我正在尝试使用python将来自UK Companies House csv文件的数据批量加载到PostgreSQL中。
我正在将每行数据转换为一个dicts列表，然后使用一个不需要的语句将数据解压缩到一个高容量的sql语句中，这里是我正在做的一个示例，（还有更多的字段）在来源）...
def buildDict(row)
clean_name = row[0].decode('utf-8').upper()
country_code = lookups.getCountryCodeFromName(row[14])
if len(country_code) > 2:
country_code = None
insert_dict = {
'companyname': row[0],
'companynumber': row[1],
'regaddress_careof': row[2],
'regaddress_pobox': row[3],
'dissolutiondate': row[13],
}
# convert 'None' and '' strings to None
for k, v in six.iteritems(insert_dict):
insert_dict[k] = set_to_null(v)
def fastInsert(data):
sql='''
INSERT INTO uk_data.companies_house(
companyname,
companynumber,
regaddress_careof,
regaddress_pobox,
dissolutiondate
)
SELECT
unnest( %(companyname)s ),
unnest( %(companynumber)s ),
unnest( %(regaddress_careof)s ),
unnest( %(regaddress_pobox)s ),
unnest( %(dissolutiondate)s )
;
'''
companyname=[str(r['companyname']) for r in data]
companynumber=[str(r['companynumber']) for r in data]
regaddress_careof=[str(r['regaddress_careof']) for r in data]
regaddress_pobox=[str(r['regaddress_pobox']) for r in data]
dissolutiondate=[datetime.strptime(r['dissolutiondate'], "%d/%m/%Y") if r['dissolutiondate'] else None for r in data]
execute(sql,locals())
def execute(sql,params={}):
with connect() as connection:
with connection.cursor() as cursor:
if params:
cursor.execute(sql,params)
else:
cursor.execute(sql)
只要将所有内容都转换为字符串，此代码就可以正常运行，但是当我尝试将数据转换为日期时，每次日期记录都没有值时，我会收到以下错误（NB此值已设置为{{ 1}}由条件，所以应该加载到PostgreSQL）。
None我已经尝试在不需要的语句中将类型转换为Error could not determine polymorphic type because input has type "unknown"
，如下所示：
::DATE但这没有帮助。我的当地人的印刷品显示以下单个记录：
sql='''
INSERT INTO uk_data.companies_house(
companyname,
companynumber,
regaddress_careof,
regaddress_pobox,
dissolutiondate
)
SELECT
unnest( %(companyname)s ),
unnest( %(companynumber)s ),
unnest( %(regaddress_careof)s ),
unnest( %(regaddress_pobox)s ),
unnest( %(dissolutiondate)s )::DATE
;
'''
我不确定这是否相关，但我注意到局部变量一旦从dict中取出，都被放在一个列表中：('these are my locals: ', {'regaddress_posttown': ['LEEDS'], 'regaddress_addressline1': ['METROHOUSE 57 PEPPER ROAD'], 'regaddress_addressline2': ['HUNSLET'], 'regaddress_careof': ['None'], 'companystatus': ['Active'], 'companycategory': ['Private Limited Company'], 'companyname': ['! LTD'], 'countryoforigin': ['None'], 'regaddress_pobox': ['None'], 'regaddress_country': ['None'], 'dissolutiondate': None, 'regaddress_postcode': ['LS10 2RU'], 'regaddress_county': ['YORKSHIRE'], 'sql': '
INSERT INTO uk_data.companies_house(
companyname,
companynumber,
regaddress_careof,
regaddress_pobox,
regaddress_addressline1,
regaddress_addressline2,
regaddress_posttown,
regaddress_county,
regaddress_country,
regaddress_postcode,
companycategory,
companystatus,
countryoforigin,
dissolutiondate
)
SELECT
unnest( %(companyname)s ),
unnest( %(companynumber)s ),
unnest( %(regaddress_careof)s ),
unnest( %(regaddress_pobox)s ),
unnest( %(regaddress_addressline1)s ),
unnest( %(regaddress_addressline2)s ),
unnest( %(regaddress_posttown)s ),
