YAML is a must-have skill for IT professionals, since it is probably becoming the the most commonly used document format for manifest and configuration files - think for example to Kubernetes, Ansible and a lot of other modern Dev-Ops oriented or CI/CD tools such as drone.

Being skilled on YAML does not only mean being able to write YAML documents, but also efficiently query and manipulate YAML files.

This post provides everything it is very likely you must know to exploit YAML in your daily work, explaining its syntax and showing things in action by using yq - a tool we can consider "the jq for YAML", and using Python with PyYAML.

By the way, this post is part of a trilogy of posts dedicated to markup and serialization formats, so be sure not to miss

What is YAML

It stands for Yet Another Markup Language and it is a Unicode based human-readable data-serialization language. Its very compact and readable notation, along with DRY features such as anchors and aliases make it the ideal format to write configuration files and manifests. For this reason this format has become the default format used by Kubernetes, Ansible and a lot of other popular Dev-Ops tools.

The nesting of its data structures relies on indentation (same way as Python does): the use of indentation enables YAML to be read and written in streams - chunks of consecutive YAML lines that are well-formed YAML documents themselves. This saves parsers from having to process a whole YAML document when dealing to extract a specific part of it, avoiding loading everything into memory. This means that you can also parse very large YAML files without actually having to fully load them in memory.

Besides the regular format, YAML has also the flow-style notation: a compact notation that encloses sequences (list of items) into square brackets [...] and makes use of curly braces {...} for maps (dictionaries). This notation  quite recalls JSON by the way.

Since YAML nesting relies on correctly indenting things, it is quite easy to make mistakes: a handy tool that can help you to validate YAML documents and find syntax errors is yamllint.

We can install it as follows:

sudo dnf -y install yamllint

we can use this tool to validate YAML file as follows:

yamllint myfile.yml

Ansible heavily relies on YAML files: we can get some YAML files to play with by installing the rhel-system-roles RPM package:

sudo dnf install -y rhel-system-roles

This package provides stock Ansible roles you can use to manage Red Hat based systems, installing them beneath the "/usr/share/ansible/roles" directory.

Using VIM with YAML

If you are ancient like me, you certainly cannot work without the old fashioned vim, ... so here is a list of plugins you cannot miss to work with YAML:

let's install them using vim-plug plugin manager: let's download it as follows:

curl -fLo ~/.vim/autoload/plug.vim --create-dirs https://raw.githubusercontent.com/junegunn/vim-plug/master/plug.vim

now let's modify our "~/.vimrc" file adding the following snippet:

call plug#begin()
Plug 'https://github.com/stephpy/vim-yaml'
Plug 'https://github.com/Yggdroot/indentLine'
call plug#end()

and  launch vim as usual:

vim

while in command mode, enter the command to install the plugins we listed into "~/.vimrc":

:PlugInstall

if everything went well we can verify the status of the plugins as follows:

:PlugStatus

we can now configure vim to ease our life with YAML file: configure our "~/.vimrc":

au! BufNewFile,BufReadPost *.{yaml,yml} set filetype=yaml
autocmd FileType yaml setlocal ts=2 sts=2 sw=2 expandtab 

we simply define the "yaml" file type and bind ".yaml" and ".yml" files to it. Then we configure some help with indentation - YAML does not allow tabs, and the suggested indents are multiples of two spaces.

Once installed  indentLine plugin, we can modify the indentation character used by Indentation guides displaying a thinner line: add the following line to our "~/.vimrc":

let g:indentLine_char = '|'
let g:indentLine_color_term = 239 

This is the final outcome when editing a YAML file:

it's much more readable and usable, isn't it?

If you need to quickly fold the whole YAML document you are editing with vim, switch to command mode and enter ":set foldmethod=indent": once folded you select and can expand the nodes you are interested in by using the arrows keys.

YQ - an overview

It is a really handy command line tool to manage YAML documents in shell scripts - you can consider it "the jq for YAML".

There are two different projects called yq:

The last one seems to be the more broadly used, probably because the first one is not 100% jq compatible. In this post we see how to use the last one.

It is not a native tool to manage YAML objects: it is much more a format converter from YAML to JSON that, right after converting the object, executes jq. This means that it requires installing jq.

