497 lines
21 KiB
Python
497 lines
21 KiB
Python
import django.db.utils
|
||
from django.core.management.base import BaseCommand, CommandError
|
||
from django.apps import apps
|
||
|
||
from django.db.utils import IntegrityError
|
||
|
||
from app.models import *
|
||
|
||
import csv
|
||
import json
|
||
|
||
|
||
class Command(BaseCommand):
|
||
help = 'Imports csv to DB'
|
||
csv_files_models_dict = {
|
||
"v2-LU_GMBA_SpeciesGroups.csv": "GMBA_SpeciesGroup",
|
||
"v2-LU_Countries.csv": "Country",
|
||
"v2-LU_Languages.csv": "Language",
|
||
"v2-LU_Sources.csv": "Source",
|
||
"v2-LU_RedListCategories.csv": "RedListCategory",
|
||
"v2-LU_RangeTypes.csv": "RangeType",
|
||
"v2-LU_PeopleStatus.csv": "PeopleStatus",
|
||
"v2-LU_TrendsQuantity.csv": "TrendsQuantity",
|
||
"v2-LU_TrendsQuality.csv": "TrendsQuality",
|
||
"v2-LU_TaxonUnit.csv": "TaxonUnit",
|
||
"v2-LU_TaxonStatus.csv": "TaxonStatus",
|
||
|
||
"v2-Ranges-cleaned.csv": "MountainRange",
|
||
"v2-AddElevations.csv": "AddElevation",
|
||
|
||
"v2-GMBA_Function.csv": "GMBA_function",
|
||
"v2-Gmba_V2_centroid.csv": "GMBA_V2_Centroid",
|
||
"v2-ImportGeom210915.csv": "ImportGeom210915",
|
||
"v2-LanguageLink.csv": "LanguageLink",
|
||
"v2-Keywords.csv": "Keyword",
|
||
"v2-NamesImport.csv": "NamesImport",
|
||
"v2-Organisations-cleaned.csv": "Organization",
|
||
"v2-Peaks.csv": "Peak",
|
||
|
||
"v2-People.csv": "Person",
|
||
"v2-PeopleRanges.csv": "PeopleRange",
|
||
"v2-PeopleFunction.csv": "PeopleFunction",
|
||
"v2-Resources.csv": "Resource",
|
||
|
||
"v2-PeopleResources.csv": "PeopleResource",
|
||
"v2-RangeCountries.csv": "RangeCountry",
|
||
"v2-RangeNameTranslations.csv": "RangeNameTranslation",
|
||
"v2-RangeOnlineInfo.csv": "RangeOnlineInfo",
|
||
"v2-ResourceRanges.csv": "ResourceRange",
|
||
"v2-ResourceKeywords.csv": "ResourceKeyword",
|
||
"v2-Repositories.csv": "Repository",
|
||
|
||
"v2-Species.csv": "Species",
|
||
"v2-Searches.csv": "Search",
|
||
"v2-TaxonRange.csv": "TaxonRange",
|
||
"v2-SpeciesRange.csv": "SpeciesRange"
|
||
|
||
}
|
||
cols_to_django_fields = {
|
||
"ID": 'id',
|
||
"Source": 'source',
|
||
"RangeName": 'range_name_id',
|
||
"LanguageTranslation": 'language_translation_id',
|
||
"RangeNameTranslation": 'range_name_translation',
|
||
"GMBA_ID_v2": 'gmba_v2_id',
|
||
"Elev_Min": 'elev_min',
|
||
"Elev_Max": 'elev_max',
|
||
"Elev_Range": 'elev_range',
|
||
"TaxonStatus": 'taxon_status',
|
||
"InfoSource": 'info_source',
|
||
"URL": 'url',
|
||
"GMBA function": 'gmba_function',
|
||
"TaxonUnit": 'taxon_unit',
|
||
"Range_ID": 'id',
|
||
"RangeNameMap": 'range_name_map',
|
||
"RangeNameAscii": 'range_name_ascii',
|
||
"RangeNameLanguage": 'range_name_language',
|
||
"MotherRange": 'mother_range',
|
||
"Feature": 'feature',
|
||
"MapUnit": 'map_unit',
|
||
"Level": 'level',
|
||
"LevelText": 'level_text',
|
||
"Level_1": 'level_1',
|
||
"Level_2": 'level_2',
|
||
"Level_3": 'level_3',
|
||
"Latitude": 'latitude',
|
||
"Longitude": 'longitude',
|
||
"Orogeny": 'orogeny',
|
||
"Area": 'area',
|
||
"GMBA_V1_ID": 'GMBA_v1_id',
|
||
"Countries": 'countries',
|
||
"Peak_Elevation": 'peak_elevation',
