject_records_not_in_worms
##############################################################################################
# @BEGIN update_scientific_name
# @IN original_scientific_name
# @IN matching_worms_record
# @OUT updated_scientific_name
updated_scientific_name = None
# get scientific name from WoRMs record if the taxon name match was fuzzy
if worms_match_result == 'fuzzy':
updated_scientific_name = matching_worms_record['scientificname']
# @END update_scientific_name
##############################################################################################
# @BEGIN update_authorship
# @IN matching_worms_record
# @IN original_authorship
# @OUT updated_authorship
updated_authorship = None
# get the scientific name authorship from the WoRMS record if different from input record
worms_name_authorship = matching_worms_record['authority']
if worms_name_authorship != original_authorship:
updated_authorship = worms_name_authorship
# @END update_authorship
##############################################################################################
# @BEGIN compose_cleaned_record
# @IN original_record
# @IN worms_lsid
# @IN updated_scientific_name
# @IN original_scientific_name
# @IN updated_authorship
# @IN original_authorship
# @OUT cleaned_record
cleaned_record = original_record
cleaned_record['LSID'] = worms_lsid
cleaned_record['WoRMsMatchResult'] = worms_match_result
if updated_scientific_name is not None:
timestamp("UPDATING scientific name from '{0}' to '{1}'.".format(
original_scientific_name, updated_scientific_name))
cleaned_record['scientificName'] = updated_scientific_name
cleaned_record['originalScientificName'] = original_scientific_name
if updated_authorship is not None:
timestamp("UPDATING scientific name authorship from '{0}' to '{1}'.".format(
original_authorship, updated_authorship))
cleaned_record['scientificNameAuthorship'] = updated_authorship
cleaned_record['originalAuthor'] = original_authorship
# @END compose_cleaned_record
##############################################################################################
# @BEGIN write_clean_data_set
# @PARAM cleaned_data_file_name
# @PARAM output_field_delimiter
# @IN cleaned_record
# @OUT cleaned_data @FILE file:{cleaned_data_file_name}
# open file for storing cleaned data if not already open
if 'cleaned_data' not in locals():
cleaned_record_field_names = input_data.fieldnames + \
['LSID', 'WoRMsMatchResult', 'originalScientificName', 'originalAuthor']
cleaned_data = csv.DictWriter(open(cleaned_data_file_name, 'w'),
cleaned_record_field_names,
delimiter=output_field_delimiter)
cleaned_data.writeheader()
timestamp('ACCEPTED record {0:03d}.'.format(record_num))
cleaned_data.writerow(cleaned_record)
accepted_record_count += 1
# @END write_clean_data_set
print
timestamp("Wrote {0} accepted records to '{1}'.".format(accepted_record_count, cleaned_data_file_name))
timestamp("Wrote {0} rejected records to '{1}'.".format(rejected_record_count, rejected_data_file_name))
def __init__(self):
""" Initialize a SOAP client using the WSDL for the WoRMS Aphia names service"""
self._worms = WoRMSService()