Let's begin by installing yq requirements:

sudo dnf -y install jq python3-pip

we can now install yq using pip as follows:

sudo pip3 install yq 
sudo bash -c "cat << \EOF > /etc/profile.d/aliases.sh
alias yq='/usr/local/bin/yq'
EOF"

Let's test it to see what the step "Enable phc2sys" of the timesync Ansible role does: the role is installed into "/usr/share/ansible/roles/rhel-system-roles.timesync" directory, and tasks are declared into the "tasks/main.yml" file.

We can simply cat the file and pipe it to yq, passing the same syntax we would use with jq as argument:

cat /usr/share/ansible/roles/rhel-system-roles.timesync/tasks/main.yml | yq -y '. | to_entries[] |select(.value.name=="Enable phc2sys") | .value'

the output streams are:

name: Enable phc2sys
service:
    name: phc2sys
    state: started
    enabled: true
when:
    - timesync_mode == 2
    - timesync_mode2_hwts

as you can see, the nice thing is that you are not required to learn anything more than you already know to use jq, … besides remembering to supply the -y command option when you want to get the output converted from JSON back to YAML format.

I recommend you to read JSON and jq in a nutshell to get more familiar with jq. : I won’t provide examples of filtering to avoid redundancy, since by the way they are well explained in JSON and jq in a nutshell post.

YAML Serialization

YAML serialization is quite huge: here we focus only on the things that you are most likely to hit in the daily work. YAML is used to store key-value pairs where the key is called node.

Be wary that YAML keys are case-sensitive.

There are only three kind of nodes:

  • scalar, that is an opaque datum that can be presented as a series of zero or more Unicode characters
  • sequence, that is an ordered series of zero or more nodes; in particular, a sequence may contain the same node more than once. It could even contain itself
  • mapping, that is an unordered set of key/value node pairs, with the restriction that each of the keys is unique. YAML places no further restrictions on the nodes. In particular, keys may be arbitrary nodes, the same node may be used as the value of several key/value pairs and a mapping could even contain itself as a key or a value

TAGS

A Tag is a simple identifier used to represent type information of native data structures. There do exist:

  • local tags, that are specific to a single application, and start with the "!" character - for example "!TomcatInstance"
  • global tags, that are unique across all applications - they are actually URI that make use of the "tag:" scheme and use URI character escaping - for example "!<tag:yaml.org,2002:str>"

Note that when dealing with global tags it is most used the "!!" shorthand - for example:

  • !!str is the shorthand of !<tag:yaml.org,2002:str>
  • !!map is the shorthand of !<tag:yaml.org,2002:seq>
  • !!seq is the shorthand of !<tag:yaml.org,2002:map> 

Please note that YAML provides also a "TAG" directive to make tag notation less verbose.

YAML tags are used to associate meta information with each node. In particular, each tag must specify the expected node kind (scalar, sequence or mapping).

We'll see YAML tags in action later on with an example using PyYAML.

Versions And Schemas

The YAML specifications are available on the official website - the current release at the time of writing this post is 1.2.0 - by the way, this release was published with the claimed purpose of bringing YAML "into compliance with JSON as an official subset".

Conversely from JSON, which has been specifically designed to promote its usage for data exchange between different systems, YAML is instead more aimed at writing Manifests, so it is often used with a specific processor.

Since a processor often implements a specific version of YAML, you must pay very careful attention to be compliant to the version implemented by your processor, or try to write the YAML code in the most portable manner possible.

Version 1.2, besides adding support to UTF-32, introduces the concept of "Schema": a schema basically is the connection between Tags in the YAML document and Classes / data types in the programming language.

It provides three different schemas:

For example, these are the tags defined in YAML 1.2 Specifications JSON Schema:

  • !!str
  • !!map
  • !!seq
  • !!null A null value. Match: null
  • !!bool Boolean. Match: true | false
  • !!int Integer. Match: 0 | -? [1-9] [0-9]*
  • !!float Float. Match: -? ( 0 | [1-9] [0-9]* ) ( \. [0-9]* )? ( [eE] [-+]? [0-9]+ )?

If you do not have special needs, such as the extra types provided by the Core schema, you can simply follow the YAML 1.2 JSON Schema: this way your YAML code should work for most YAML 1.1/1.2 processors. Be wary that 1.1 specifications support only UTF-8 and UTF-16 and anyway the recommended output encoding is UTF-8.