unnest( %(regaddress_county)s ),
unnest( %(regaddress_country)s ),
unnest( %(regaddress_postcode)s ),
unnest( %(companycategory)s ),
unnest( %(companystatus)s ),
unnest( %(countryoforigin)s ),
unnest( %(dissolutiondate)s )
;
', 'r': {'regaddress_posttown': 'LEEDS', 'regaddress_careof': None, 'companystatus': 'Active', 'companynumber': '08209948', 'regaddress_addressline1': 'METROHOUSE 57 PEPPER ROAD', 'regaddress_addressline2': 'HUNSLET', 'companycategory': 'Private Limited Company', 'companyname': '! LTD', 'countryoforigin': None, 'regaddress_pobox': None, 'regaddress_country': None, 'dissolutiondate': None, 'regaddress_postcode': 'LS10 2RU', 'regaddress_county': 'YORKSHIRE'}, 'data': [{'regaddress_posttown': 'LEEDS', 'regaddress_careof': None, 'companystatus': 'Active', 'companynumber': '08209948', 'regaddress_addressline1': 'METROHOUSE 57 PEPPER ROAD', 'regaddress_addressline2': 'HUNSLET', 'companycategory': 'Private Limited Company', 'companyname': '! LTD', 'countryoforigin': None, 'regaddress_pobox': None, 'regaddress_country': None, 'dissolutiondate': None, 'regaddress_postcode': 'LS10 2RU', 'regaddress_county': 'YORKSHIRE'}], 'companynumber': ['08209948']})
但是导致的日期变量问题（['None']）以真dissolutiondate值给出。
答案 0 :(得分：1)
确定。所以问题原来是psycopg2和postgresql在处理数组时的交互方式，pscyopg中曾经存在一个错误，它不允许将一个空值数组导入到postgres中，详见此处：
https://github.com/psycopg/psycopg2/issues/285
正如Vao Tsun指出的那样，解决方案是每个不需要的语句的转换，必须是明确的，但也必须在每个数据类型说明符后包含[]括号。
我也错误地将我的变量转换为python中的字符串：
companyname=[str(r['companyname']) for r in data]
导致None值变为'None'值的字符串。
以下是正确代码的示例：
SELECT
unnest( %(companyname)s::TEXT[] ),
unnest( %(companynumber)s::TEXT[] ),
unnest( %(regaddress_careof)s::TEXT[] ),
unnest( %(regaddress_pobox)s::TEXT[] ),
unnest( %(regaddress_addressline1)s::TEXT[] ),
unnest( %(regaddress_addressline2)s::TEXT[] ),
unnest( %(regaddress_posttown)s::TEXT[] ),
unnest( %(regaddress_county)s::TEXT[] ),
unnest( %(regaddress_country)s::TEXT[] ),
unnest( %(regaddress_postcode)s::TEXT[] ),
unnest( %(companycategory)s::TEXT[] ),
unnest( %(companystatus)s::TEXT[] ),
unnest( %(countryoforigin)s::TEXT[] ),
unnest( %(dissolutiondate)s::TIMESTAMP[] ),
和
companyname=[(r['companyname']) for r in data]
companynumber=[(r['companynumber']) for r in data]
regaddress_careof=[(r['regaddress_careof']) for r in data]
regaddress_pobox=[(r['regaddress_pobox']) for r in data]
regaddress_addressline1=[(r['regaddress_addressline1']) for r in data]
regaddress_addressline2=[(r['regaddress_addressline2']) for r in data]
regaddress_posttown=[(r['regaddress_posttown']) for r in data]
regaddress_county=[(r['regaddress_county']) for r in data]
regaddress_country=[(r['regaddress_country']) for r in data]
regaddress_postcode=[(r['regaddress_postcode']) for r in data]
companycategory=[(r['companycategory']) for r in data]
companystatus=[(r['companystatus']) for r in data]
countryoforigin=[(r['countryoforigin']) for r in data]
dissolutiondate=[datetime.strptime(r['dissolutiondate'], "%d/%m/%Y") if r['dissolutiondate'] else None for r in data]