使用pymssql将数据插入SQL Server表 [英] Insert Data to SQL Server Table using pymssql
问题描述
我正在尝试将数据帧写入SQL Server表.我的代码:
I am trying to write the data frame into the SQL Server Table. My code:
conn = pymssql.connect(host="Dev02", database="DEVDb")
cur = conn.cursor()
query = "INSERT INTO dbo.SCORE_TABLE VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)"
cur.executemany(query, df_sql)
conn.commit()
cur.close()
conn.close()
df_sql
的维数为(5860, 20)
,即数据框中的列数与SQL Server表中的列数相同.仍然出现以下错误:
The dimension of the df_sql
is (5860, 20)
i.e. the number of columns in the data frame is same as the number of columns in the SQL Server Table. Still I am getting following error:
ValueError:sql中的占位符多于可用的参数
ValueError: more placeholders in sql than params available
以下更新
根据评论之一,我尝试使用turbodbc
如下:
As per one of the comments, I tried using turbodbc
as below:
conn = turbodbc.connect(driver="{SQL Server}", server="Dev02", Database="DEVDb")
conn.use_async_io = True
cur = conn.cursor()
query = "INSERT INTO dbo.STG_CONTACTABILITY_SCORE VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)"
cur.executemany(query, df_sql.values)
cur.commit()
cur.close()
conn.close()
我遇到以下错误:
ValueError:具有多个元素的数组的真值是 模糊的.使用a.any()或a.all()
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
我不明白.怎么了我看到了df_sql.values
,但没有发现任何问题.
I don't get it. What is wrong here. I see df_sql.values
and I don't find anything wrong.
ndarray的第一行如下:
The first row of ndarray is as below:
[nan 'DUSTIN HOPKINS' 'SOUTHEAST MISSOURI STATE UNIVERSITY' 13.0
'5736512217' None None 'Monday' '8:00AM' '9:00AM' 'Summer' None None None
None '2017-12-22 10:39:30.626331' 'Completed' None '1-11KUFFZ'
'Central Time Zone']
推荐答案
我认为您只需要指定每个列名即可,并且不要忘记该表必须具有id字段来收费数据帧索引:
I think you just need to specify each column name and don't forget the table must have the id field to charge the data frame index:
conn = pymssql.connect(host="Dev02", database="DEVDb")
cur = conn.cursor()
query = """INSERT INTO dbo.SCORE_TABLE(index, column1, column2, ..., column20)
VALUES (?, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s,
%s, %s, %s, %s, %s, %s)"""
cur.executemany(query, df_sql)
conn.commit()
cur.close()
conn.close()
好吧,我一直在使用熊猫,并且将最后一个数据帧导出到csv中,如下所示:
Ok I have been using pandas and I exported the last data frame to csv like:
df.to_csv('new_file_name.csv', sep=',', encoding='utf-8')
然后我只使用了pyobdc
和BULK INSERT
Transact-SQL,如:
Then I just used pyobdc
and BULK INSERT
Transact-SQL like:
import pyodbc
conn = pyodbc.connect(DRIVER='{SQL Server}', Server='server_name', Database='Database_name', trusted_connection='yes')
cur = conn.cursor()
cur.execute("""BULK INSERT table_name
FROM 'C:\\Users\\folders path\\new_file_name.csv'
WITH
(
CODEPAGE = 'ACP',
FIRSTROW = 2,
FIELDTERMINATOR = ',',
ROWTERMINATOR = '\n'
)""")
conn.commit()
cur.close()
conn.close()
将15314行记录到SQL Server中是一秒钟.我希望这能给您一个主意.
It was a second to charge 15314 rows into SQL Server. I hope this gives you an idea.
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