Be wary that despite the 1.1 specifications having been superseded by the 1.2, it is still the one implemented by many broadly used serialization libraries such as PyYAML.

In the following paragraphs I'm describing the serialization 1.2 JSON Schema compliant.

Document separator

You can have multiple documents within a single file by separating them using three hyphens ("---"). Please note that three dots ("...") mark the end of a document without starting a new one.

Comments

Comment lines begin with the Octothorpe (also called "hash", "sharp", or "number sign" - "#"), and anyway anything after the "#" character is a comment:

# This is a YAML comment
foo: bar # This is also a YAML comment

null value

The "null" word identifies the null value

my_undefined: null
Be wary that YAML specifications also consider both an empty value and the "~" character as null.

Numbers and booleans

Numbers and booleans values must not be enclosed by quotes.

Let's see some examples:

toggle: true
fixed: 42.88
exponential: 0.42e+3
sexagesimal: 190:20:30.15
negative infinity: -.inf
not a number: .nan

booleans values can be either true or false.

Strings

Strings do not normally require quotation marks, although you are free to enclose them in either double or single quotes.

msg: this is a string
msg: 'this is another string'
msg: "this is yet another a string"
msg: "42"

Note however that sometimes quoting the string is mandatory. For example:

  • if the string contains a colon (:)  followed by a space character
  • if the string begins with an opening curly brace "{" or square bracket "[", since they are used in the flow-style notation to  enumerate list items or maps
  • if the string is a literal such as true or false: the risk is to get the string mapped to a different type, such as booleans.

Just to provide a real life example, Ansible uses curly braces to enable JINJA2 template engine, so the right syntax of a string that contains only an Ansible variable is:

msg: "{{ variable }}"

Multiline strings

There are two ways to handle multi-line strings:

if you want to preserve newlines, then use the vertical bar (|)  - for example:

preserve_newlines: |
  Carcano SA
  piazza indipendenza, 123
  Lugano, 6900
  CH

if instead you want to fold newlines (have newlines converted into spaces), use the greater-than (>) character - for example:

fold_newlines: >
  Marco Antonio
  Carcano

Get elements using yq

Get elements from a YAML document is pretty simple - consider the following example:

status: "WARN"
message: "Free disk space too low"
threshold: "10%"

let's pretty-print it:

RESULT='status: "WARN"\nmessage: "Free disk space too low"\nthreshold: "10%"'
echo -e $RESULT | yq

the output is:

{
    "status": "WARN",
    "message": "Free disk space too low",
    "threshold": "10%"
}

Let's get only the "threshold" value:

echo -e $RESULT | yq '.threshold'

the output is:

"10%"
Once more, I recommend you to read JSON and jq in a nutshell to get more familiar with jq.

Lists

The syntax that must be used to declare a list (a sequence in YAML terms) is depicted by the following snippet:

servers:
    - servera
    - serverb
    - serverc

Please note that lists also have an inline block format (flow-style, sometimes called compact) enclosed by square braces as depicted by the following snippet:

servers: [ 'servera', 'serverb', 'serverc' ]

Dictionaries

The syntax that must be used to declare a dictionary (a map in YAML term) is depicted by the following snippet:

vars:
    package_name: apache
    service_name: httpd
    port: 80

Please note that dictionaries also have an inline block format (flow-style, sometimes called compact) enclosed by curly braces as depicted by the following snippet:

vars: { package_name: apache, service_name: httpd, port: 80 }

List of Dictionaries

We can of course have list of dictionaries: the syntax is as depicted by the following snippet:

packages:
    - name: apache
      service: httpd
      port: 80
    - name: tomcat
      service: tomcat
      port: 8080

Don't Repeat Yourself (DRY)

The Don't Repeat Yourself - aka DRY - approach requires avoiding to use duplicates: repeating the same thing makes maintaining things hard and error prone indeed.

YAML provides a few handy features to achieve this: anchors, aliases and the Merge Key Language-Independent type.

Anchors and Aliases

They are a feature of YAML that lets you accomplish the task of avoiding repetitions in the document.

