This python guide is intended to those who already know python and want a mind refresh or looking for a specific syntax.
-as this guide doesn't elaborate in explaining thing that a programmer would already know -like: variable, function, csv, json-
additionally, this guide is not intended to be a replacement for reading official Python documentation.
guide version: 2.1.0 | python version: 3.10
| Part of Version | Explanation |
| func main() { | |
| s := time.Now() | |
| args := os.Args[1:] | |
| if len(args) != 6 { // for format LogExtractor.exe -f "From Time" -t "To Time" -i "Log file directory location" | |
| fmt.Println("Please give proper command line arguments") | |
| return | |
| } | |
| startTimeArg := args[1] | |
| finishTimeArg := args[3] |
| FROM postgres:15-alpine | |
| LABEL maintainer="Jordan Gould <jordangould@gmail.com>" | |
| # Based on https://github.com/andreaswachowski/docker-postgres/blob/master/initdb.sh | |
| ENV PG_JOBMON_VERSION v1.4.1 | |
| ENV PG_PARTMAN_VERSION v4.7.1 | |
| # Install pg_jobmon | |
| RUN set -ex \ | |
| \ |
| ############################################################################## | |
| # | |
| # Author: Miku Laitinen / Avoin.Systems | |
| # Copyright 2019 Avoin.Systems | |
| # | |
| # This program is free software: you can redistribute it and/or modify | |
| # it under the terms of the GNU Affero General Public License as | |
| # published by the Free Software Foundation, either version 3 of the | |
| # License, or (at your option) any later version. | |
| # |
Please refer to ZFS 2-3x slower than EXT4 to see how ZFS defaults + Postgres defaults severely underperform EXT4 defaults + Postgres defaults (and also to know more about the system on which these benchmarks were performed). This page documents how to tune ZFS + Postgres to give better performance for the tpcb-like benchmark.
Please do not copy these settings blindly because I am myself not clear on why/how these settings had the impact they did. For example, I cannot explain why full_page_writes=off independently did not give that much boost, nor did an optimized PG configuration. However, putting both of them together gave a 2-4x boost compared to baseline numbers.
| package main | |
| import ( | |
| "github.com/jinzhu/gorm" | |
| _ "github.com/jinzhu/gorm/dialects/mysql" | |
| "github.com/satori/go.uuid" | |
| "fmt" | |
| ) | |
| type Email struct { |
AWS 학습 링크집 시리즈
| #!/bin/bash | |
| # variables | |
| # listening address for jupyter. set to localhost if only accessing locally. | |
| read -p $'\n\e[32mServer static IP address\e[m: ' ipAddress | |
| # Set this either as parent or direct working directory of the project you want to work on. | |
| read -p $'\n\e[32mProject Parent Directory\e[m: ' WorkingDirectory | |
| echo -e "\n...\e[32mGenerating random token\e[m...\n" |
| ;; database name = connect string | |
| ;; | |
| ;; connect string params: | |
| ;; dbname= host= port= user= password= | |
| ;; client_encoding= datestyle= timezone= | |
| ;; pool_size= connect_query= | |
| [databases] | |
| odoo1 = host=127.0.0.1 auth_user=odoo dbname=odoo1 port=5432 | |
| odoo2 = host=127.0.0.1 auth_user=odoo dbname=odoo2 port=5432 | |
| odoo3 = host=127.0.0.1 auth_user=odoo port=5432 dbname=odoo3 |
