Python Serialization
There are many different methods for serializing data in Python. We’ll quickly look at three of them.
XML
Python includes the ElementTree library for processing XML. Unfortunately, due to the way that Python handles objects, we have to write some of the processing ourselves. There are some external libraries that will automatically explore Python objects and build the XML based on its attributes.
To write an XML file in Python, we can use code similar to this:
import xml.etree.ElementTree as ET
person = Person("Willie Wildcat", 42, Pet("Reggie", 4, "Shorkie"))
print("Saving person:")
print(person)
person_elem = ET.Element("person")
ET.SubElement(person_elem, "name").text = person.name
ET.SubElement(person_elem, "age").text = str(person.age)
pet_elem = ET.SubElement(person_elem, "pet")
ET.SubElement(pet_elem, "name").text = person.pet.name
ET.SubElement(pet_elem, "age").text = str(person.pet.age)
ET.SubElement(pet_elem, "breed").text = person.pet.breed
with open("person.xml", "w") as file:
file.write(ET.tostring(person_elem, encoding="unicode"))To construct an XML document, we simply must construct each element and set the parent element, tag, and data of each element, as shown in the example above.
import xml.etree.ElementTree as ET
xml_tree = ET.parse("person.xml")
person_elem = xml_tree.getroot()
for child in person_elem:
if child.tag == "name":
name = child.text
if child.tag == "age":
age = child.text
if child.tag == "pet":
for subchild in child:
if subchild.tag == "name":
pet_name = subchild.text
if subchild.tag == "age":
pet_age = subchild.text
if subchild.tag == "breed":
pet_breed =subchild.text
person = Person(name, age, Pet(pet_name, pet_age, pet_breed))
print("Loading person:")
print(person)Then, to parse that data, we can simply iterate through the tree structure and find each tag, loading the text data into a variable and using those variables to reconstruct our objects.
For more information on using UML, refer to these resources. The full source code can be found on GitHub:
- ElementTree in Python Documentation
JSON
To handle JSON data in Python, we can use the json library.
Then, the process for saving and loading JSON data is very similar to working with XML:
import json
person = Person("Willie Wildcat", 42, Pet("Reggie", 4, "Shorkie"))
print("Saving person:")
print(person)
person_dict = dict()
person_dict['name'] = person.name
person_dict['age'] = person.age
person_dict['pet'] = dict()
person_dict['pet']['name'] = person.pet.name
person_dict['pet']['age'] = person.pet.age
person_dict['pet']['breed'] = person.pet.breed
with open("person.json", "w") as file:
json.dump(person_dict, file)For JSON, it is easiest to construct a dictionary containing the structure and data to be serialized. This could easily be done as a method within the class itself, but this example shows it outside the class just to demonstrate how it works.
To read the serialized data, we can do the reverse:
import json
with open("person.json") as file:
person_dict = json.load(file)
person = Person(
person_dict['name'],
person_dict['age'],
Pet(
person_dict['pet']['name'],
person_dict['pet']['age'],
person_dict['pet']['breed']))
print("Loading person:")
print(person)For more information on using JSON in Python, refer to these resources. The full source code can be found on GitHub:
- JSON Library from Python Documentation
Binary using Pickle
Python also includes a built-in mechanism for serialization. All that is required is the Pickle library.
person = Person("Willie Wildcat", 42, Pet("Reggie", 4, "Shorkie"))
print("Saving person:")
print(person)
with open("person.p", "wb") as file:
pickle.dump(person, file)with open("person.p", "rb") as file:
person = pickle.load(file)
print("Loading person:")
print(person)All we have to do is open the file in a binary format by adding b to the open command.
For more information on Java serialization, refer to these resources. The full source code can be found on GitHub:
- Pickle from Python Documentation
- Using Pickle from Python Wiki