Welcome to Part 6 of our series: File Handling and Error Management! This section marks a huge leap in the power and usefulness of the programs we can build.
So far, every program we’ve written has had a major limitation: it has no memory. The moment our script finishes running, all the data we created—every variable, list, and dictionary—vanishes forever.
In this post, we’ll introduce the crucial concept of data persistence—the ability to make our programs remember information between runs.
The Problem: Volatile Memory
All the data we’ve worked with until now has been stored in your computer’s RAM (Random-Access Memory). RAM is incredibly fast, which makes it perfect for the active, moment-to-moment work a program does while it’s running.
However, RAM is volatile. Think of it as a whiteboard. Your program can quickly write, read, and erase information on it. But as soon as the program finishes, the whiteboard is wiped completely clean.
This is why our to-do list from Post #57 and our contact book from Post #74 started empty every single time we ran them. The data wasn’t saved anywhere permanent.
The Solution: Data Persistence and Files
To make our programs remember things, we need to save our data to non-volatile storage, like your computer’s hard drive or SSD (Solid-State Drive).
This is the equivalent of taking the information from the temporary whiteboard and writing it down in a permanent notebook. Even after you walk away (the program closes), the information in the notebook remains, ready to be read the next time you open it.
This principle of saving data in a way that it survives after the program terminates is called data persistence. The most fundamental way for our Python programs to achieve persistence is by reading and writing files.
What’s Coming Up in Part 6
Over the next series of posts, we will learn the essential skills for working with files and making our programs more robust. We will cover:
- How to open files, read their contents, and write new data to them.
- How to work with common structured data formats like CSV (for spreadsheet-like data) and JSON (the language of web APIs).
- Just as importantly, we’ll learn how to handle errors. What if the file we’re trying to read doesn’t exist? A robust program shouldn’t crash. We’ll learn how to manage these exceptions gracefully.
What’s Next?
By learning to work with files, we are giving our programs a long-term memory. This will allow us to build applications that can save user data, store configurations, and interact with the wider world of data on our computers.
Before we can open our first file, we need to know how to tell our program where to find it. This involves understanding the concept of file paths. In Post #144, we will learn the difference between absolute and relative file paths.
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Experienced Cloud & DevOps Engineer with hands-on experience in AWS, GCP, Terraform, Ansible, ELK, Docker, Git, GitLab, Python, PowerShell, Shell, and theoretical knowledge on Azure, Kubernetes & Jenkins. In my free time, I write blogs on ckdbtech.com