Building a Simple CSV-Based Expense Tracker in Python (Step-by-Step)

Managing personal finances is a skill and building your own tool to do it? That’s empowering. In this tutorial, I’ll walk you through how to create a command-line based Expense Tracker in Python that stores and analyzes expenses using a CSV file.

This project is part of my hands-on learning journey to grow more confident in Python and command-line tools. It’s beginner-friendly, practical, and something you can actually use or expand into a larger app.

---

Prerequisites

• Python 3.x installed
• Basic knowledge of Python syntax
• Command Line (Terminal or CMD)
• A text editor (e.g., VS Code)

---

Project Setup

Open your terminal and run:

bashCopyEdit 
mkdir expense_tracker
cd expense_tracker
touch tracker.py expenses.csv README.md

Inside expenses.csv, paste:

csvCopyEdit Date,Category,Description,Amount

This will act as your database.

---

Step-by-Step Breakdown

1. Add New Expense Entries

We start by writing a function to add user input to the CSV:

pythonCopyEdit 
from datetime import datetime
import csv

def add_expense():
    date = input("Enter date (YYYY-MM-DD) or press Enter for today: ") or datetime.today().strftime('%Y-%m-%d')
    category = input("Enter category (e.g., Food, Transport): ")
    description = input("Enter description: ")
    amount = input("Enter amount: ")

    with open("expenses.csv", "a", newline="") as file:
        writer = csv.writer(file)
        writer.writerow([date, category, description, amount])
        print("✅ Expense added.")

2. View All Expenses

pythonCopyEdit
def view_expenses():
    with open("expenses.csv", "r") as file:
        reader = csv.reader(file)
        next(reader)
        for row in reader:
            print(row)

3. Calculate Total Spending

pythonCopyEdit
def total_spent():
    total = 0
    with open("expenses.csv", "r") as file:
        reader = csv.reader(file)
        next(reader)
        for row in reader:
            total += float(row[3])
    print(f"Total spent: ${total:.2f}")

4. Filter by Category

pythonCopyEdit
def filter_by_category(category):
    with open("expenses.csv", "r") as file:
        reader = csv.reader(file)
        next(reader)
        for row in reader:
            if row[1].lower() == category.lower():
                print(row)

5. Use CLI Arguments to Trigger Actions

pythonCopyEdit
import sys

if __name__ == "__main__":
    if len(sys.argv) < 2:
        print("Usage: python tracker.py [add | view | total | filter <category>]")
    elif sys.argv[1] == "add":
        add_expense()
    elif sys.argv[1] == "view":
        view_expenses()
    elif sys.argv[1] == "total":
        total_spent()
    elif sys.argv[1] == "filter" and len(sys.argv) == 3:
        filter_by_category(sys.argv[2])
    else:
        print("Invalid command.")

6. Run It Like a Pro

bashCopyEdit
python tracker.py add
python tracker.py view
python tracker.py total
python tracker.py filter Food

---

📦 Stretch Goals

• Sort by amount or date
• Export results to new CSV
• Use argparse for better CLI experience
• Add visual summary using matplotlib or pandas

---

GitHub Repo

You can view the full project and code here:
👉 GitHub Link to Your Repository

---

Final Thoughts

This project is a great way to get comfortable using Python in a practical way. You’ll understand how to work with real data, write clean code, and build useful tools—skills that form the backbone of software development.