使用 Psycopg2 和 unnest 时的“未知”数据类型
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【中文标题】使用 Psycopg2 和 unnest 时的“未知”数据类型【英文标题】:"Unknown" datatype when using Psycopg2 and unnest 【发布时间】:2017-01-20 10:41:20 【问题描述】:我正在尝试使用 python 将 UK Companies House csv 文件中的数据批量加载到 PostgreSQL 中。
我将每一行数据转换为一个字典列表,然后使用一个 unnest 语句将数据解压缩为一个大容量的 sql 语句,这是我正在做的一个示例,(还有更多字段在源代码中)...
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,此代码就可以正常工作,但是当我尝试将数据转换为日期时,每次日期记录没有值时都会出现以下错误(注意,此值已设置为 @987654323 @由条件,所以应该加载到PostgreSQL)。
Error could not determine polymorphic type because input has type "unknown"
我已尝试在 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
;
'''
但这无济于事。我的当地人的打印显示以下一条记录:
('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,但我注意到局部变量一旦从字典中取出,就会全部放在一个列表中:['None']
但导致问题的日期变量(dissolutiondate
) 作为真正的None
值给出。
【问题讨论】:
unnest( %(dissolutiondate)s )::DATE
尝试替换为unnest( %(dissolutiondate)s )::DATE[]
最好的办法是***.com/a/30985541/131874
【参考方案1】:
好的。所以问题原来是 psycopg2 和 postgresql 在处理数组时交互的方式,pscyopg 中曾经有一个错误,不允许将空值数组导入 postgres,如下所述:
https://github.com/psycopg/psycopg2/issues/285
正如 Vao Tsun 指出的那样,解决方案在于每个 unnest 语句的强制转换,这必须是明确的,但还必须在每个数据类型说明符之后包含 []
括号。
我在这里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
值转换为'None'
值的字符串。
这是正确代码的示例:
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]
【讨论】:
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