Serialization: Understanding Its Role in Python, Java, and Data Management

Serialization protects data during transfer from third party sources by converting it into different formats. Python and Java use serialization to securely transfer data across domains, between databases, through firewalls, and more, ensuring safe and reliable data management. As a programmer, you might use serialization for efficient data exchange across various platforms, reduced latency, and safe data transmission.

Expand your understanding of serialization’s role in Python and Java and learn the fundamentals of serialization in programming. 

What is serialization?

Serialization refers to transforming data into a format you can transmit over a network or save in a database. To complete this task, you can use data serializers to convert data objects into byte streams that hold the information until the stream converts back into an object. Serialization is an excellent choice for storing large amounts of data because it reduces storage space usage. Additionally, serialized data enables real-time information processing, making it a valuable solution for faster data management. 

Deserialization is serialization’s counterpart. It converts byte streams back into data objects. After transfer, you will need to deserialize your data to read and interact with it appropriately. 

Serialization and deserialization work together to help you store and transfer data from one platform to another.

How serialization works in programming

You can use many data serialization languages as serializers to encode your data for efficient data transmission. Once your data is serialized, you can save it in various formats, including JSON and XML. You can use JSON and XML to store and convert data into strings to ensure it’s seamlessly and efficiently transferred. 

Common serialization formats 

JavaScript Object Notation (JSON) is a data interchange language that enables serialization and deserialization of data. It integrates well with various other languages, including C++, C, Java, Python, and many more, ensuring accessibility and ease of use. You can transform a JavaScript object into a JSON string, serializing it and making it easily transferable. 

XML serialization refers to the process of transforming XML data into a serialized string format to enable data transfer. XML only works with public objects and doesn’t support private information. An XML serializer is helpful if you need to determine whether to encode a field as an attribute or an element. 

Serialization in Python

Python provides various serialization modules, including pickle, JSON, and marshal. 

Python serialization modules 

Pickle applies binary formats to serialize and deserialize Python data. “Pickling” refers to the process of serializing objects and turning them into bytes, then deserializing the byte back into an object. Pickle is synonymous with serialization but for Python objects. Developers created the pickle module to manage complex data structures while maintaining overall structure. Pickle isn’t readable to humans, which makes it difficult to manually debug and manage.

As described previously, JSON is a serialization module written in Javascript that enables you to code Python objects into JSON format and then decode JSON-formatted objects back into Python format. The JSON module is a text serialization format that is interoperable with various libraries outside of Python and is human and machine-readable.

Marshal enables you to read and write Python data in a binary format. Marshal’s primary purpose is to simplify the reading and writing of code within Python modules. Marshal also enables serialization methods, but again, it only works with Python objects. It’s the fastest serialization method, yet not as versatile in comparison to JSON and pickle because it only supports elementary data, such as lists, numbers, and strings. 

Serialization in Java

Serialization in Java, serialization allows you to convert an object into a stream and send it securely over a network. 

Java serializable interface 

When serializing data in Java, you must identify and validate the Java class and restore the data in a new format. The interface enables you to perform serializable methods, including labeling Java classes and defining a specific method, such as writeObject, readObject, writeReplace, or readResolve. 

• writeObject: Determines what information to save. 

• readObject: Reads the information written by the writeObject method and updates the object’s state after it’s restored. 

• writeReplace: Enables a class to write a replacement object into the stream.

• readResolve: Enables the class to identify the replacement object. 

In Java, you can implement serialization by saving files or sending them over a network using ObjectInputStream and ObjectOutputStream. 

Serialization in data management

Serialization manages data by implementing the following tasks:

• Data standardization: Serialization standardizes the representation of complex data structures across various systems. 

• Data transmission: Serialization compresses the data, ensuring more storage space and efficient data transfer over networks. 

• Data structure: Serialized data supports changes in the data structure, enabling compatibility and versioning. 

• Data retrieval: When you need to retrieve the data within the serialization, you can efficiently deserialize it back to its original format, simplifying the data retrieval process. 

Choosing the correct serialization method 

The serialization method you choose to use depends on your project requirements and the language you work in. For Python, you have three serialization methods to choose from. Each has its own unique benefits and potential disadvantages.

• JSON: JSON is a good choice for data you can easily read and interpret. Some methods, such as pickle, are not human-readable, which can make working with the data difficult. JSON is also interoperable with various other formats, which may be beneficial if you’re using libraries other than Python. Generally, developers use JSON for web APIs and configuration files. 

• Pickle: If you’re handling mass amounts of complex Python data, pickle would be a good choice because of its ability to handle intricate data streams within Python. Additionally, if you’re working solely with Python objects, you may want to consider pickle, as it can serialize a variety of Python objects. However, Pickle is generally used for internal data storage and object persistence. 

• Marshal: Marshal is best for serializing code for Python objects. If you’re hoping for a quick serialization method, marshal is a good choice, but keep in mind that it has low-level capabilities compared to JSON and pickle. It’s also important to note that marshal isn’t safe against maliciously constructed data, so don’t marshal and unmarshal data from an unauthenticated source. 

If you’re hoping to serialize information within Java, you can use the Java serializable interface. The readObject, writeObject, writeReplace, and writeResolve methods can help you change the way the data is saved and its serialization behavior. 

Getting started with serialization on Coursera

Serialization is an important way to ensure the safe and secure transfer of data between databases and across networks. 

You can advance your knowledge of serialization and build in-demand skills on Coursera. For example, you might learn how to work with Python and advance your data analytics skills with the IBM Full-Stack JavaScript Developer Professional Certificate, where you’ll build the skills and hands-on experience to get job-ready in under four months, no prior experience required. You could also choose to advance your knowledge of data structures and Java programming with UC San Diego’s Object Oriented Java Programming: Data Structures and Beyond Specialization.