|
||
"Peak_Name": 'peak_name',
|
||
"Peak_Latitude": 'peak_latitude',
|
||
"Peak_Longitude": 'peak_longitude',
|
||
"Comments": 'comments',
|
||
"Checked": 'checked',
|
||
"Range_AlternateID": 'range_alternate_id',
|
||
"GeologicRegion": 'geologic_region',
|
||
"GMBA_V2_ID": 'gmba_v2_id',
|
||
"GMBA_V2_ID_str": 'gmba_v2_id_str',
|
||
"WikiDataID": 'wiki_data_id',
|
||
"WikiDataURL": 'wiki_data_url',
|
||
"Select_300": 'select_300',
|
||
"Gmba_Narrow": 'gmba_narrow',
|
||
"Name_FR": 'name_fr',
|
||
"Name_DE": 'name_de',
|
||
"Name_ES": 'name_es',
|
||
"Name_PT": 'name_pt',
|
||
"Name_CN": 'name_cn',
|
||
"Name_RU": 'name_ru',
|
||
"Name_TR": 'name_tr',
|
||
"Perimeter": 'perimeter',
|
||
"ColorAll": 'color_all',
|
||
"ColorBasic": 'color_basic',
|
||
"Color300": 'color_300',
|
||
"Elev_Low": 'elev_low',
|
||
"Elev_High": 'elev_high',
|
||
"Elev_Avg": 'elev_avg',
|
||
"gridcode": 'gridcode',
|
||
"Trend": 'trend',
|
||
"RepositoryName": 'repository_name',
|
||
"RepositoryURL": 'repository_url',
|
||
"Resource": 'resource_id',
|
||
"Keyword": 'keyword_id',
|
||
"Keyword_ID": 'keyword_id',
|
||
"Mother": 'mother',
|
||
"CN": 'cn',
|
||
"DE": 'de',
|
||
"ES": 'es',
|
||
"FR": 'fr',
|
||
"PT": 'pt',
|
||
"RU": 'ru',
|
||
"TR": 'tr',
|
||
"ResourceTitle": 'resource_title_id',
|
||
"LanguageLetterCode": 'language_letter_code',
|
||
"LanguageNumberCode": 'language_number_code_id',
|
||
"OrgNum1": 'org_num1',
|
||
"Organisation Search": 'organisation_search',
|
||
"OrgAlphaSearch": 'org_alpha_search',
|
||
"Organisation English": 'organisation_english',
|
||
"Organisation 2": 'organisation_2',
|
||
"Organisation 3": 'organisation_3',
|
||
"Organisation Original": 'organisation_original',
|
||
"Acronym": 'acronym',
|
||
"Street": 'street',
|
||
"PO Box": 'po_box',
|
||
"Postcode": 'postcode',
|
||
"City": 'city',
|
||
"Region": 'region',
|
||
"SearchURL": 'search_url',
|
||
"LatLon": 'lat_long',
|
||
"URL Org": 'url',
|
||
"Tel Org": 'tel',
|
||
"Email Org": 'email',
|
||
"Country": 'country_id',
|
||
"Tags": 'tags',
|
||
"Description": 'description',
|
||
"Northing": 'northing',
|
||
"Easting": 'easting',
|
||
"Category": 'category',
|
||
"Subject": 'subject',
|
||
"Title": 'title',
|
||
"Citation": 'citation',
|
||
"Type": 'type',
|
||
"Abstract": 'abstract',
|
||
"AuthorKeywords": 'author_keywords',
|
||
"Lat": 'lat',
|
||
"Lon": 'lon',
|
||
"Stars": 'stars',
|
||
"PEGASuS_Check_map_with_author": 'PEGASuS_Check_map_with_author',
|
||
"PEGASuS_polygon_ID": 'PEGASuS_polygon_ID',
|
||
"PEGASuS_Polygon_comments": 'PEGASuS_Polygon_comments',
|
||
"PEGASuS_Assessment_ID": 'PEGASuS_Assessment_ID',
|
||
"GLORIA": 'gloria',
|
||
"GNOMO": 'gnomo',
|
||
"LTER": 'lter',
|
||
"LTSER": 'ltser',
|
||
"MIREN": 'miren',
|
||
"TEAM": 'team',
|
||
"Inventory": 'inventory',
|
||
"DOI": 'doi',
|
||
"ShortName": 'short_name',
|
||
"FormalName": 'formal_name',
|
||
"Membership within the UN System": 'membership_within_un_system',
|
||
"Membership within the UN System": 'membership_within_un_system',
|
||
"Continent": 'continent',
|
||
"EU_MS": 'eu_ms',
|
||
"EEA_MS": 'eea_ms',
|
||
"ISO3": 'iso3',
|
||
