hugo/docs/content/en/templates/data-templates.md
2019-02-01 09:01:04 +01:00

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Data Templates In addition to Hugo's built-in variables, you can specify your own custom data in templates or shortcodes that pull from both local and dynamic sources. 2017-02-01 2017-02-01 2017-03-12
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Hugo supports loading data from YAML, JSON, and TOML files located in the data directory in the root of your Hugo project.

{{< youtube FyPgSuwIMWQ >}}

The Data Folder

The data folder is where you can store additional data for Hugo to use when generating your site. Data files aren't used to generate standalone pages; rather, they're meant to be supplemental to content files. This feature can extend the content in case your front matter fields grow out of control. Or perhaps you want to show a larger dataset in a template (see example below). In both cases, it's a good idea to outsource the data in their own files.

These files must be YAML, JSON, or TOML files (using the .yml, .yaml, .json, or .toml extension). The data will be accessible as a map in the .Site.Data variable.

Data Files in Themes

Data Files can also be used in Hugo themes but note that theme data files follow the same logic as other template files in the Hugo lookup order (i.e., given two files with the same name and relative path, the file in the root project data directory will override the file in the themes/<THEME>/data directory).

Therefore, theme authors should take care to not include data files that could be easily overwritten by a user who decides to customize a theme. For theme-specific data items that shouldn't be overridden, it can be wise to prefix the folder structure with a namespace; e.g. mytheme/data/<THEME>/somekey/.... To check if any such duplicate exists, run hugo with the -v flag.

The keys in the map created with data templates from data files will be a dot-chained set of path, filename, and key in file (if applicable).

This is best explained with an example:

Example: Jaco Pastorius' Solo Discography

Jaco Pastorius was a great bass player, but his solo discography is short enough to use as an example. John Patitucci is another bass giant.

The example below is a bit contrived, but it illustrates the flexibility of data Files. This example uses TOML as its file format with the two following data files:

  • data/jazz/bass/jacopastorius.toml
  • data/jazz/bass/johnpatitucci.toml

jacopastorius.toml contains the content below. johnpatitucci.toml contains a similar list:

discography = [
"1974  Modern American Music … Period! The Criteria Sessions",
"1974  Jaco",
"1976 - Jaco Pastorius",
"1981 - Word of Mouth",
"1981 - The Birthday Concert (released in 1995)",
"1982 - Twins I & II (released in 1999)",
"1983 - Invitation",
"1986 - Broadway Blues (released in 1998)",
"1986 - Honestly Solo Live (released in 1990)",
"1986 - Live In Italy (released in 1991)",
"1986 - Heavy'n Jazz (released in 1992)",
"1991 - Live In New York City, Volumes 1-7.",
"1999 - Rare Collection (compilation)",
"2003 - Punk Jazz: The Jaco Pastorius Anthology (compilation)",
"2007 - The Essential Jaco Pastorius (compilation)"
]

The list of bass players can be accessed via .Site.Data.jazz.bass, a single bass player by adding the filename without the suffix, e.g. .Site.Data.jazz.bass.jacopastorius.

You can now render the list of recordings for all the bass players in a template:

{{ range $.Site.Data.jazz.bass }}
   {{ partial "artist.html" . }}
{{ end }}

And then in the partials/artist.html:

<ul>
{{ range .discography }}
  <li>{{ . }}</li>
{{ end }}
</ul>

Discover a new favorite bass player? Just add another .toml file in the same directory.

Example: Accessing Named Values in a Data File

Assume you have the following data structure in your User0123.[yml|toml|json] data file located directly in data/:

{{< code-toggle file="User0123" >}} Name: User0123 "Short Description": "He is a jolly good fellow." Achievements:

  • "Can create a Key, Value list from Data File"
  • "Learns Hugo"
  • "Reads documentation" {{</ code-toggle >}}

You can use the following code to render the Short Description in your layout::

<div>Short Description of {{.Site.Data.User0123.Name}}: <p>{{ index .Site.Data.User0123 "Short Description" | markdownify }}</p></div>

Note the use of the markdownify template function. This will send the description through the Blackfriday Markdown rendering engine.