  • The '&' character marks an anchor, that roughly put is a marker of a chunk of configuration
  • The '*' character marks an aliases, that is a placeholder that is expanded using the contents of the anchor it refers to

Let's see both of them in action with this example snippet of an Ansible playbook - create the "anchors.yml" file with the following contents:

---
- name: Update Tomcat Application Servers
  hosts: apps-ci-up3a 
  vars:
    tomcat:
      options: &tomcat_opts
        opts: '-Xms1G -Xmx2G'
        catalina_home: /opt/tomcat
    instance01:
      options:
        *tomcat_opts
    instance02:
      options:
        opts: '-Xms2G -Xmx2G'
        catalina_home: /opt/tomcat-02

as you can see:

  • at line 6 we define the &tomcat_opts anchor with lines 7 and 8 as contents
  • at line 11 we use the *tomcat_opts alias to refer to the contents of the &tomcat_opts anchor

so "instance01" uses the defaults defined by &tomcat_opts anchor, whereas "instance02" uses explicitly defined values.

Let's have yq parsing it to see what happens:

cat anchors.yml | yq -y .

the output is as follows:

- name: Update Tomcat Application Servers
  hosts: apps-ci-up3a
  vars:
    tomcat:
      options:
        opts: -Xms1G -Xmx2G
        catalina_home: /opt/tomcat
    instance01:
      options:
        opts: -Xms1G -Xmx2G
        catalina_home: /opt/tomcat
    instance02:
      options:
        opts: -Xms2G -Xmx2G
        catalina_home: /opt/tomcat-02

yq as expected expands the alias with the contents of the related anchor.

Be wary that YAML anchors and aliases cannot use the flow-style (compact) syntax, since they cannot contain ' [ ', ' ] ', ' { ', ' } ', and ' , ' characters.

But what does it happen if we try to do an override too, for example explicitly setting a different home to "instance01" like in the following snippet?

---
- name: Update Tomcat Application Servers
  hosts: apps-ci-up3a 
  vars:
    tomcat:
      options: &tomcat_opts
        opts: '-Xms1G -Xmx2G'
        catalina_home: /opt/tomcat
    instance01:
      options:
        *tomcat_opts
        catalina_home: /opt/tomcat-01
    instance02:
      options:
        opts: '-Xms2G -Xmx2G'
        catalina_home: /opt/tomcat-02

let's try to parse it with yq:

cat anchors.yml | yq -y .

this time we have the following error:

yq: Error running jq: ParserError: while parsing a block mapping
  in "", line 10, column 7
expected , but found ''
  in "", line 12, column 9.

so we cannot make overrides when using aliases, ... at least not with the above syntax.

Overrides

Overrides require the alias to be preceded by <<: - create the file "overrides.yml" with the following contents:

---
- name: Update Tomcat Application Servers
  hosts: apps-ci-up3a
  vars:
    defaults:
      options: &tomcat_opts
        opts: '-Xms1G -Xmx2G'
        catalina_home: /opt/tomcat
    tomcat01:
      options:
        <<: *tomcat_opts
        catalina_base: /opt/tomcat/instance-01
    tomcat02:
      options:
        <<: *tomcat_opts
        opts: '-Xms2G -Xmx2G'
        catalina_base: /opt/tomcat/instance-02

so this time:

  • at line 6 we define the &tomcat_opts anchor with lines 7 and 8 as contents
  • *tomcat_opts alias is applied to both the instances (line 11 and line 15)
  • each of the instances is performing overrides (line 12, lines 16-17)

let's parse it with yq:

cat overrides.yml | yq -y .

the output is as follows:

- name: Update Tomcat Application Servers
  hosts: apps-ci-up3a
  vars:
    defaults:
      options:
        opts: -Xms1G -Xmx2G
        catalina_home: /opt/tomcat
    tomcat01:
      options:
        opts: -Xms1G -Xmx2G
        catalina_home: /opt/tomcat
        catalina_base: /opt/tomcat/instance-01
    tomcat02:
      options:
        opts: -Xms2G -Xmx2G
        catalina_home: /opt/tomcat
        catalina_base: /opt/tomcat/instance-02

Using YAML TAGS

We already saw what YAML tags are,  so now let's see then in action using Python and PyYAML library - just create "tags.yml" file with the following contents:

name: Update Tomcat Application Servers
hosts: apps-ci-up3a
defaults: &defaults
  catalina_home: /opt/tomcat
vars:
  - !Instance
    name: instance01
    options:
      <<: *defaults
      opts: -Xms1G -Xmx2G
      catalina_base: /opt/tomcat/instance01
  - !Instance
    name: instance02
    options:
      <<: *defaults
      opts: -Xms2G -Xmx2G
      catalina_base: /opt/tomcat/instance02

Remember that tags are only used to "clarify" types: here we defined two nodes of !Instance type (line 6 and line 12).