"ISO2": 'iso2',
|
||
"Point_Name": 'point_name',
|
||
"Elevation": 'elevation',
|
||
"Link": 'link',
|
||
"Repository": 'repository_id',
|
||
"SearchString": 'search_string',
|
||
"SearchDate": 'search_date',
|
||
"Result": 'result',
|
||
"NumberOfRecords": 'number_of_records',
|
||
"Stored": 'stored',
|
||
"SpeciesGroup": 'species_group',
|
||
"MrMrs": 'mr_mrs',
|
||
"First name": 'first_name',
|
||
"Last name": 'last_name',
|
||
"Full name": 'full_name',
|
||
"SearchName": 'search_name',
|
||
"e-mail 1": 'contact_email',
|
||
"e-mail 2": 'email_2',
|
||
"Skype": 'skype',
|
||
"Professional phone": 'professional_phone',
|
||
"Mobile number": 'mobile_number',
|
||
"Field of expertise": 'field_of_expertise',
|
||
"Biography": 'biography',
|
||
"Position": 'position',
|
||
"Status": 'status',
|
||
"Entry date": 'entry_date',
|
||
"Newsletter": 'news_letter',
|
||
"CountryLookup": 'country_lookup',
|
||
"Organisation": 'organization_id',
|
||
"Birds": 'birds',
|
||
"Mammals": 'mammals',
|
||
'Reptiles': 'reptiles',
|
||
'Amphibians': 'amphibians',
|
||
'Fish': 'fish',
|
||
'Insects': 'insects',
|
||
'Molluscs': 'molluscs',
|
||
'Crustaceans': 'crustaceans',
|
||
'Arachnids': 'arachnids',
|
||
'Angiosperms': 'angiosperms',
|
||
'Gymnosperms': 'gymnosperms',
|
||
'Fungi': 'fungi',
|
||
'Algae': 'algae',
|
||
'Microbes': 'microbes',
|
||
'Biological field sampling': 'biological_field_sampling',
|
||
'Data mining': 'data_mining',
|
||
'Remote sensing': 'remote_sensing',
|
||
'GIS': 'gis',
|
||
'Spatial analysis': 'spatial_analysis',
|
||
'Statistical analysis': 'statistical_analysis',
|
||
'Modelling': 'modelling',
|
||
'Assessment': 'assessment',
|
||
'Meta-analysis': 'meta_analysis',
|
||
'Synthesis': 'synthesis',
|
||
'Qualitative social science methods (interviews, surveys)': 'qualitative_ssm',
|
||
'Genetic analyses': 'genetic_analyses',
|
||
'Field site': 'field_site',
|
||
'Transect': 'transect',
|
||
'Mountain top': 'mountain_top',
|
||
'Mountain range': 'mountain_range',
|
||
'Landscape': 'landscape',
|
||
'Regional': 'regional',
|
||
'National': 'national',
|
||
'Global': '_global',
|
||
'Geographic area of expertise': 'geographic_area_of_expertise',
|
||
'ProfileOnWeb': 'profile_on_web',
|
||
'Updated': 'updated',
|
||
'ORCID': 'orcid',
|
||
'WebOfScience': 'web_of_science',
|
||
'Twitter': 'twitter',
|
||
'Instagram': 'instagram',
|
||
'ScientificName': 'scientific_name_id',
|
||
'Class': '_class',
|
||
'EnglishName': 'english_name',
|
||
'Language': 'language',
|
||
'Person': 'person_id',
|
||
'Field': 'field_id',
|
||
'Method': 'method_id',
|
||
'Scale': 'scale_id',
|
||
'Function': 'function_id',
|
||
'Range': 'range_id',
|
||
'Endemic': 'endemic',
|
||
'SourceURL': 'source_url',
|
||
'MountainRange': 'mountain_range',
|
||
'TaxonRangeID': 'id',
|
||
'SubRangeOrRegion': 'subrange_or_region',
|
||
'Taxon': 'taxon_id',
|
||
'Distribution': 'distribution',
|
||
'RedList': 'redlist',
|
||
'CountUnit': 'count_unit',
|
||
'NumberUnits': 'number_of_units',
|
||
'Remarks': 'remarks',
|
||
'RangeType': 'range_type',
|
||
'Role': 'role',
|
||
'RedListCategory': 'red_list_category'
|
||
}
|
||
