If I didn’t look at it, I might have […] Because If I do the same thing with less complex query I got following times: InteractiveSQL execution time: 8ms. Now python is doing the heavy lifting parsing and interpreting the data received from the socket while MySQLdb offloads that to the C library. Looks like the prefetching does not work. In this example, the result printed after "all persons" will be the result of the second query (the list where salesrep='John Doe') and the result printed after “John Doe” will be empty.This happens because the underlying TDS protocol does not have client side cursors. The difference is quite obvious. I don’t know how many people are cheated in by this head map:) The reason for this is that last week, a classmate asked Xiaobian and looked at the sample code of Xiaobian and knocked on the code. After upgrade to Python 3.5.0 1 I noticed that one query generated by SQLAlchemy in my web app executes very slow.. Sample script: import sqlite3 conn = sqlite3.connect('example.db') c = conn.cursor() c.execute(''' SELECT * FROM companies WHERE EXISTS (SELECT 1 FROM companies_branches, branches WHERE companies.id = … The protocol requires that the client flush the results from the first query before it can begin another query. Slow(er) queries Example of executing and reading a query into a pandas dataframe - cx_oracle_to_pandas.py Up until now we have been using fetchall() method of cursor object to fetch the records. The fetchall() fetches all rows in the result set and returns a list of tuples. This makes large dataset providing queries even less efficient and the difference is growing with the number of returned rows. The exact same query in Python runs in 5 minutes or more. dbisql works fine with the same query and connection. I noticed that when you use python sqlanydb module on a WAN (when the server is in a different datacenter), the sqlanydb module is very slow : it can take 16-30 seconds to fetch 1000 rows. I did a job that scribe data from web site and put it in MSSQL. As a result MySQLdb has fetchone() and fetchmany() methods of cursor object to fetch records more efficiently. PyMySQL Evaluation. Python execute time: 2.3ms and fetchall time 0.9ms. An inordinately large number of rows would be indicated by a very slow call to fetchall() at the DBAPI level: 2 0.300 0.600 0.300 0.600 { method 'fetchall' of 'sqlite3.Cursor' objects } In python execute time is 4ms and fetchall time is 328.8ms. And here are the results:… That helped a little, but it's still unusably slow. I have a sqlite3 database created in Python 3.4. I wrote it in python using pyodbc. But I discovered writing multiple record to MSSQL server using pyodbc is very slow So after some digging in I found a way to make it much faster. 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