All of the scripts and code snippets are in freely downloadable public repositories on GitHub. To read further, and to get the GitHub repository links, click these tabs.
If the final output of your online help files is HTML, you can include these code snippets in your HTML transforms. The files use the jQuery and the jQuery UI libraries, and are implemented through the
class attribute of HTML elements. Therefore, the code will work on any HTML or DITA element that takes a
The following effects are ready for your use:
These are scripts to make the everyday life of a technical writer a wee bit easier.
To run these scripts, you need Python 2.7.5. Download and install Python from www.python.org. You need Python only to run the script; you don't need to know Python to run the scripts.
The script scans all DITA files in a directory, recursively, for occurrences of an entire list of words and phrases that you specify.
You want to scan all files in a directory for several words, all at once. Maybe these words are a list of do-not-use words that your style guide specifies, but you don't have an automated word checker to look for such occurences. Maybe you want to know if you've used certain DITA tags in your files but do not want to run a system search for each tag, one by one. This script searches for multiple words at one go, and also phrases and DITA tags. You specify a list of words and phrases, and tell the script which directory it should scan. The script runs the checks and gives you a report that you can read and act upon.
The script scans all files in a directory, recursively, and reports the files that are not called by any DITA file in the directory.
You have several image files, topic files, and other files in the directory but hesitate to delete them because you are not sure if any of these files are referenced by the DITA files in that directory. You tell the script which directory it should scan. The script runs the checks and gives you a report that you can read and act upon to clean up your workspace.
Sometimes, a diagram is the best way to convey information. Complicated task flows, for example, or large data sets often make more sense if presented visually.
Sometimes, the inbuilt functions of Microsoft Excel and OpenOfficeCalc are sufficient for drawing charts ( ). At other times, data needs to be processed first before it can be fed into a spreadsheet ( ). At still other times, data needs be run through a script ( ). At all of these times, the data becomes more appealing and understandable when presented as an image. See Turn data into stories.
The data-processing scripts (and the data source files) are in this GitHub repository: Visualisations repo.
Playing with words and images