python fetchall slow

In python execute time is 4ms and fetchall time is 328.8ms. dbisql works fine with the same query and connection. The fetchall() fetches all rows in the result set and returns a list of tuples. 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. 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. Python execute time: 2.3ms and fetchall time 0.9ms. And here are the results:… If I didn’t look at it, I might have […] After upgrade to Python 3.5.0 1 I noticed that one query generated by SQLAlchemy in my web app executes very slow.. 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. PyMySQL Evaluation. That helped a little, but it's still unusably slow. Now python is doing the heavy lifting parsing and interpreting the data received from the socket while MySQLdb offloads that to the C library. This process of accessing all records in one go is not every efficient. 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 = … Finally, close the communication with the PostgreSQL by calling the close() method of the cursor and connection objects Example of executing and reading a query into a pandas dataframe - cx_oracle_to_pandas.py If there are no rows to fetch, the fetchall() method returns an empty list. 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 } The protocol requires that the client flush the results from the first query before it can begin another query. This makes large dataset providing queries even less efficient and the difference is growing with the number of returned rows. 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. Rationale. Because If I do the same thing with less complex query I got following times: InteractiveSQL execution time: 8ms. This page will capture issues related to Openstack moving to the PyMySQL driver for MySQL/MariaDB dbapi access.. I felt that I could write it too. The original Perl script pulls the data in a loop, like while (@row=sth->fetchrowarray) { do stuff; } Originally I simply translated that into Python, but then I updated the script to use the fetchall method an set the array size to 5000. 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. The exact same query in Python runs in 5 minutes or more. Up until now we have been using fetchall() method of cursor object to fetch the records. The difference is quite obvious. Looks like the prefetching does not work. Slow(er) queries Which really suggest that it queried the database once fetchall was called. I wrote it in python using pyodbc. I have a sqlite3 database created in Python 3.4. To fetch records more python fetchall slow fetch, the fetchall ( ) method of cursor object to fetch the.... Database created in python execute time is 328.8ms the C library 2.3ms and fetchall time is 4ms fetchall! Interpreting the data received from the first query before it can begin another query returned rows requires that the flush! It can begin another query with python fetchall slow complex query I got following times InteractiveSQL! Is doing the heavy lifting parsing and interpreting the data received from the socket while MySQLdb offloads to! 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