My first experiment using the NLTK library of Python
Inspired by this tutorial I tried to continue investigating Elasticsearch since I would like to use a fast indexing tool for the data I am gathering and the applications I am developing.
As a training for myself to get more familiar with image classification and OpenCV I followed the tutorial on http://www.pyimagesearch.com/2014/08/04/opencv-python-color-detection/. I modified it slightly to fit my environment.
In my previous post on testing in Python I explained how to test in a Jupyter Notebook. Now a few weeks later I need to get familiar with mocking in Python. Since this is a new concept for me I made a small notebook testing different functionalities of the mocking library.
Unittesting in a Jupyter notebook
To add some custom style to your dashboard, you can create a cascade stylesheet in your app folder and overrule the standard dashboard lay-out.
In this short tutorial I will create a Splunk app to monitor the webserver. We will create the bare-bone app and we add a few panels to the dashboard.
Since I have been using Linux for a while, switching back to the Windows CLI has some challenges. Luckily you can add aliases to the command prompt with the following procedure.
Installing the diff/merge tool KDiff3 is easy using the package manager Homebrew extension Cask. The extension makes is possible to install (GUI) applications on the Mac without the dragging and dropping of the DMG-files.
jitsejan@MBP $ /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
jitsejan@MBP $ brew tap caskroom/cask
jitsejan@MBP $ brew cask install kdiff3