I have a database on a 10cpu 56GB ram machine. And there are 2-4 clients that runs a simulation and writes data into this db. first client is a MacBook Pro on Wifi, the first machine that I start my simulation code and runs no problem. The other machines are Mac mini, and an intel and AMD pc’s co0nnected via Gigabit lan connection. When I start simulation on Mac mini, it has error when tries to run to db. I can not find any reason for this. Each client has its own db user, all users have needed grants. They all work on dbeaver.

I’m trying to create a simple relational database for a login in postgreSQL python. I’m new to this and i got stuck trying to execute a variable with the command .execute([local variable]).

I would like to understand, why is my database (postgres in docker) that slow.
Table has 35 columns and 3.8m records. Table size is rouglhy 2GB.

I’m trying to upload data to a postgresql timeseries database.
My problem isn’t a usual coding / engine one, but a logical one.
I have many dataframes, which are varying lengths.
For this example, say I have three – df1 df2 and df3, with lenths 800k, 100k and 120k

import psycopg2 from passlib.hash import bcrypt #from config import host, user, password, db_name try: # connect to the existing database connection = psycopg2.connect( host=”127.0.0.1″, user=”user”, password=”123a”, database=”postgres3″ ) connection.autocommit = True with connection.cursor() as cursor: cursor.execute( “SELECT version();” ) print(f”Server version: {cursor.fetchone()}”) # Generate a strong password from passlib import pwd strong_password = pwd.genword(length=15, charset=’ascii_letters’ […]