Right, your worst case is a css file with as many specs as tables, BUT in the 
process you’ve id’d (and/or classified) all your tables, only minimally changed 
your html files, while simultaneously opening up options for more efficient 
oversight and control going forward.

Assuming (from your other post) a fluency with FMP and SQL, you open up the 
option of taking advantage of integrating them into your workflow — An FMP 
table, perhaps, holding a list of your HTML tables, the column counts and 
widths, which in turn generates the css specs.  Just one of many options that 
open up.


> On Nov 27, 2019, at 05:42, Andrew Brown <[email protected]> wrote:
> 
> This all makes good sense, thanks Harvey, and indeed some patterns could 
> emerge, particularly for the simple tables — but I would end up with almost 
> as many css specifications as tables given that I can rarely use automatic 
> column width. For the moment I am making do the colgroup approach. — AB
> 
>> Consider a data-and-code solution as opposed to one that involves 
>> custom-editing each and every table.
>> In approx. the same time it takes you to mark up each table you could 
>> instead be logging each table (say giving each table an id (or probably 
>> better, a class), it’s column count, and preferred column sizing)
>> There are a number of ways to go about doing this. ( I prefer a JS-coded 
>> approach, but at very least you could create a central .css file that 
>> effectively lists all your table classes and their customized td widths. )
>> A number of interesting things come from this approach:
>> a) You get a centralized overview of all your tables.
>> b) When you want to make changes you don’t have to again edit all your 
>> tables, just the centralized file.
>> c) You typically discover patterns in your datasets and even your website 
>> you weren’t previously aware of, and you can start to think about how to 
>> leverage those discoveries in efficient, innovative ways.
>> d) You open up the possibility — if it makes a difference — of extracting 
>> the data out of all the html files into more data-friendly contexts 
>> (databases, JSON, etc)
> 
> 
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