ditectrev / automation-tools-for-courses Goto Github PK

This is important, because the punctuation can give a proper reading comfort.

Converting csv from Python at this point of time results in 1 row of data in the csv format. The data is being shown again after converting to xls manually. It should contain all data in csv, automatically after running the Python script.

Ideally, it would create a table of contents first and then, based on feedback, improve/modify it slightly. Generating an entire book doesn't seem feasible for proper validation and improvement/modification of specific categories. We want to have it checked and read by a human with feedback s/he can provide. Hence, generating each chapter/main section separately would be the preferred way to proceed.

Content should be generated with code examples and occasionally with images when needed. However, for this part, a human can add an input for each chapter/main section, and then the AI will generate it.

Rest assured, the addition of code examples to CodeSandboxes can be done manually at a later stage. It might be overcomplicated to generate code snippets with CodeSandboxes, but as per Copilot, it's doable (maybe another issue after this is completed).

Other than programming books, we'd like to use it for cloud-related learning, like most of our materials. Not the questions & answers we have but also handbooks to properly teach the material.

It must be generated in Markdown format, in a format like https://github.com/Ditectrev/Awesome-HTML-Book-HyperText-Markup-Language-HTML

Both currently working scriptsweb-scrap-exam4training.py and web-scrap-vce.py return lots of data, which is different from the format we use, and for now we need to remove & format it manually.

Ideally, after scrapping we're receiving this format:

### QUESTION

![Image X](images/questionX.png) # could be the case there's no image in the question as well.

- [ ] SAMPLE WRONG ANSWER.
- [ ] SAMPLE WRONG ANSWER.
- [x] SAMPLE CORRECT ANSWER.
- [ ] SAMPLE WRONG ANSWER.

**[⬆ Back to Top](#table-of-contents)**

even better would be to include already explanation using some kind of AI-related tool (see #4 for that):

### QUESTION

 ![Image X](images/questionX.png) # could be the case there's no image in the question as well.

- [ ] SAMPLE WRONG ANSWER.
- [ ] SAMPLE WRONG ANSWER.
- [x] SAMPLE CORRECT ANSWER.
- [ ] SAMPLE WRONG ANSWER.

#### EXPLANATION.

**[⬆ Back to Top](#table-of-contents)**

The task is to automate the creation of ToC.

The current solution is based on:

1. readme.py - file to generate questions in Udemy-friendly format scrapped via web-scrap.py (with minor manual improvements, but it can be a different task) and other non-automated sources.
2. urls.py - file which to generate URL's.
3. Based on the output from 2., manually pasting those URL's to manually created ToC.

The format can be found in tests around Ditectrev repositories, such as here.

Output from the automation, ideally, would be:

| No. | Questions |
| --- | --------------------------- |
| 1   | [Question1?](#question1-url) |
| 2   | [Question2?](#question2-url) |
| 3   | [Question3?](#question3-url) |
...
| n   | [QuestionN?](#questionN-url) |

where n is the number of questions in a test.

Make it using some kind of AI tool.

Maybe solution to Ditectrev/Practice-Exams-Platform#17 could be reused for just a script generation, so it's also possible to not only have it on https://education.ditectrev.com, but also on all the distribution channels we publish on.