Foo jimmytuc

psql: FATAL: Peer authentication failed for user “postgres” (or any user)

The connection failed because by default psql connects over UNIX sockets using peer authentication, that requires the current UNIX user to have the same user name as psql. So you will have to create the UNIX user postgres and then login as postgres or use sudo -u postgres psql database-name for accessing the database (and psql should not ask for a password).

If you cannot or do not want to create the UNIX user, like if you just want to connect to your database for ad hoc queries, forcing a socket connection using psql --host=localhost --dbname=database-name --username=postgres (as pointed out by @meyerson answer) will solve your immediate problem.

But if you intend to force password authentication over Unix sockets instead of the peer method, try changing the following pg_hba.conf* line:

from

Collection of sample Elasticsearch queries

Use the Python client elasticsearch.

Connect to cluster (the client)

from elasticsearch import Elasticsearch

es_client = Elasticsearch() # local

Concurrency in JavaScript

Javascript is a programming language with a peculiar twist. Its event driven model means that nothing blocks and everything runs concurrently. This is not to be confused with the same type of concurrency as running in parallel on multiple cores. Javascript is single threaded so each program runs on a single core yet every line of code executes without waiting for anything to return. This sounds weird but it's true. If you want to have any type of sequential ordering you can use events, callbacks, or as of late promises.

Docker - How to cleanup (unused) resources

Once in a while, you may need to cleanup resources (containers, volumes, images, networks) ...

delete volumes

// see: https://github.com/chadoe/docker-cleanup-volumes

$ docker volume rm $(docker volume ls -qf dangling=true)

$ docker volume ls -qf dangling=true | xargs -r docker volume rm

Using Python 3 + Google Cloud Vision API's OCR to extract text from photos and scanned documents

Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.

The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.

On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:

####### 1. A low-resolution photo of road signs

	# import python core modules
	import datetime
	import logging

	# import external modules
	import pandas as pd
	import requests

	# import luigi modules
	import luigi

	<?php

	/**


	This Scheduler will run once every minute unlike the Heroku scheduler which only runs every 10 mintues.

	To use this scheduler with Laravel 5.4+ add this file to /app/Console/Commands/RunScheduler.php
	Register this file in app/Console/Kernel.php

	// Copyright Stephen Feather and other contributors.
	//
	// Permission is hereby granted, free of charge, to any person obtaining a
	// copy of this software and associated documentation files (the
	// "Software"), to deal in the Software without restriction, including
	// without limitation the rights to use, copy, modify, merge, publish,
	// distribute, sublicense, and/or sell copies of the Software, and to permit
	// persons to whom the Software is furnished to do so, subject to the
	// following conditions:
	//

	for (var i = 0; i < 1024 * 1024; i++) {
	process.nextTick(function () { Math.sqrt(i) } )
	}