Data Structures Writeup | Ian’s CSP Blog

[utterances-bot]

Data Structures Writeup | Ian’s CSP Blog

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https://iwu78.github.io/csp-blog/2024/04/16/DataStructuresWriteup_IPYNB2.html

[Lin-cT]

Reviewer: Lindsay Tang

Collections- Attempted: 1/1, Accuracy: 1/1 Demonstrates the correct code and provides a picture of the SQL Database to demonstrate the stored data. Very concise and organized.

Lists and Dictionaries- Attempted: 1/1, Accuracy: .8/1 Demonstrations are mostly all correct. Shows an example of a list in debugger, and also one example of a dictionary, except the image is a duplicate.

APIs and JSON- Attempted: 1/1, Accuracy: .9/1 Demonstrates all the code in Postman and shows responses in screenshot. Concise. One requirement could not be met due to the way the code was programmed.

Frontend- Attempted: 1/1, Accuracy: 1/1 Demonstrates correct frontend responses from Put, Post, and Get. Displays the code and is very concise.

[vynx1]

Grading:

Collections - Total 3 / 3, Grade 0.99/1

All the requirements were met, but seemed to lack data/data seemed to be only testing data. Would recommend at least 10-20 data entries just to prove you're actually using the date. By seeing your code and understanding it I know your using the data, but more data will never hurt you.

Lists and Dictionaries - Total 3/3, Grade 0.98/1

Met all the requirements, and demonstrated excellent use of VSCODE Debugging. Would've liked to see more explanation on how you made your list, ie: how did you get styling data?, and the purpose of the list in your code. Just a tiny bit of explanation and comments needed,

APIs and JSON - Total 7/7, Grade .99/1

Had all the necessary requirements, but I think you could've added more. At the top you talked about your design python model, and I think a more in-depth of analysis of that would've been nice here. I know your coding skills are great, but talking about the simple USER function seems like a waste when you have a better/more in-depth function you can discuss.

Frontend - Total 8/8, Grade .96/1

Frontend contained all of the necessary requirments, but the code was missing comments and explanations. Make sure to add them to the code themselves. your explanation of the code outside of comments was good, but I would like to see them in the comments of the code as well.

Optional/Extra, ML Algorithm Analysis - Total 5/5, Grade 1/1

The machine learning was done really well. As someone who likes ML your method of explaining was really well done. The additional images and diagrams along with how you explained these diagrams showed that you didn't just copy and paste Mr M's code, but you really spent time learning, understanding, and iterating on it.

Improvements: Add in a bit more commenting and documentation to bits and pieces in your code, and talk about your Design Model more and how you integrated it with your API/Backend usage.

3.93/4 Regular

1/1 Extra ML

[Lin-cT]

Demonstrates the following:

• [ ] Sorting
• [ ] Hashing / Dictionaries
• [ ] Algorithms
• [ ] Object-Oriented design
• [ ] Collections / Lists

Total Points 3.86/4 Extra Points .94/1

Collections - Total 2.9/3, Grade .97/1

• [ ] Blog Python Model code and SQLite Database. -[ ] Show your unique collection/table in database, display rows and columns in the table of the SQLite database from VSCode using SQLite3 Editor. -[ ] Show your unique code that was created to initialize table and create test data from VSCode model.

Feedback: I see that you've made changes to clarity and explained the columns within the database. One slightly knit-picky thing I have is that your initialize data still does not look amazing, but at least you cleared it up from last time and the users from last time were cleared up.

Lists and Dictionaries - Total 2.85/3, Grade .95/1

• [ ] Blog Python API code and use of List and Dictionaries.
  • [ ] Show a list as extracted from database as Python objects in VSCode using Debugger.
  • [ ] Show two distinct examples of dictionaries, show Keys/Values using debugger in VSCode.

Feedback: I like how in-depth the explanations are on your blog, however in your screenshot of the dictionary in the debugger does not have the code shown, unlike your list in debugger. I would like for you to show the code and the breakpoints in the screenshots next time.

APIs and JSON - Total 6.7/7, Grade .96/1

• [ ] Blog Python API code and use of Postman to request and respond with JSON.
  • [ ] Show Python API code definition for request and response using GET, POST, UPDATE methods in VSCode. Discuss algorithmic condition used to direct request to appropriate Python method based on request method.
  • [ ] Show algorithmic conditions used to validate data on a POST condition in VSCode.
  • [ ] Show URL request and Body requirements for GET, POST, and UPDATE methods in Postman.
  • [ ] Show the JSON response data for 200 success conditions on GET, POST, and UPDATE methods in Postman.
  • [ ] Show the JSON response for error for 400 when missing body on a POST request in Postman.
  • [ ] Show the JSON response for error for 404 when providing an unknown user ID to a UPDATE request in Postman.

Feedback: The screenshots are accurate in demonstrating the body requirements, the JSON response for 200 and response for 400. However, when explaining the algorithmic conditions, a more fleshed out and clearer explanation is expected. Even though no JSON response for providing an unknown user ID is shown, it is due to a higher level of skill demonstrated. Error handling for an unknown user was implemented into their code, and thus there isn't even a possibility of providing an invalid user ID for a PUT request, as they utilize cookies to prevent this error. The point for that question was deserved.

Frontend - Total 7.8/8, Grade .98/1

• [ ] Blog JavaScript API fetch code and formatting code to display JSON.
  • [ ] Show response of JSON objects from fetch of GET, POST, and UPDATE methods in Chrome inspect.
  • [ ] Show a demo (GET) of obtaining an Array of JSON objects that are formatted into the browsers screen in the Chrome browser.
  • [ ] Describe fetch and method that obtained the Array of JSON objects in JavaScript code.
  • [ ] Show code that performs iteration and formatting of data into HTML in JavaScript code.
  • [ ] Show a demo (POST or UPDATE) gathering and sending input and receiving a response that show update. Repeat this demo showing both success and failure in the Chrome browser.
  • [ ] Show and describe code that handles success. Describe how code shows success to the user in the Chrome Browser screen in JavaScript code.
  • [ ] Show and describe code that handles failure. Describe how the code shows failure to the user in the Chrome Browser screen in JavaScript code.

Feedback: Method responses are fine. Shows code that preforms iteration and formatting of data received from backend and displays it onto a table. The demo of the PUT request shows a successful PUT and error, and demonstrates code for success and error handling. However still, I am looking for a more in-depth explanation when describing the fetch method for receiving an array.

Optional/Extra, ML Algorithm Analysis - Total 4.7/5, Grade .94/1

• [ ] Machine Learning Algorithm Analysis
  • [ ] Show algorithms and preparation of data for analysis. This includes cleaning, encoding, and one-hot encoding.
  • [ ] Show algorithms and preparation for predictions.
  • [ ] Discuss concepts and understanding of Linear Regression algorithms.
  • [ ] Discuss concepts and understanding of Decision Tree analysis algorithms.

Feedback: The demonstration of your own machine learning algorithm is neat and concise. But, when looking at your understanding of Decision Tree analysis algorithms and even Linear Regression, I see a lack of explanation (specifically Decision Tree). I would like for more explanation on what nodes are, and how a Decision Tree even works. While you explained that it makes decisions depending on the nodes, you never explained what they are. I would like more clarity on that.

[Lin-cT]

Grading Breakdown:

Collections: Total 3/3, Grade .97/1 Lists and Dictionaries: Total 3/3, Grade .95/1 APIs and JSON: Total 7/7, Grade .96/1 Frontend: 8/8, Grade .98/1 Optional/Extra, ML Algorithm Analysis: Total 5/5, Grade .94/1 Total: 4.8/5, 9.6/10