Day 26: Connecting to Databases in Python

 So far in this series, we’ve worked with variables, functions, OOP, modules, and even Python’s built-in libraries. But in real-world projects, storing data in files isn’t always enough — that’s where databases come in.

Python provides multiple ways to connect to databases like SQLite, MySQL, PostgreSQL, and MongoDB. In this post, we’ll start with the most common relational databases.

                                            

1. Why Use a Database?

• To handle large amounts of data efficiently

• To perform fast queries and updates

• To maintain data consistency

• To support multiple users accessing data simultaneously

2. SQLite (Built-in Database)

SQLite comes bundled with Python, so no extra installation is required.

Example: Connecting to SQLite

                            

✅ Easy, lightweight, perfect for small projects.

3. Connecting to MySQL

For MySQL, you’ll need the library:

                

Example:

                                        

4. PostgreSQL

Install library:

                                      

Example:

                                            

5. Key Points to Remember

• Always close the connection after work

• Use placeholders (?, %s) to prevent SQL injection

• Commit changes when modifying data

• Use connection pooling in production for efficiency

✅ Conclusion

Databases make Python applications powerful and scalable. Start with SQLite for practice, then move on to MySQL or PostgreSQL for real-world projects.

Tomorrow, we’ll look at performing CRUD operations in detail with Python and databases. 🚀

Keep This in Mind:

                                “A database is like memory for your applications — without it, programs forget everything the moment they stop.”