Magic words:
psql -U postgresSome interesting flags (to see all, use -h or --help depending on your psql version):
-E: will describe the underlaying queries of the \ commands (cool for learning!)-l: psql will list all databases and then exit (useful if the user you connect with doesn't has a default database, like at AWS RDS)
| <template> | |
| <v-card> | |
| <v-card-text> | |
| {{ category }} | |
| <radio-tree :items="categories" value-key="id" v-model="category" ref="radioTree"></radio-tree> | |
| </v-card-text> | |
| <v-card-actions> | |
| <v-btn @click.stop="nuke()" color="warning">Nuke</v-btn> | |
| </v-card-actions> | |
| </v-card> |
| Lesson 1 - Iterations | |
| - BinaryGap - https://codility.com/demo/results/trainingU2FQPQ-7Y4/ | |
| Lesson 2 - Arrays | |
| - OddOccurrencesInArray - https://codility.com/demo/results/trainingFN5RVT-XQ4/ | |
| - CyclicRotation - https://codility.com/demo/results/trainingSH2W5R-RP5/ | |
| Lesson 3 - Time Complexity | |
| - FrogJmp - https://codility.com/demo/results/training6KKWUD-BXJ/ | |
| - PermMissingElem - https://codility.com/demo/results/training58W4YJ-VHA/ |
| # -*- coding: utf-8 -*- | |
| """ | |
| Copyright 2018-09-09, Wolfgang Kühn | |
| Fast inter-process communication (ipc) for Python (CPython, PyPy, 2.7, 3.6+) on MS-Windows. | |
| It uses shared memory and eventing. | |
| Example rpc style synchronization: | |
| Server (rpc provider): |
| import React from 'react' | |
| import { | |
| ThemeProvider, | |
| theme, | |
| ColorModeProvider, | |
| CSSReset, | |
| Box, | |
| Flex, | |
| IconButton, | |
| useColorMode, |
| #!/usr/bin/env python3 | |
| # -*- coding: UTF-8 -*- | |
| import socket | |
| import json | |
| server_address = '/tmp/example.sock' | |
| sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM) | |
| sock.connect(server_address) |
For this configuration you can use web server you like, i decided, because i work mostly with it to use nginx.
Generally, properly configured nginx can handle up to 400K to 500K requests per second (clustered), most what i saw is 50K to 80K (non-clustered) requests per second and 30% CPU load, course, this was 2 x Intel Xeon with HyperThreading enabled, but it can work without problem on slower machines.
You must understand that this config is used in testing environment and not in production so you will need to find a way to implement most of those features best possible for your servers.
| source 'https://rubygems.org' | |
| gem "graphql", github: "rmosolgo/graphql-ruby", branch: "subscriptions" | |
| gem "sinatra" | |
| gem "thin" |
| worker_processes 5; | |
| worker_rlimit_nofile 8192; | |
| events { | |
| worker_connections 4096; | |
| } | |
| http { | |
| client_max_body_size 20M; |
| ## Refer to http://caffe.berkeleyvision.org/installation.html | |
| # Contributions simplifying and improving our build system are welcome! | |
| # cuDNN acceleration switch (uncomment to build with cuDNN). | |
| USE_CUDNN := 1 | |
| # CPU-only switch (uncomment to build without GPU support). | |
| # CPU_ONLY := 1 | |
| # uncomment to disable IO dependencies and corresponding data layers |