| RewriteEngine On | |
| RewriteMap fedora-map prg:/wgbh/http/openvault/map.fedora.py | |
| RewriteCond %{REQUEST_URI} Proxy #map just URIs with Proxy in them.. | |
| RewriteRule ^/fedora/get/([a-zA-Z0-9/:\-\.]+)$ ${fedora-map:$1} [QSA] # send along the query string.. hopefully the regex is about right.. ought to check it someday. |
| # adapted from http://notes.jimlindley.com/2008/3/25/git-svn-that-works-for-me | |
| # initial setup | |
| git svn clone <svn_repo> | |
| # begin the workflow | |
| git svn fetch -r HEAD --ignore-paths="Package.zip" # aliased to 'git up', my Package.zip is very large. | |
| git svn rebase -l # we just updated, no need to go back to the svn repo | |
| # 99% of daily workflow |
| Vagrant::Config.run do |config| | |
| # Every Vagrant virtual environment requires a box to build off of. | |
| config.vm.box = "base" | |
| # Assing IP to the VM | |
| config.vm.network :hostonly, "10.0.33.10" | |
| # Share directory between the host and the VM | |
| config.vm.share_folder "git","/opt/git","/home/anarey/git/djandoapps" |
| <?xml version="1.0"?> | |
| <xsl:stylesheet version="2.0" | |
| xmlns:xsl="http://www.w3.org/1999/XSL/Transform" | |
| xmlns:wsdl="http://schemas.xmlsoap.org/wsdl/" | |
| xmlns:xsd="http://www.w3.org/2001/XMLSchema"> | |
| <xsl:output version="1.0" encoding="utf-8" indent="yes" name="xml" /> | |
| <xsl:template match="/"> | |
| <xsl:apply-templates /> |
A Dashing widget to display the number of issues returned by a Jira Query Language (JQL) search. The number of issues will be displayed using the Numbers widget. This widget is a generalized version of the Atlassian Jira: Number of issues in a Jira filter query widget, which shows the number of issues for saved Jira filter.
The following dependencies are required. Please add them to your dashing gemfile.
gem 'jira-ruby', :require => 'jira'
Apache Zeppelin has a helpful feature in its Spark Interpreter called Object Exchange. This allows you to pass objects, including DataFrames, between Scala and Python paragraphs of the same notebook. You can do your data prep/feature engineering with the Scala Spark Interpreter, and then pass off a DataFrame containing the features to PySpark for use with libraries like NumPy and scikit-learn. Also with Zeppelin's support for matplotlib you have a pretty good setup for poking around and testing out machine learning on your data.
| #!/bin/bash | |
| # Dashing service | |
| # Add this file to /etc/init.d/ | |
| # $ sudo cp dashboard /etc/init.d/ | |
| # Update variables DASHING_DIR, GEM_HOME, & PATH to suit your installation | |
| # $ sudo nano /etc/init.d/dashboard | |
| # Make executable | |
| # $ sudo chmod 755 /etc/init.d/dashboard | |
| # Update rc.d | |
| # $ sudo update-rc.d dashboard defaults |
The MIT License (MIT)
Copyright (c) 2014 David Underwood
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:
| library(tidyverse) | |
| library(janitor) | |
| library(lubridate) | |
| library(zoo) | |
| library(ckanr) | |
| # generates age/sex population lookup for Scotland based on NRS mid-year | |
| # population estimates/projections, interpolated linearly to day level | |
| # (July 2nd used as mid-year reference date). | |
| # |
