A google colab notebook, that collects time logged in and logged out with a press of a button.
Why an App?
For a few months, I was tracking my hours with an excel sheet, but it got tedious and a bit boring just entering data 🤷 I wanted something to automate this task and coding a project is fun! 👍
Plus, It gives me practice in python programming 💻 and I have something to work on if I ever wanted to refactor and tinker with my code down the road.
Salary or Hourly?
Having been an hourly employee from the start of my working life up to June 2021, I decided to create an app to track my salaried hours. This is built entirely on google colab and stores data in my google drive.
How did I built this?
I started this project by reading and cleaning the data from my google sheets. Along the way I found some mistakes with my manual entries like wrong dates or day, this has to be fixed first. Then, I converted this data to a pandas DataFrame.
The challenging part is to create this entire logging app, where will I store it? How can build a DataFrame that is just like excel? Like entering log in and log out in separate cell? I'm sure there was already solutions with this problem posted somewhere, but I wanted to create and come up with the solution myself.
My solution is to create a separate
timein.csvandtimeout.csvfile, then concatenate this two to create a main dataframe, if the length oftimeinandtimeoutlogs are off, then I must have made a mistake in double logging or forgetting to log, a solution that I found was to have print statements that returns the number of logs.
Storage problem was solved using my google drive, I specified a path where I wanted my log to be saved and every entry is appended.
What about logging mistakes?
This is where the challenging part started, My first solution was undo the last log. I did this by reading the file, find the last line of the file and re-write everything except the last line.
Another solution, is to replace the value in the DataFrame, using index. First, by finding the log that needs editing, second, using the index to find which entry is to be edited then enter the edits manually. Then, re-write this as file.
Libraries used:
- pandas
- datetime
- pytz
- csv
- xcelwriter
Features:
- Hours Analyses - Average hours worked by week and day
- Analyses Table - Hours worked vs hour rate vs overtime rate
- Back ups - Auto saves into csv and excel file in google drive
- Data Visualization - Quickly see trends
Functionalities:
- log time or time out with just a click
- undo last log
- edit time in or time out
- number of records are returned after every log, to ensure accuracy