Data-Driven Content

In addition to the data files feature, Hugo also has a "data-driven content" feature, which lets you load any JSON or CSV file from nearly any resource.

Data-driven content currently consists of two functions, getJSON and getCSV, which are available in all template files.

Implementation details

Call the Functions with a URL

In your template, call the functions like this:

{{ $dataJ := getJSON "url" }}
{{ $dataC := getCSV "separator" "url" }}

If you use a prefix or postfix for the URL, the functions accept variadic arguments:

{{ $dataJ := getJSON "url prefix" "arg1" "arg2" "arg n" }}
{{ $dataC := getCSV  "separator" "url prefix" "arg1" "arg2" "arg n" }}

The separator for getCSV must be put in the first position and can only be one character long.

All passed arguments will be joined to the final URL:

{{ $urlPre := "https://api.github.com" }}
{{ $gistJ := getJSON $urlPre "/users/GITHUB_USERNAME/gists" }}

This will resolve internally to the following:

{{ $gistJ := getJSON "https://api.github.com/users/GITHUB_USERNAME/gists" }}

Finally, you can range over an array. This example will output the first 5 gists for a GitHub user:

<ul>
  {{ $urlPre := "https://api.github.com" }}
  {{ $gistJ := getJSON $urlPre "/users/GITHUB_USERNAME/gists" }}
  {{ range first 5 $gistJ }}
    {{ if .public }}
      <li><a href="{{ .html_url }}" target="_blank">{{ .description }}</a></li>
    {{ end }}
  {{ end }}
</ul>

Example for CSV files

For getCSV, the one-character-long separator must be placed in the first position followed by the URL. The following is an example of creating an HTML table in a partial template from a published CSV:

{{< code file="layouts/partials/get-csv.html" >}}

{{ $url := "https://example.com/finance/employee-salaries.csv" }} {{ $sep := "," }} {{ range $i, $r := getCSV $sep $url }} {{ end }}
Name Position Salary
{{ index $r 0 }} {{ index $r 1 }} {{ index $r 2 }}
{{< /code >}}

The expression {{index $r number}} must be used to output the nth-column from the current row.

Cache URLs

Each downloaded URL will be cached in the default folder $TMPDIR/hugo_cache/. The variable $TMPDIR will be resolved to your system-dependent temporary directory.

With the command-line flag --cacheDir, you can specify any folder on your system as a caching directory.

You can also set cacheDir in the main configuration file.

If you don't like caching at all, you can fully disable caching with the command line flag --ignoreCache.

Authentication When Using REST URLs

Currently, you can only use those authentication methods that can be put into an URL. OAuth and other authentication methods are not implemented.

Load Local files

To load local files with getJSON and getCSV, the source files must reside within Hugo's working directory. The file extension does not matter, but the content does.

It applies the same output logic as above in Calling the Functions with a URL.

{{% note %}} The local CSV files to be loaded using getCSV must be located outside of the data directory. {{% /note %}}

LiveReload with Data Files

There is no chance to trigger a LiveReload when the content of a URL changes. However, when a local file changes (i.e., data/* and themes/<THEME>/data/*), a LiveReload will be triggered. Symlinks are not supported. Note too that because downloading of data takes a while, Hugo stops processing your Markdown files until the data download has completed.

{{% warning "URL Data and LiveReload" %}} If you change any local file and the LiveReload is triggered, Hugo will read the data-driven (URL) content from the cache. If you have disabled the cache (i.e., by running the server with hugo server --ignoreCache), Hugo will re-download the content every time LiveReload triggers. This can create huge traffic. You may reach API limits quickly. {{% /warning %}}

Examples of Data-driven Content

Specs for Data Formats