Why would you want to run a web site from a spreadsheet? Because your customer only understands spreadsheets.
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Spreadsheet-backed Website


This is a response to the frustration I had with a 'resource library' (list of links) we were implementing for a quasi-governmental web site using a content-management system (Drupal, as it happens). Our customer was actually the subcontractor of the subcontractor of the quango charged with creating the site. No-one in this hierarchy was capable of using the CMS to edit the links; instead proposed changes floated up and down the layers of management in the form of a spreadsheet with columns for title, keywords, and so on.

My job, as a programmer with over thirty years experience, was to copy the data from the spreadsheet in to the web forms of the CMS. And to repeat the process when they realized one of the links was wrong and sent us an updated spreadsheet. And to repeat the process when deploying to the live web site once the staging site had been signed off.

At one point I had six spreadsheets. Three or four of them of them were named Resource Library_21Nov2009_FINAL_rev2.xls, none of which was the 21 November 2009 release, and none of which was in any sense final.

Doing this by hand would have been tedious and error-prone. I ended up concocting a Python program that read the links from the spreadsheet, corrected the obvious typos in the URLs, and then called a web service I added to the site to allow it to inject appropriate document nodes. Once I had this working I was able to update the staging site, get them to sign off the changes, and then make identical additions to the live site.

One of the biggest problems with this approach was the complexity of the CMS. All the features designed to allow the editors of the site to collaborate via web forms were useless complications that got in the way of my automated program. Why not, therefore, cut out the middleman, and have a web site that runs directly from the spreadsheet?


The present version is a proof of concept, using Django as its web framework.

This is in no way a finely finished piece of work; I have not spent much more than a working day's worth of work on it. If I were to seriously use this for a site I would add a bit more finesse. I may work on it enough to get it in the form of a re-usable Django app, just for the sake of the exercise.

How it Works

A 'resource library' is a collection of links to resources on web sites (either the same as this site or external sites). A library is defined by a directory containing, at minimum, a spreadsheet with data about the links in it. Other, optional, files may add more metadata to flesh out the definition.

Libraries are named after the directory. Libraries all live in a 'root directory'. For the sample app, the root is resource-libraries and the Fan films library is in resource-libraries/fanfilms.

The standard Drupal URLconf in spreadlinks/urls.py has these lines:

urlpatterns = patterns('spreadsite.spreadlinks.views',
    (r'^$', 'library_list', {'root_dir': settings.SPREADLINKS_DIR}, 'library_list'),
    (r'^(?P<library_name>[^/]*)/$', 'library_detail', {'root_dir': settings.SPREADLINKS_DIR}, 'library_detail'),
    (r'^(?P<library_name>[^/]*)/page(?P<page>[0-9]+)$', 'library_detail', {'root_dir': settings.SPREADLINKS_DIR}, 'library_detail'),
    (r'^(?P<library_name>[^/]*)/tags/(?P<urlencoded_keywords>[a-z_0-9+:-]+)$', 'library_detail', {'root_dir': settings.SPREADLINKS_DIR}, 'library_detail'),
    (r'^(?P<library_name>[^/]*)/tags/(?P<urlencoded_keywords>[a-z_0-9+:-]+)/page(?P<page>[0-9]+)$', 'library_detail', {'root_dir': settings.SPREADLINKS_DIR}, 'library_detail'),

Each view takes an argument that is the root directory; in this case it is in turn acquired from the web site settings. The library name will match one of its subdirectories. I recommend using short names consisting only of lowercase letters and numbers; it keeps the URLs tidy.

Data Format

At present the spreadsheet must be in comma-separated values form; this is just because I have not bothered adding support for one of the Excel-parsing libraries available for Python. The first row MUST be column headings. Each of the subsequent rows specifies an entry in the library.

The meaning of the columns is inferred from the column heading. Column headings are normalized to lower case and spaces replaced with underscores before interpreting them. The following columns are significant:

  • title: The title of the link. Should be one line long and will be unique.
  • description: A paragraph or two describing the link. Markdown format.
  • url: The location of the item.
  • image-url: A picture to illustrate the item.
  • href or url: The address of the resource being linked to.
  • keywords or main_keywords: Keywords in the Main facet (see below)
  • FACET_keywords: Keywords in an additional facet (where FACET is replaced with the name of that facet).

At present other columns are ignored. (Probably they should be displayed as part of the link description or something.)

Keywords are used to build a browseable drill-down navigation thingummy. The navigator automatically hides keywords that would lead to no matches.

A facet is a collection of keywords that describe the resource in the same way. You might use a secondary facet to describe the resource type, or the intended audience, say. The navigator allows the user to select keywords from separate facets independently.

The value of the keywords cells may contain multiple keywords. By default, keywords are required to go one per line within the cell; this allows for keywords to be normal phrases with spaces and punctuation.


Additional information about the library may be specified with a separate file METADATA.txt. This contains one or more headings following the RFC-2822 format of heading:value, followed by a blank line and then the description of the library. The description uses Markdown format.

The following headers are understood:

  • Title: A title for the library as a whole.
  • Keyword-Separator: A character to use instead of newlines to separate keywords in the data file.

If there is no METADATA.txt, or no title is specified, then it uses library name (the same as the directory name).