Budget Smartly with Python: A Feature-Packed Budget Tracker Program

danitellini — Tue, 29 Oct 2024 08:47:00 +0000

Introduction

Managing personal finances can be challenging, especially when balancing bills, expenses, and savings. Inspired by this everyday need, I created a budget tracker program in Python, designed to simplify personal budgeting and empower users to take control of their finances. This program features tracking income, expenses, and recurring bills and even set and manage savings goals. It was designed to be a practical, interactive tool, suitable for both beginner programmers and individuals seeking an easy-to-use budgeting solution.

Program Overview

Above: A screenshot of the budget tracker's main menu

The program has several core functionalities, allowing users to:

Add Income and Expenses: Track all sources of income and expenses, each recorded with timestamps.
Manage Recurring Bills: Set up bills to automatically recur at specified intervals (weekly, monthly), with automatic balance updates.
View and Delete Entries: Quickly access and delete entries for income, expenses, or bills as needed.
Set and Monitor Savings Goals: Users can create multiple savings goals and monitor their progress with calculated time frames based on contributions.
Export Data to CSV: For more detailed analysis, users can export all data to a CSV file, compatible with software like Excel or Google Sheets.

Code Description

The code is written in Python and organized into modular functions for each major feature. The main program uses a command-line interface, which interacts with the user in real time. Here are some key highlights:

Persistent Data Storage: All data, including the last program startup time, is stored in a JSON file. This allows the program to process and display only the processed recurring bills during the time between each new session start.
Recurring Bill Processing: Bills are scheduled based on a timestamp of the previous session, ensuring that only new bills appear for processing. The program calculates new due dates for recurring bills and adjusts the user's balance as bills are processed.
CSV Export with Timestamps: Each income and expense entry includes a timestamp, and users can export this data to a CSV file for external analysis.
Error Handling: The program includes input validation, ensuring entries for income, expenses, bills, and other data are correctly formatted.

You can find the complete code on GitHub here. It's well-commented for clarity and easy modification, perfect for anyone looking to understand or build upon this functionality.

Conclusion

This budget tracker is more than just a Python program -- it's a real-world application that simplifies personal budgeting. The program can be easily expanded or customized for new features. Whether you're looking to improve your Python skills or streamline your finances, I hope this project can serve as both an educational and practical tool.

Feel free to check out the code on GitHub, and let me know what you think! Happy coding and happy budgeting!

Portfolio Project - Intro to IT - Software Development Concepts

danitellini — Sat, 12 Oct 2024 07:23:47 +0000

Speeding Up Log Searches with a Pattern Searching Algorithm

Tired of digging through endless logs just to find one pesky error? A pattern searching algorithm can do all the heavy lifting for you, saving you tons of time. Instead of sifting through log after log, this algorithm scans them for you, looking for specific keywords like "ERROR" or "FAILURE." It’s like having a super-fast assistant to help you out.

Here's how it works: You give the algorithm the pattern you want to find and a list of logs. It checks if there are logs to search, then if you’ve provided a pattern. If something’s missing, it lets you know with messages like “No logs to search” or “No pattern provided.” If everything’s good, it searches through each log, saving any that match the pattern. Once done, it either gives you the list of matches or says, “No pattern found.”

The process is simple, as you can see in this flowchart.

Here’s the pseudocode to give you a peek at the logic behind it:

define pattern
define log or logs
create list_of_logs = []

if list_of_logs is empty:
  "No logs to search"
  end

if pattern is empty:
  "No pattern provided"
  end

create pattern_present = []

for each log in list_of_logs:
  if pattern is found in the log:
    append the log to pattern_present
  end if
end for

if pattern_present is empty:
  "No pattern found"
  end

return the pattern_present list
end

And that's it! With this simple algorithm, you'll breeze through your logs, find exactly what you need, and move on to bigger things.