|
||
def add_arguments(self, parser):
|
||
parser.add_argument('--path', type=str, help="file path")
|
||
parser.add_argument('--csv_folder_path', type=str, help="Path where the csvs are located")
|
||
parser.add_argument('--model_name', type=str, help="model name")
|
||
parser.add_argument('--app_name', type=str, help="django app name that the model is connected to", default='app')
|
||
parser.add_argument('--mother_range_reload', action='store_true', help="Whether we are trying to reload mother "
|
||
"range relationship")
|
||
parser.add_argument('--all', action='store_true', help="Imports all csvs")
|
||
|
||
# ./manage.py import --path /home/pcoder/Downloads/gmbadb/csvs/v2-LU_RedListCategories.csv --model_name RedListCategory --app_name app
|
||
def handle(self, *args, **options):
|
||
csv.register_dialect(
|
||
'mydialect',
|
||
delimiter=',',
|
||
quotechar='"',
|
||
doublequote=True,
|
||
skipinitialspace=True,
|
||
lineterminator='\n',
|
||
quoting=csv.QUOTE_MINIMAL)
|
||
csv_folder_path = '/home/pcoder/Downloads/gmbadb/csvs'
|
||
if options['csv_folder_path']:
|
||
csv_folder_path = options['csv_folder_path']
|
||
if options.get('all'):
|
||
print("Doing an import of all csvs")
|
||
for csv_file_name, model_name in self.csv_files_models_dict.items():
|
||
print("Importing %s -- %s" % (csv_file_name, model_name))
|
||
models_to_ignore = ['Range', 'NamesImport', 'ImportGeom210915', 'Organization', 'AddElevation',
|
||
'GMBA_V2_Centroid', 'Person', 'PeopleRange', 'PeopleFunction', "PeopleResource",
|
||
"RangeCountry", "RangeNameTranslation", "RangeOnlineInfo", "ResourceRange",
|
||
"ResourceKeyword", "Repository"]
|
||
models_to_ignore = []
|
||
if model_name in models_to_ignore:
|
||
# we have already imported and do not want to spend more time redoing stuff
|
||
continue
|
||
if csv_folder_path.endswith('/'):
|
||
file_path = '%s%s' % (csv_folder_path, csv_file_name)
|
||
else:
|
||
file_path = '%s/%s' % (csv_folder_path, csv_file_name)
|
||
_model = apps.get_model(options.get('app_name', 'app'), model_name)
|
||
with open(file_path, 'r') as csv_file:
|
||
reader = csv.reader(csv_file, dialect='mydialect')
|
||
first = True
|
||
for row in reader:
|
||
if first:
|
||
# Assume the first row to be the header
|
||
header = row
|
||
header = [h.strip('"') for h in header]
|
||
first = False
|
||
continue
|
||
_object_dict = {str(self.cols_to_django_fields.get(key)): str(value.lstrip('"').rstrip('"')) for key, value in zip(header, row)}
|
||
_object_dict = handle_object_dict(_object_dict, model_name)
|
||
m = _model(**_object_dict)
|
||
try:
|
||
m.save()
|
||
except IntegrityError as ie:
|
||
print(str(ie))
|
||
if "UNIQUE constraint failed: range.gmba_v2_id" in str(ie):
|
||
print("======")
|
||
print("Could not save %s" % json.dumps(_object_dict))
|
||
print("======")
|
||
print("Done importing %s" % model_name)
|
||
else:
|
||
_model = apps.get_model(options.get('app_name', 'app'), options['model_name'])
|
||
model_name = options['model_name']
|
||
mother_range_reload = options.get('mother_range_reload')
|
||
k = ''
|
||
csv_file_name = ''
|
||
for k, v in self.csv_files_models_dict.items():
