cheeming

diff --git a/src/gridfs.c b/src/gridfs.c
index f51b397..66f8d88 100644
--- a/src/gridfs.c
+++ b/src/gridfs.c
@@ -43,7 +43,7 @@ int gridfs_init( mongo *client, const char *dbname, const char *prefix,
 
     int options;
     bson b;
-    bson_bool_t success;
+    bson_bool_t success = 1;

jeffyip

# Fork of MessageVerifier from Rails 3.2.3
# https://raw.github.com/rails/rails/f3e1b21ca91afbd97f33d1e51808dd320d82b4de/activesupport/lib/active_support/message_verifier.rb
# Author: Jeff Yip (jeffyip)
# This should work with Rails 3.0 - Rails 3.2

require 'active_support/base64'
require 'active_support/deprecation'
require 'active_support/core_ext/object/blank'

module ActiveSupport

ssimpson89

#!/bin/bash

### VARIABLES ### \
EMAIL=""
SERVER=$(hostname)
MYSQL_CHECK=$(mysql -e "SHOW VARIABLES LIKE '%version%';" || echo 1)
LAST_ERRNO=$(/usr/bin/mysql -e "SHOW SLAVE STATUS\G" | grep "Last_Errno" | awk '{ print $2 }')
SECONDS_BEHIND_MASTER=$(/usr/bin/mysql -e "SHOW SLAVE STATUS\G"| grep "Seconds_Behind_Master" | awk '{ print $2 }')
IO_IS_RUNNING=$(/usr/bin/mysql -e "SHOW SLAVE STATUS\G" | grep "Slave_IO_Running" | awk '{ print $2 }')
SQL_IS_RUNNING=$(/usr/bin/mysql -e "SHOW SLAVE STATUS\G" | grep "Slave_SQL_Running" | awk '{ print $2 }')

clemsos

#!/usr/bin/env python
# -*- coding: utf-8 -*-

'''

This script just show the basic workflow to compute TF-IDF similarity matrix with Gensim 


OUTPUT :

ngrilly

package auth

import (
	"net/http"
	"net/url"
	"strings"
	"time"

	"lib/crypto"
	"lib/utils"

shantanuo

#!/bin/sh
# copy the database source files to destination

dbname='palus'
source='/DATA/4GLV/tokudb/'

destip='192.168.150.137'
destuser='db'
destpass='db'
destport='3306'

rklaehn

package akkahttptest

import akka.actor.ActorSystem
import akka.http.Http
import akka.stream.FlowMaterializer
import akka.http.server._
import akka.http.marshalling.PredefinedToResponseMarshallers._
import akka.stream.scaladsl.{HeadSink, Source}

object Proxy extends App {

paulirish

Option 1: Command-line download extension as zip and extract

extension_id=jifpbeccnghkjeaalbbjmodiffmgedin   # change this ID
curl -L -o "$extension_id.zip" "https://clients2.google.com/service/update2/crx?response=redirect&os=mac&arch=x86-64&nacl_arch=x86-64&prod=chromecrx&prodchannel=stable&prodversion=44.0.2403.130&x=id%3D$extension_id%26uc" 
unzip -d "$extension_id-source" "$extension_id.zip"

Thx to crxviewer for the magic download URL.

ilyaigpetrov

Meteor Alternatives Per Feature

This table was created in 2015 so may be quite outdated today.

Feature	Meteor Solution	Alternative Solutions	Description
Live DB Sync	[livequery][lq] ([mongo-oplog]), [ddp]	RethinkDB, Redis, ShareDB, [npm:mongo-oplog], [firebase], etc.	Push DB updates to client/server.
Latency Compensation, Optimistic UI	[minimongo][mm]	[RethinkDB][lcr], [mWater/minimongo] (fork, not ws but http, browserify)	Imitate successful db query on client before it is done.
Isomorphic Code	[isobuild] & isopacks	browserify	Write one code for server/client/mobile.
Isomorphic Packaging	[isobuild], atmosphere		No more separate packages for server & client. Get bower + npm + mobile.

dannguyen

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