Let's parse it with yq to see how this YAML gets interpreted:

cat tags.yml | yq -y .

the output is as follows:

hosts: apps-ci-up3a
defaults:
  catalina_home: /opt/tomcat
vars:
  - name: instance01
    options:
      catalina_home: /opt/tomcat
      opts: -Xms1G -Xmx2G
      catalina_base: /opt/tomcat/instance01
  - name: instance02
    options:
      catalina_home: /opt/tomcat
      opts: -Xms2G -Xmx2G
      catalina_base: /opt/tomcat/instance02

as you can see, aliases get expanded using the value of the anchor, and tags simply "disappear".

But they are still there: we can use them to easily convert types into code indeed: create the "tags.py" file with the following contents:

#!/usr/bin/env python3
import yaml

class Instance:
    """Instance class."""
    def __init__(self, name, options):
        self._name, self._options = name, options

    @property
    def name(self):
        return self._name;

    @property
    def options(self):
        return self._options;

def instance_constructor(loader: yaml.SafeLoader, node: yaml.nodes.MappingNode) -> Instance:
    """Construct an instance."""
    return Instance(**loader.construct_mapping(node))

def get_loader():
    """Add constructors to PyYAML loader."""
    loader = yaml.SafeLoader
    loader.add_constructor("!Instance", instance_constructor)
    return loader

instances=yaml.load(open("tags.yml", "rb"), Loader=get_loader())

print("Instances:")
for instance in instances['vars']:
    print(instance.options)

let's discuss the code:

  • line 24 maps the "instance_constructor" function to the "!Instance" YAML tag: this means that each time a node with !Instance tag is found, this function is called to process it
  • the "instance_constructor" function returns a new instance of the "Instance" class (line19).
  • it iterates the "vars" node and prints the "options" of each item (lines 30-31).

Let's assign the execute permission to it and have a go:

chmod 755 tags.py
./tags.py

the output is as follows:

Instances:
{'catalina_home': '/opt/tomcat', 'opts': '-Xms1G -Xmx2G', 'catalina_base': '/opt/tomcat/instance01'}
{'catalina_home': '/opt/tomcat', 'opts': '-Xms2G -Xmx2G', 'catalina_base': '/opt/tomcat/instance02'}

as you see from it, the outcome of loading the YAML is actually the creation of two instances of the Instance class.

If you want some precious hints on Python, I suggest you to read the following posts of a trilogy I wrote about how to develop a full-featured Python3 project: Python Full Featured Project, Python Setup Tools and Packaging a Python Wheel as RPM.

Footnotes

Here it ends our quick tour of the amazing world of YAML: instead of limiting to show only the grammar, I preferred to leverage on yq and Python to show you things in action. However, be wary that although we saw how to deal with YAML using yq, when dealing with YAML it is more convenient to avoid writing shell scripts and instead use other scripting languages that can natively handle it, such as Python.

In my opinion yq is a powerful tool, but I use it only to perform ad-hoc commands or to add YAML support to scripts that maybe is not worth the effort to rewrite into another language.

By the way, this post is part of a trilogy of posts dedicated to markup and serialization formats, so be sure not to miss

Writing a post like this takes a lot of hours. I'm doing it for the only pleasure of sharing knowledge and thoughts, but all of this does not come for free: it is a time consuming volunteering task. This blog is not affiliated to anybody, does not show advertisements nor sells data of visitors. The only goal of this blog is to make ideas flow. So please, if you liked this post, spend a little of your time to share it on Linkedin or Twitter using the buttons below: seeing that posts are actually read is the only way I have to understand if I'm really sharing thoughts or if I'm just wasting time and I'd better give up.

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