gmba_django/app/management/commands/import.py

440 lines
18 KiB
Python
Raw Normal View History

from django.core.management.base import BaseCommand, CommandError
from django.apps import apps
from django.db.utils import IntegrityError
2021-11-22 14:18:36 +00:00
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": "Range",
"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('--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))
2021-11-10 17:12:40 +00:00
models_to_ignore = ['Range', 'NamesImport', 'ImportGeom210915', 'Organization', 'AddElevation',
'GMBA_V2_Centroid', 'Person', 'PeopleRange', 'PeopleFunction', "PeopleResource",
"RangeCountry", "RangeNameTranslation", "RangeOnlineInfo", "ResourceRange",
2021-11-10 17:12:40 +00:00
"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']
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
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 = {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)
2021-11-22 14:41:57 +00:00
try:
m = _model(**_object_dict)
m.save()
except Exception as ex:
print('-----')
print(str(ex))
print('----------------')
continue
print("Done importing %s" % str(_model))
def handle_object_dict(object_dict, model_name):
if model_name == 'Range':
# Reinstate range_name key
object_dict['range_name'] = object_dict['range_name_id']
object_dict.pop('range_name_id')
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']))
2021-11-22 14:18:36 +00:00
if 'status' in object_dict:
print('Getting status of %s' % object_dict['status'])
2021-11-22 14:28:48 +00:00
if object_dict['status'] == '':
object_dict['status'] = 0
2021-11-22 14:21:39 +00:00
object_dict['status'] = PeopleStatus.objects.get(id=int(object_dict['status']))
2021-11-22 14:24:46 +00:00
if 'country_lookup' in object_dict:
2021-11-22 14:26:09 +00:00
print('Getting country of %s' % object_dict['country_lookup'])
2021-11-22 14:27:59 +00:00
if object_dict['country_lookup'] == '':
object_dict['country_lookup'] = 0
2021-11-22 14:24:46 +00:00
object_dict['country'] = Country.objects.get(id=int(object_dict['country_lookup']))
2021-11-22 14:26:09 +00:00
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
print(object_dict)
if object_dict is None:
print("Object None for %s" % model_name)
return object_dict