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我正在尝试使用该pd.to_sql方法将数据框推送到 SQL 服务器中。langyuage-python 3.6，熊猫版pandas(0.25.1)

引擎变量

engine = create_engine("mssql+pyodbc:///?odbc_connect=%s"%PARAM,pool_size = 20,max_overflow =10,pool_recycle=60,pool_timeout=30)

这是调用staging_standardisation()方法的主要脚本。

import pyodbc
from sqlalchemy import create_engine,event
import pandas as pd
from utils import engine

@event.listens_for(engine, 'before_cursor_execute')
def plugin_bef_cursor_execute(conn, cursor, statement, params, context,executemany):
   if executemany:
       cursor.fast_executemany = True  # replace from execute many to fast_executemany.
       cursor.commit()

table = "table_name"
column_name = ["Some column_names"] #selecting some columns names

column_obj = {"a":"A",
              "b":"B",
              "c":"C"
              }

staging_standardisation(engine=engine, table_name=table, column_names=column_name, column_obj=column_obj)

staging_standardisation 方法

def staging_standardisation(engine, table_name, column_names, column_obj, **kwargs):
    try:
        query = "SELECT * FROM  dbo.License_Search"
        sql_df = pd.read_sql(query, engine)
        df = sql_df[column_names]
        df = df.rename(index=str, columns=column_obj)
        try:
            if 'authority_id' in column_obj.values():
                pass
            else:

                df['authority_id'] =53

        except KeyError:
            df['authority_id'] = None
    try:
        df.to_sql(name=staging_table, con=engine, index=False, if_exists='append') # this line causing error.

    except Exception as exe:
        print(table_name, exe)

投掷错误

(pyodbc.ProgrammingError) ('42000', '[42000] [Microsoft][ODBC Driver 17 for SQL Server][SQL Server]
The server failed to resume the transaction. Desc:8c00000007. 
(3971) (SQLEndTran); [42000] [Microsoft][ODBC Driver 17 for SQL Server][SQL Server]The 
transaction active in this session has been committed or aborted by another session. (3926)')
(Background on this error at: http://sqlalche.me/e/f405)
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1 回答 1

2

问题出在铸件上。在数据框中日期（列）类型是一个字符串。然后我将列类型转换为日期时间。

仅供参考：vs 代码显示的错误是有限的。我们在 jupyter notebook 中运行了一个单独的测试，我们有完整的错误，发现它是日期列

def staging_standardisation(engine, table_name, column_names, column_obj, **kwargs):
    try:
        query = "SELECT * FROM  dbo.License_Search"
        sql_df = pd.read_sql(query, engine)
        df = sql_df[column_names]
        df = df.rename(index=str, columns=column_obj)
        df['Date'] = pd.to_datetime(df['Date'])
        try:
            if 'authority_id' in column_obj.values():
                pass
            else:

                df['authority_id'] =53

        except KeyError:
            df['authority_id'] = None
    try:
        df.to_sql(name=staging_table, con=engine, index=False, if_exists='append') # this line causing error.

    except Exception as exe:
        print(table_name, exe)

欲了解更多信息，请阅读这篇文章

于 2019-11-18T10:16:41.927 回答