|
||
if v.strip().lower() == model_name.strip().lower():
|
||
csv_file_name = k
|
||
if k == '':
|
||
raise Exception('Could not find a csv file name for model %s' % model_name)
|
||
if csv_folder_path.endswith('/'):
|
||
file_path = '%s%s' % (csv_folder_path, csv_file_name)
|
||
else:
|
||
file_path = '%s/%s' % (csv_folder_path, csv_file_name)
|
||
csv.register_dialect(
|
||
'mydialect',
|
||
delimiter=',',
|
||
quotechar='"',
|
||
doublequote=True,
|
||
skipinitialspace=True,
|
||
lineterminator='\n',
|
||
quoting=csv.QUOTE_MINIMAL)
|
||
with open(file_path, 'r', newline='') as csv_file:
|
||
reader = csv.reader(csv_file, dialect='mydialect')
|
||
first = True
|
||
error_row_count = 0
|
||
total = 0
|
||
for row in reader:
|
||
total += 1
|
||
if first:
|
||
# Assume the first row to be the header
|
||
header = row
|
||
header = [h.strip('"') for h in header]
|
||
first = False
|
||
continue
|
||
if mother_range_reload:
|
||
# We have loaded the range model already and we are attempting to construct the mother_range
|
||
# relationship
|
||
try:
|
||
this_range = MountainRange.objects.get(id=int(row[0]))
|
||
r = MountainRange.objects.get(id=int(row[5])) # default Range which exists already
|
||
this_range.mother_range = r
|
||
this_range.save()
|
||
except MountainRange.DoesNotExist as dne:
|
||
print("this range = %s, mother range --> %s" % (row[0], row[5]))
|
||
print(str(dne))
|
||
error_row_count += 1
|
||
except ValueError as ve:
|
||
print(str(ve))
|
||
error_row_count += 1
|
||
continue
|
||
_object_dict = {self.cols_to_django_fields.get(key): value.lstrip('"').rstrip('"') for key, value in zip(header, row)}
|
||
_object_dict = handle_object_dict(_object_dict, model_name)
|
||
try:
|
||
m = _model(**_object_dict)
|
||
m.save()
|
||
except django.db.utils.IntegrityError as ex1:
|
||
error_row_count += 1
|
||
print(str(ex1))
|
||
print("**********************")
|
||
print(str(_object_dict))
|
||
print("**********************")
|
||
except Exception as ex:
|
||
error_row_count += 1
|
||
print('-----')
|
||
print(str(ex))
|
||
print('----------------')
|
||
continue
|
||
print("Done importing %s" % str(_model))
|
||
print("Total rows = %s, error rows = %s" % (total, error_row_count))
|
||
|
||
|
||
def handle_object_dict(object_dict, model_name, debug=False):
|
||
if model_name == 'Resource':
|
||
object_dict['url'] = object_dict['url'].strip("#")
|
||
for i in ['PEGASuS_Check_map_with_author', 'gloria', 'gnomo', 'lter', 'ltser', 'miren', 'team', 'inventory']:
|
||
if i in object_dict:
|
||
object_dict[i] = True if object_dict[i].lower().strip() == 'true' else False
|
||
if model_name == 'MountainRange':
|
||
# Reinstate range_name key
|
||
object_dict['range_name'] = object_dict['range_name_id']
|
||
object_dict.pop('range_name_id')
|
||
connected_fields = [{'range_name_language': Language}, {'feature': RangeType}]
|
||
for f in connected_fields:
|
||
for k, v in f.items():
|
||
if k in object_dict:
|
||
if debug:
|
||
print('Getting %s of %s' % (k, object_dict[k]))
|
||
if object_dict[k] == '':
|
||
object_dict[k] = 0
|
||
object_dict[k] = v.objects.get(id=int(object_dict[k]))
