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Non-printing characters or formatting marks are characters for content designing in word processors, which are not displayed at printing. It is also possible to customize their display on the monitor. The most common non-printable characters in word processors are pilcrow, space, non-breaking space, tab character etc. [1] [2]
An "image" in the form of a table is much more convenient to edit than an uploaded image. If all the cells in a row are empty the cells still show up. If the header cell is also empty for that row all the cells show up, but they are narrow. That can be fixed with a simple <br> in one of the cells. That is what is done here:
The template puts an image in the element cell. Default size is 210px wide. Depending on the picture size the text has two layouts: ... 2 = Element name (and default ...
Unit-less numerical value for font-size (do not append 'px') id-fc Text color for the id label. CSS color string (hex or name) id-p Space/padding Between the id content and the userbox border. This cell padding uses a CSS length value. Unlike the other unit-less values, this must have a CSS length unit such as px or pt. (E.g. id-p = 8px). id-lh
Preserve the original image size, and put a box around the image. Show any caption below the image. Float the image on the right unless overridden with the location attribute. Note: Any size options specified will be ignored and flagged as a 'bogus file option' by the Linter. frameless Automatically scale the image up or down.
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Do not explicitly define the size of an image in pixels unless there is a good reason to do so. Preferably the size should be specified as a value relative to the user's preferred thumbnail width, using the |upright=scaling factor parameter rather than pixel values, whenever an image is to be displayed at something other than the default width.
Python Imaging Library is a free and open-source additional library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is available for Windows, Mac OS X and Linux. The latest version of PIL is 1.1.7, was released in September 2009 and supports Python 1.5.2–2.7. [3]