Python 如何在pandas中使用sqlalchemy执行具有多个日期参数的sql存储过程

我能够执行不带参数的存储过程：

import pandas as pd
import sqlalchemy
import pyodbc
import datetime as dt  

engine = sqlalchemy.create_engine('mssql+pymssql://MyServer/MyDB')
df = pd.read_sql_query('EXEC dbo.TestProcedure' , engine)  # stored procedure without parameters
print(df)

import pandas as pd
import sqlalchemy
import pyodbc
import datetime as dt  

myparams = ['2017-02-01','2017-02-28', None]  # None substitutes NULL in sql

engine = sqlalchemy.create_engine('mssql+pymssql://MyServer/MyDB')
df = pd.read_sql_query('EXEC PythonTest_Align_RSrptAccountCurrentMunich @EffectiveDateFrom=?,@EffectiveDateTo=?,@ProducerLocationID=?', engine, params=myparams)
print(df)

  File "src\pymssql.pyx", line 465, in pymssql.Cursor.execute
sqlalchemy.exc.ProgrammingError: (pymssql.ProgrammingError) (102, b"Incorrect syntax near '?'.DB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\n")
[SQL: EXEC PythonTest_Align_RSrptAccountCurrentMunich @EffectiveDateFrom=?,@EffectiveDateTo=?,@ProducerLocationID=?]
[parameters: ('2017-02-01', '2017-02-28', None)]
(Background on this error at: http://sqlalche.me/e/f405)

但无法使用参数执行存储过程：

import pandas as pd
import sqlalchemy
import pyodbc
import datetime as dt  

engine = sqlalchemy.create_engine('mssql+pymssql://MyServer/MyDB')
df = pd.read_sql_query('EXEC dbo.TestProcedure' , engine)  # stored procedure without parameters
print(df)

import pandas as pd
import sqlalchemy
import pyodbc
import datetime as dt  

myparams = ['2017-02-01','2017-02-28', None]  # None substitutes NULL in sql

engine = sqlalchemy.create_engine('mssql+pymssql://MyServer/MyDB')
df = pd.read_sql_query('EXEC PythonTest_Align_RSrptAccountCurrentMunich @EffectiveDateFrom=?,@EffectiveDateTo=?,@ProducerLocationID=?', engine, params=myparams)
print(df)

  File "src\pymssql.pyx", line 465, in pymssql.Cursor.execute
sqlalchemy.exc.ProgrammingError: (pymssql.ProgrammingError) (102, b"Incorrect syntax near '?'.DB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\n")
[SQL: EXEC PythonTest_Align_RSrptAccountCurrentMunich @EffectiveDateFrom=?,@EffectiveDateTo=?,@ProducerLocationID=?]
[parameters: ('2017-02-01', '2017-02-28', None)]
(Background on this error at: http://sqlalche.me/e/f405)

错误消息：

import pandas as pd
import sqlalchemy
import pyodbc
import datetime as dt  

engine = sqlalchemy.create_engine('mssql+pymssql://MyServer/MyDB')
df = pd.read_sql_query('EXEC dbo.TestProcedure' , engine)  # stored procedure without parameters
print(df)

import pandas as pd
import sqlalchemy
import pyodbc
import datetime as dt  

myparams = ['2017-02-01','2017-02-28', None]  # None substitutes NULL in sql

engine = sqlalchemy.create_engine('mssql+pymssql://MyServer/MyDB')
df = pd.read_sql_query('EXEC PythonTest_Align_RSrptAccountCurrentMunich @EffectiveDateFrom=?,@EffectiveDateTo=?,@ProducerLocationID=?', engine, params=myparams)
print(df)

  File "src\pymssql.pyx", line 465, in pymssql.Cursor.execute
sqlalchemy.exc.ProgrammingError: (pymssql.ProgrammingError) (102, b"Incorrect syntax near '?'.DB-Lib error message 20018, severity 15:\nGeneral SQL Server error: Check messages from the SQL Server\n")
[SQL: EXEC PythonTest_Align_RSrptAccountCurrentMunich @EffectiveDateFrom=?,@EffectiveDateTo=?,@ProducerLocationID=?]
[parameters: ('2017-02-01', '2017-02-28', None)]
(Background on this error at: http://sqlalche.me/e/f405)

---

如何使用

sqlalchemy

传递参数？

Read\u sql仅用于读取表。要使用参数执行某些操作，请尝试使用

engine.execute（您的sql查询）#您可以尝试输入参数，以了解如何给出 在sql中

---

engine.execution\u options（autocommit=True）

如果执行带有参数占位符的原始SQL查询，则必须使用DBAPI层支持的。pymssql使用的是“格式”参数样式

%s

，而不是“qmark”参数样式

？

（pyodbc使用的）

但是，可以通过将查询包装在SQLAlchemy

text

对象中并一致使用“named”参数样式来避免歧义。SQLAlchemy将自动将参数占位符转换为您正在使用的DBAPI的适当样式。例如，要调用名为

echo\u datetimes

的存储过程：

导入日期时间
将sqlalchemy作为sa导入
# ...
query=sa.text（“EXEC echo\u datetimes@p1=：param1，@p2=:param2”）
值={'param1'：datetime.datetime（2020,1,1,1,1,1），
“param2”：datetime.datetime（2020,2,2,2,2,2）}
df=pd.read\u sql\u查询（查询、引擎、参数=值）
打印（df）
#dt_开始dt_结束
# 0 2020-01-01 01:01:01 2020-02-02 02:02:02