Data Templates
Hugo supports loading data from YAML, JSON, XML, and TOML files located in the data
directory at the root of your Hugo project.
The Data Folder
The data
folder should store additional data for Hugo to use when generating your site.
Data files are not for generating standalone pages. They should supplement content files by:
- extending the content when the front matter fields grow out of control, or
- showing a larger dataset in a template (see the example below).
In both cases, it’s a good idea to outsource the data in their (own) files.
These files must be YAML, JSON, XML, or TOML files (using the .yml
, .yaml
, .json
, .xml
, or .toml
extension). The data will be accessible as a map
in the .Site.Data
variable.
To access the data using the site.Data.filename
notation, the filename must begin with an underscore or a Unicode letter, followed by zero or more underscores, Unicode letters, or Unicode digits. For example:
123.json
- Invalidx123.json
- Valid_123.json
- Valid
To access the data using the index
function, the filename is irrelevant. For example:
Data file | Template code |
---|---|
123.json | {{ index .Site.Data "123" }} |
x123.json | {{ index .Site.Data "x123" }} |
_123.json | {{ index .Site.Data "_123" }} |
x-123.json | {{ index .Site.Data "x-123" }} |
Data Files in Themes
Data Files can also be used in Hugo themes.
However, note that the theme data files are merged with the project directory taking precedence. That is, Given two files with the same name and relative path, the data in the file in the root project data
directory will override the data from the file in the themes/<THEME>/data
directory for keys that are duplicated).
Therefore, theme authors should be careful not to 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 the 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)
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)']
{
"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 \u0026 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|xml|json]
data file located directly in data/
:
Achievements:
- Can create a Key, Value list from Data File
- Learns Hugo
- Reads documentation
Name: User0123
Short Description: He is a **jolly good** fellow.
Achievements = ['Can create a Key, Value list from Data File', 'Learns Hugo', 'Reads documentation']
Name = 'User0123'
'Short Description' = 'He is a **jolly good** fellow.'
{
"Achievements": [
"Can create a Key, Value list from Data File",
"Learns Hugo",
"Reads documentation"
],
"Name": "User0123",
"Short Description": "He is a **jolly good** fellow."
}
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 Markdown rendering engine.
Get Remote Data
Use getJSON
or getCSV
to get remote data:
{{ $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" }}
Add HTTP headers
Both getJSON
and getCSV
takes an optional map as the last argument, e.g.:
{{ $data := getJSON "https://example.org/api" (dict "Authorization" "Bearer abcd") }}
If you need multiple values for the same header key, use a slice:
{{ $data := getJSON "https://example.org/api" (dict "X-List" (slice "a" "b" "c")) }}
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:
<table>
<thead>
<tr>
<th>Name</th>
<th>Position</th>
<th>Salary</th>
</tr>
</thead>
<tbody>
{{ $url := "https://example.com/finance/employee-salaries.csv" }}
{{ $sep := "," }}
{{ range $i, $r := getCSV $sep $url }}
<tr>
<td>{{ index $r 0 }}</td>
<td>{{ index $r 1 }}</td>
<td>{{ index $r 2 }}</td>
</tr>
{{ end }}
</tbody>
</table>
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 Get Remote Data.
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 data takes a while, Hugo stops processing your Markdown files until the data download has been completed.
Examples of Data-driven Content
- Photo gallery JSON powered: https://github.com/pcdummy/hugo-lightslider-example
- GitHub Starred Repositories in a post using data-driven content in a custom short code.