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Supported File Formats

Depending on the installed libraries the Import Source currently supports multiple file formats. In case you’re missing any of the following formats in your Director frontend please re-read our Installation instructions.

CSV (Comma Separated Value)

CSV is a not so well defined data format, therefore the Import Source has to make some assumptions and ask for optional settings.

Basically, the rules to follow are:

  • a header line is required
  • each row has to have as many columns as the header line
  • defining a value enclosure is mandatory, but you do not have to use it in your CSV files. So while your import source might be asking for "hostname";"ip", it would also accept hostname;ip in your source files
  • a field delimiter is required, this is mostly comma (,) or semicolon (;). You could also opt for other separators to fit your very custom file format containing tabular data

Sample CSV file


More complex but perfectly valid CSV sample

"hostname","ip address","location"
"csv3","","Nott"", at Home"

JSON - JavaScript Object Notation

JSON is a pretty simple standarized format with good support among most scripting and programming languages. Nothing special to say here, as it is easy to validate.

Simple JSON example

This example shows an array of objects:

[{"host": "json1", "address": ""},{"host": "json2", "address": ""}]

This is the easiest machine-readable form of a JSON import file.

Pretty-formatted extended JSON example

Single-line JSON files are not very human-friendly, so you’ll often meet pretty- printed JSON. Such files also make also prefectly valid import candidates:

  "json1.example.com": {
    "host": "json1.example.com",
    "address": "",
    "location": "HQ",
    "groups": [ "Linux Servers" ]
  "json2.example.com": {
    "host": "json2.example.com",
    "address": "",
    "location": "HQ",
    "groups": [ "Windows Servers", "Lab" ]

Microsoft Excel

XSLX, the Microsoft Excel 2007+ format is supported since v1.1.0.

XML - Extensible Markup Language

When working with XML please try to ship simple files as shown in the following example. We’d love to add more features like better attribute support or XPath- based filters. In case you need such, please let us know and ship some exmple data, helping us to better understand your requirements!

Simple XML example

<?xml version="1.0" encoding="UTF-8" ?> 

YAML (Ain’t Markup Language)

YAML is all but simple and well defined, it allows you to write the same data in various ways. In case you opt for it you might have your reasons and should already be familiar with how to generate such files.

Simple YAML example

So, let’s start with a simple example:

- host: "yaml1.example.com"
  address: ""
  location: "HQ"
- host: "yaml2.example.com"
  address: ""
  location: "HQ"
- host: "yaml3.example.com"
  address: ""
  location: "HQ"

Advanced YAML example

People who think that NoSQL solves all there data problems tend to believe that YAML solve all their config problems. So, YAML is pretty hip and widely used among tools in hyped niches such as configuration management. I’ll pick Puppet as an example, but this might work in a similar way for many other tools.

Instead of a single YAML file I have to deal with a directory full of files in this case. Our Import Source documentation already shows how to configure such, here you can see part of such a file:

--- !ruby/object:Puppet::Node::Facts
  name: foreman.localdomain
    architecture: x86_64
    timezone: CEST
    kernel: Linux
    system_uptime: "{\x22seconds\x22=>5415, \x22hours\x22=>1, \x22days\x22=>0, \x22uptime\x22=>\x221:30 hours\x22}"
    domain: localdomain
    virtual: kvm
    is_virtual: "true"
    hardwaremodel: x86_64
    operatingsystem: CentOS
    facterversion: "2.4.6"
    filesystems: xfs
    fqdn: foreman.localdomain
    hardwareisa: x86_64
    hostname: foreman

If this looks foreign to you don’t worry, most similar constructs are handled in a smooth way by the underlying YAML parser.