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python speeding up pandas dataframe sql with fast i would like to send a large pandas dataframe to a remote server running ms sql the way i do is by converting a data frame object to a list of tuples and then send it away with pyodbc s executemany function it goes something like this import pyodbc as pdb list of tuples = convert df data frame connection = pdbnnect cnxn str cursor = connectionrsor cursor fast executemany the importance of python in sql server administration some of my previous articles on python provided insight of the basics and the usage of python in sql server 2017 why would a sql server dba be interested in python an overview of python vs powershell for sql server database administration data interpolation and transformation using python in sql server 2017 this article is […] 4 mon developer tasks for impala getting started for first time users ly as you’ll see in chapter 5 you can issue an insert values statement to create new data from literals and function return values you can insert multiple rows through a single statement by including multiple tuples after the values clause we re mend against relying on this technique for production data because it really only applies to very small volumes of web2py the database abstraction layer in this case you will be able to call select insert update and delete to generate sql but not call select insert update and delete in most of the cases you can use do connect=false even without having the required database drivers notice that by default web2py uses utf8 character encoding for databases pyodbc bulk insert from memory
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