What did you do this past week?
This past week my team met up and discussed our plan for the last phase of the project. We decided how we wanted to do our presentation and the kinds of visualizations we should make. Besides, I figured out how to create and populate an in-memory database for the backend tests.
What’s in your way?
There are still some issues with the mock DB, so I need to do more debugging. Also, looking at the feedback we got from phase 3, we need to fix a couple of issues in our Postman documentation and refactor our front-end code for sorting/filtering.
What will you do next week?
Next week, I will finish debugging the mock DB and start to refactor our front-end code. I will also have more meetings with my teammates to discuss the details of our presentation. We plan to have all the visualizations done by the end of next week, so we can just spend the last couple of days making the presentation video.
If you read it, what did you think of the What Happens to Us Does Not Happen to Most of You?
Unfortunately, I didn’t get a chance to read this week’s paper.
What was your experience of joins and refactoring? (this question will vary, week to week)
Overall, I think that the concept and the SQL code for joins are straightforward and explained clearly during lectures. It was interesting to see different ways to join multiple tables and extract out the information we needed. The only part I found a bit confusing was where a table was joined with itself. For refactoring, I agree that improving the readability of your code is really important, especially if someone else needs to use or modify your code in the future. I hope to learn more about refactoring in the next’s lectures.
What made you happy this week?
I got all the classes I wanted during registration! Also, since most of my classes are marked as in-person next semester, I am looking forward to going back to campus.
What’s your pick-of-the-week or tip-of-the-week?
My pick of the week is Google Colab notebooks. It is a tool that allows you to use and collaborate with others on Jupyter notebooks without downloading or installing anything on your computer. To use it, you can simply go to your google drive and create a new document there (just like how you create a new google doc). It’s a great place to test out any python code for machine learning or data analysis projects.