我正在尝试使用python将来自英国公司House csv文件的数据批量加载到PostgreSQL中。
我将每一行数据转换成一个dict列表，然后使用一个unnest语句将数据解压成一个大容量sql语句，下面是我正在做的一个示例（源代码中还有很多字段）。。。
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)
只要所有内容都转换为字符串，这段代码就可以正常工作，但是当我尝试将数据转换为日期时，每次a日期记录没有值时，我都会得到以下错误（注意，这个值被条件设置为
None，所以应该加载到PostgreSQL中）。Error could not determine polymorphic type because input has type "unknown"
我尝试在unnest语句中将类型转换为
::DATE，如下所示：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
;
'''
但这没用。一张本地人的照片显示了一条记录的以下内容：
('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']})
我不确定这是否相关，但我注意到，一旦从dict中取出局部变量，它们都会按如下方式放置在一个列表中：
['None']，但是导致问题的日期变量（dissolutiondate）被作为一个真正的值给出。 最佳答案
好 啊。因此，问题是psycopg2和postgresql在处理数组时的交互方式，pscyopg中曾经存在一个错误，不允许将空值数组导入postgres，详情如下：
https://github.com/psycopg/psycopg2/issues/285
正如Vao Tsun指出的，解决方案是在每个unnest语句的强制转换中，它必须是显式的，但也必须在每个数据类型说明符之后包含[]括号。
在这里，我还错误地将变量转换为python中的字符串：
companyname=[str(r['companyname']) for r in data]
导致
None值变成'None'值的字符串。下面是正确代码的示例：
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]