|
||
if 'mother_range' in object_dict:
|
||
if debug:
|
||
print('Getting mother_range of %s' % object_dict['mother_range'])
|
||
if object_dict['mother_range'] == '':
|
||
object_dict['mother_range'] = 0
|
||
try:
|
||
object_dict['mother_range'] = MountainRange.objects.get(id=0) # default Range which exists already
|
||
except MountainRange.DoesNotExist as dne:
|
||
print(str(dne))
|
||
for i in ['checked']:
|
||
if i in object_dict:
|
||
object_dict[i] = True if object_dict[i].lower().strip() == 'true' else False
|
||
if model_name == 'Keyword':
|
||
object_dict['keyword'] = object_dict['keyword_id']
|
||
object_dict.pop('keyword_id')
|
||
if model_name == 'Organization' and 'country_id' in object_dict:
|
||
object_dict['country'] = object_dict['country_id']
|
||
object_dict.pop('country_id')
|
||
if model_name == 'PeopleRange' and 'mountain_range' in object_dict:
|
||
object_dict['range_id'] = object_dict['mountain_range']
|
||
object_dict.pop('mountain_range')
|
||
if model_name == 'Species' and 'scientific_name_id' in object_dict:
|
||
object_dict['scientific_name'] = object_dict['scientific_name_id']
|
||
object_dict.pop('scientific_name_id')
|
||
if model_name == 'TaxonRange' and 'taxon_id' in object_dict:
|
||
object_dict['taxon'] = object_dict['taxon_id']
|
||
object_dict.pop('taxon_id')
|
||
if model_name == 'Person' and 'organization_id' in object_dict:
|
||
print("organization_id=%s" % object_dict['organization_id'])
|
||
if object_dict['organization_id'] == '' or object_dict['organization_id'] is None:
|
||
object_dict['organization_id'] = '-1'
|
||
else:
|
||
object_dict['organization_id'] = int(float(object_dict['organization_id']))
|
||
if 'status' in object_dict:
|
||
print('Getting status of %s' % object_dict['status'])
|
||
if object_dict['status'] == '':
|
||
object_dict['status'] = 0
|
||
object_dict['status'] = PeopleStatus.objects.get(id=int(object_dict['status']))
|
||
if 'country_lookup' in object_dict:
|
||
print('Getting country of %s' % object_dict['country_lookup'])
|
||
if object_dict['country_lookup'] == '':
|
||
object_dict['country_lookup'] = 0
|
||
object_dict['country'] = Country.objects.get(id=int(object_dict['country_lookup']))
|
||
object_dict.pop('country_lookup')
|
||
for i in ['news_letter', 'birds', 'mammals', 'reptiles', 'amphibians', 'fish', 'insects',
|
||
'molluscs', 'crustaceans', 'arachnids', 'angiosperms', 'gymnosperms', 'fungi',
|
||
'algae', 'microbes', 'biological_field_sampling', 'data_mining', 'remote_sensing',
|
||
'gis', 'spatial_analysis', 'statistical_analysis', 'modelling', 'assessment',
|
||
'meta_analysis', 'synthesis', 'qualitative_ssm', 'genetic_analyses', 'field_site',
|
||
'transect', 'mountain_top', 'mountain_range', 'landscape', 'regional', 'national',
|
||
'_global', 'profile_on_web', 'updated']:
|
||
if i in object_dict:
|
||
object_dict[i] = True if object_dict[i].lower().strip() == 'true' else False
|
||
if object_dict is None:
|
||
print("Object None for %s" % model_name)
|
||
# else:
|
||
# print(object_dict) if str(object_dict) is not None else "Str object dict is None"
|
||
return object_dict
|