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