Mentorship Programme Notes: Template firstname lastname
===

###### tags: `mentorship`

This is a collaborative document to keep track of progress during the mentorship programme.

:::info
- **Call time**: 10:30AM Eastern Time, Monday
- **Project name**: #8631 and #8616
- **Mentees**: Isaias Ruiz
- **Mentor(s)**: Damir Temir
- **Call joining link**: Discord
:::

## References
The sktime mentorship programme is inspired by the [The Turing Way](https://book.the-turing-way.org/) project and [Open Life Science](https://openlifesci.org) programme under a CC BY 4.0, Open Life Science (OLS-2), 2020 license.

**Contents**

[TOC]

## Week 0

- For reference: sktime's [mentorship programme call for applications](https://www.sktime.net/en/latest/get_involved/mentoring.html)
- Get started with HackMD using this short guide: https://hackmd.io/@openlifescience/OLS-HackMD-guide
- Please read our [Code of Conduct](https://www.sktime.net/en/latest/get_involved/code_of_conduct.html)
- [guide for getting started as an sktime contributor](https://www.sktime.net/en/latest/get_involved/contributing.html#contributing)
- [current list of project ideas](https://github.com/sktime/mentoring/blob/main/internships/projects_2023.md)
- Check out sktime's [development roadmap](https://github.com/sktime/sktime/issues/228)

**Preferred time and days provided by the mentor and mentee**

Please indicate your preferred day/time for your regular call:

* tbd

### Prep work for week 1

**Mentees will:**

1. Read https://ideas.ted.com/are-you-mentorable/
2. Set 1-2 personal development goals for yourself:
...
3. State how your mentors can best support you in your contribution to sktime (e.g., providing code reviews, share useful resources, explain ML concepts):
...
4. Open an issue on the [sktime/mentoring](https://github.com/sktime/mentoring/issues) repo. This can be updated during the mentorship program.

## Week 1 - 8/4

### Agenda
* discussing aim of mentoring
* how sktime mentoring programme works
* discussing project to work on & next steps
* developer set-up

### Notes
I feel that I need more guidance in some aspects of sktime. I don't usually seek for help unless I really stuck, but I cannot simply refuse when someone is open to help me.

suggestions of good first issues:

* try to reproduce bugs
* https://github.com/orgs/sktime/projects/6
* pick any and try to run the code of others. Report on operating system, python version, and package versions; and whether you can run the code
* optional: trying to debug
* software sided: adding more estimators
* pick one https://github.com/sktime/sktime/issues/7941
* https://github.com/sktime/sktime/issues/7885
* https://github.com/sktime/sktime/issues/6700
* https://github.com/sktime/sktime/issues/6660
* https://github.com/sktime/sktime/issues/5382
* picking 6153, try to diagnose failures
* run `check_estimator` and report what you find

### development goals
Improve more about send PR's correctly.

### project goals
Implement _evaluate_by_index into a metric class.

## Week 2 - 8/11

### work done
N/A
### Agenda
* Finish Issues #3429 and #6153
* Keep working on debbuging projects when I finish to the both issues above.
* Be more present in PR's
* Be concise about my blockers and errors in the future.

### Questions

### Notes
I'm going to practice debbuging frequently because some of my errors during my commits are involved that. I make sure to at least do the list of issues above to amend the lack of activity that I did the last week. Also I'm planning to ask every day starting Monday to leave the fear to ask for any help even if is for a small issue.

### Actions, short-term goals

* Address all of Franz's comments.
Run tests reliably on your local sktime environment. Do not put Pull Requests out until all tests are passing.

* Ask frequently in Dev-chat channel to be more reliable.

* If tests or code is not working, after investing one QUALITY hour of time into figuring it out, let Damir or sktime maintainers know through Discord
At standups, be detailed in your updates. What you have done, what you are planning to do, and what problems you may be experiencing right now.

* If you use AI, confirm that its output is correct. Do not post Pull Request with pure AI answer. Always know what it's giving you and confirm it is working.
Invest 20 hours of work as determined by the agreement.

* If you cannot attend a meeting, please give heads up to skime team and Damir. Give update in that message.

## Week 3 - 8/18

### work done
PR #8631

### Agenda
* Review feedback on PR #8631 and plan next steps for revisions.
* Suggestions about my performance and reliability working on issues.

### Questions

### Notes
* Learned more about sktime’s testing framework and how to use check_estimator effectively for metric classes.
* Recognized the importance of writing modular, reusable code that aligns with the project’s long-term architecture.

### Actions, short-term goals

* Continue logging ~5–6 hours/week toward the
20-hour commitment.
* Schedule a brief sync with Damir if stuck for more than 1 hour on a technical issue.
* How can I reproduce test_deep_estimator_full locally to debug it?
* Are there any special considerations when running deep learning estimators in check_estimator?

## Week 3 - 8/25

### work done
n/a

### Agenda
* Some advices and tutoring about how to test property in uv and create a good virtual environment.
* Suggestions about my performance and reliability working on issues.

### Questions

In case that I'm not going anywhere in this issue or still have some struggles due to my vscode, could I change to another issue?

### Notes
* Learned more about sktime’s testing framework and how to use check_estimator effectively for metric classes.
* Recognized the importance of writing modular, reusable code that aligns with the project’s long-term architecture.

### Actions, short-term goals

* Continue logging ~5–6 hours/week toward the
20-hour commitment.
* Schedule a brief sync with Damir if stuck for more than 1 hour on a technical issue.
* How can I reproduce test_deep_estimator_full locally to debug it?
* Are there any special considerations when running deep learning estimators in check_estimator?

## Week 3 - 9/2

### work done
n/a

### Agenda
* feedback session
* check #8616 if its well implemented.
* Some advices of how was my performing these past weeks so far.
* Suggestions about future issues in any case that I keep work on more sktime issues.

### Questions

How will be my next issues in case that I keep working on sktime?

### Notes

* Recognized the importance of writing modular, reusable code that aligns with the project’s long-term architecture.

Isaias feedback

* good interaction
* sometimes PR were waiting for review

FK feedback

Overall: not engaged well at the start but this improved later.

I saw that you were able to make good contributions when you put your mind to something - engagement was the limiting factor.

Engagement was patchy, needed a lot of push on side of mentors - but improved towards the end.

Took weeks until you even engaged with the mentoring notebook, so we only had a very short time of actual engagement.

You could have gotten significantly more out of the mentoring if you would have engaged from the start.

### Actions, short-term goals
* Finish the current PR's that I still working on.
* Be thankful to the rest of the dev staff that helped me these weeks.