How to Install YAML in Python
We will introduce YAML
in Python. We will also introduce how to install YAML
on different devices.
YAML in Python
YAML is a serialization language. Serialization language means that applications written with different technological languages with different data structures can transfer data to each other through different formats.
The most common and useful format, in this case, is YAML. YAML is a data serialization format for human readability and is linked with scripting languages.
The popularity of YAML has increased over time because it is easily readable by humans.
This feature makes it a great fit for writing different configuration files. Python has its YAML
library PyYAML
, a YAML
parser for Python.
There are different features of YAML. The main features are as follows:
- It is a complete YAML 1.1 parser.
- It provides Unicode support.
- It can also provide pickle support.
- It has a capable extension API.
- And sensible error messages.
PyYAML
provides support for different standard YAML tags. It can also provide Python-specific tags that permit you to represent different Python objects.
PyYAML
can help us to perform tasks easily. They are applicable for tasks that vary from complex configuration files to different object serialization.
Installation of YAML in Python
There are some requirements for installing YAML. We should have the latest versions of pip
and setuptools
installed.
The setuptools
require environment marker support (setuptools
with a version greater or equal to 20.6.8), and it is linked with Python 3.4.6 but doesn’t support 3.4.4.
We can install setuptools
using the following code.
pip install -U pip setuptools wheel
For our environment (virtualenv
, (Docker) container, etc.), before installing ruamel.yaml
, it is better to install ruamel.yaml
from PyPI
using the following command.
pip install ruamel.yaml
After that, we can easily install the PyYAML
using the following command.
pip install PyYAML
Rana is a computer science graduate passionate about helping people to build and diagnose scalable web application problems and problems developers face across the full-stack.
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