7 Methods to Convert Python Arrays to YAML

This tutorial guides you through various methods to serialize Python arrays to YAML using different libraries.

We’ll use libraries such as PyYAML, ruamel.yaml, and oyaml, as well as manual methods.

 

 

Using PyYAML

To install PyYAML, use pip:

pip install pyyaml

You can use the yaml.dump function to convert a Python array to a YAML string:

import yaml
data = ['Ahmed', 'Fatma', 'Hassan', 'Mona']
yaml_str = yaml.dump(data)
print(yaml_str)

Output:

- Ahmed
- Fatma
- Hassan
- Mona

The output shows the array serialized into YAML format where each element is listed with a hyphen.

You can also serialize more complex data structures like arrays of dictionaries:

import yaml
employees = [
    {'name': 'Sara', 'age': 30, 'department': 'Engineering'},
    {'name': 'Khaled', 'age': 28, 'department': 'Marketing'},
    {'name': 'Layla', 'age': 35, 'department': 'Sales'}
]
yaml_str = yaml.dump(employees)
print(yaml_str)

Output:

- age: 30
  department: Engineering
  name: Sara
- age: 28
  department: Marketing
  name: Khaled
- age: 35
  department: Sales
  name: Layla

The output displays the list of dictionaries converted into YAML.

 

Using ruamel.yaml

Install ruamel.yaml using pip:

pip install ruamel.yaml

To convert a Python array to YAML while preserving the order and formatting, use ruamel.yaml:

from ruamel.yaml import YAML
yaml = YAML()
data = ['Ali', 'Salma', 'Youssef', 'Nadia']
with open('output.yaml', 'w') as file:
    yaml.dump(data, file)

Output(output.yaml):

- Ali
- Salma
- Youssef
- Nadia

 

Using yaml Module with Custom Serialization

You can define custom representers to control how objects are serialized to YAML.

To serialize a custom Python class, define a representer:

import yaml
class Employee:
    def __init__(self, name, age):
        self.name = name
        self.age = age
def employee_representer(dumper, data):
    return dumper.represent_mapping('!Employee', {'name': data.name, 'age': data.age})
yaml.add_representer(Employee, employee_representer)
employees = [Employee('Omar', 25), Employee('Hana', 27)]
yaml_str = yaml.dump(employees)
print(yaml_str)

Output:

- !Employee
  age: 25
  name: Omar
- !Employee
  age: 27
  name: Hana

The output shows custom objects serialized with custom tags.

 

Manual Conversion

You can manually construct a YAML string from a Python array.

To manually create a YAML string from an array:

data = ['Samir', 'Dina', 'Karim']
yaml_str = '\n'.join(f'- {item}' for item in data)
print(yaml_str)

Output:

- Samir
- Dina
- Karim

The code builds the YAML string by iterating over the array and formatting each item.

 

Using oyaml

Install oyaml with pip:

pip install oyaml

Here’s how to use oyaml to convert a dictionary with ordered data:

import oyaml as yaml
from collections import OrderedDict
data = OrderedDict([
    ('name', 'Nour'),
    ('age', 22),
    ('city', 'Cairo')
])
yaml_str = yaml.dump(data)
print(yaml_str)

Output:

name: Nour
age: 22
city: Cairo

The output maintains the order of the keys as specified in the OrderedDict.

 

Using json Module

You can use the json module to convert arrays to JSON and then convert JSON to YAML.

First, convert the array to JSON:

import json
data = ['Amira', 'Yassin', 'Noha']
json_str = json.dumps(data)
print(json_str)

Output:

["Amira", "Yassin", "Noha"]

Then, convert the JSON string to a YAML string:

import yaml

yaml_str = yaml.dump(json.loads(json_str))
print(yaml_str)

Output:

- Amira
- Yassin
- Noha

 

Using Data Classes with PyYAML

Data classes can be serialized to YAML using PyYAML with custom representers.

Define a data class and a custom representer:

import yaml
from dataclasses import dataclass

@dataclass
class Product:
    name: str
    price: float
    in_stock: bool
def product_representer(dumper, data):
    return dumper.represent_mapping('!Product', data.__dict__)
yaml.add_representer(Product, product_representer)

products = [
    Product('Laptop', 15000.0, True),
    Product('Smartphone', 8000.0, False)
]
yaml_str = yaml.dump(products)
print(yaml_str)

Output:

- !Product
  in_stock: true
  name: Laptop
  price: 15000.0
- !Product
  in_stock: false
  name: Smartphone
  price: 8000.0

The output shows the data class instances serialized to YAML including all their attributes.