Good first issues & getting started, for new contributors

[fkiraly]

A number of good issues to start working on as a new contributor.
Contributions to documentation are especially appreciated.

getting started with contributions

1. Say hello on Discord and get set up for development, see instructions in the developer guide
2. Pick a “good first issue” to work on, see a collection in this summary issue, or from this list
   suggestion: pick something small with simple content to learn the “process”
3. Feel free to attend the regular community collab sessions or one of the topic specific stand-ups and tech sessions (see schedule on discord)
4. Once your first PR is merged and you’ve seen how things work, think about your regular time commitment. Optionally, continue attending the Friday community collaboration sessions and stand-ups; or, optionally, apply for mentoring

introductory and user testing

• work through the sktime tutorials and record feedback, you can post it in this issue [DOC] Feedback thread on tutorial notebooks #1447
• work through user testing sheets for forecasting or time series classification, record feedback and send us your user testing sheet with code (e.g., attach to this issue)
• open an issue with a time series related algorithm that you would like to see implemented or interfaced in sktime
• work through the installation instructions to install a development version of sktime. Record carefully things that are unclear or don't work as described, return the full feedback to us (e.g., in an issue).

contributors new to open source

• documentation: many code files are missing module and class/function docstrings. Pick a file and start adding these. A good starting point are estimator algorithms, these should follow the general documentation style outlined in [DOC] Completing estimator class docstrings #1148 or the extension templates. If you start, post the name of the estimator you are working on in [DOC] Completing estimator class docstrings #1148; when you open a PR, refer to the issue.
• documentation: many code files are missing examples. Pick a file and start adding these, here is the umbrella issue: [ENH] add at least one usage example to docstrings of estimators #4264

NOTE: #1148 and #932 are closed, but there are still modules without good docstrings. They are just no longer tracked by the issue, which covered the priority items only. So, feel free to go through the code base and help improve docstrings!

small-to-medium documentation and technical writing tasks

• the tutorial for time series classification should be re-factored, in the style of the forecasting tutorial
• extension templates for time series regression and time series annotation should be written. The current extension templates can be used as an extension template template.

small-to-medium python/coding tasks

• current open small tasks with a "recipe": [ENH] ensure that all estimators have two test parameter sets #3429
• pick a performance metric and implement the _evaluate_by_index method, recipe: [ENH] implement efficient _evaluate_by_index for forecast performance metrics #4304
• pick an unverified bug from the bugfixing board: https://github.com/sktime/sktime/projects/18 and try to reproduce it. Post operating system, python version and (if relevant) package versions, and whether you can yes/no. Investigate further if the bug looks simple - but note that bugs can be anywhere between easy to very difficult to track down.
• Pick an algorithm to implement or interface, according to the extension templates. Possible choices are forecasters (univariate or multivariate), time series classifiers, time series regressors, annotators, distances, kernels - these can be existing feature requests, or new suggestions. We currently do not recommend transformers as they undergo refactoring.

mid to longer term tasks

For contributing across a period of weeks or months, consider joining one of the major workstreams and weekly stand-ups on Fridays, or work on a mini-project.

Active workstreams are in the "workstream" group of channels, on discord.

Project ideas are listed here:
https://github.com/sktime/mentoring/blob/main/internships/projects_2024.md

challenging tasks

✨ Your time to shine! ✨
Talk to a core dev before starting with these.

Ideas for more difficult tasks are listed on the current roadmap:
#4691

[mloning]

Closing this now but perhaps we should rework this into a template for sprint planning, some of the items will be relevant for future sprints too?

[fkiraly]

Why not just open it and remove the scipy reference? Still good for pinning, no?

[gepitis]

Hi, thanks for the list of first issues! Where can I send my feedback on the tutorials?

[aiwalter]

Hi @gepitis ,
you could open a new issue with ideas of improvement that you have in mind

[fkiraly]

Where can I send my feedback on the tutorials?

I just opened an issue here
#1447
thanks for any feedback!

[eyjo]

The links for the sktime website are for the .org domain.

[fkiraly]

thanks for pointing out - the domain got swooped up by third parties, it's now on sktime.net - fixed all the links!

[priyakumari02]

Hello @fkiraly , I want to contribute to GSOC'24 , So this org caught my eye.I tried to join the discord channel , but It is showing invalid link

[fkiraly]

Thanks for the note, @priyakumari02!
The discord invite and the link to projects have been updated to 2024.

[iaryangoyal]

hi @fkiraly , I want to contribute to GSOC'24 , can you spot some good first issue?

[fkiraly]

Welcome to sktime! You seem to be new to open source, how about this one?
#3429

[MMTrooper]

Hello @fkiraly, I am pretty new to open source and maybe late to the participating. I would still like to know what are some issues you'd recommend I tackle?

[fkiraly]

I am pretty new to open source and maybe late to the participating.

Welcome, and rest assured that it is never too late!

How about #3429 as a starter? It is relatively simple python-wise, but allows you to practice open source workflows, git, PR, reviews, etc.

[MMTrooper]

I am pretty new to open source and maybe late to the participating.

Welcome, and rest assured that it is never too late!

How about #3429 as a starter? It is relatively simple python-wise, but allows you to practice open source workflows, git, PR, reviews, etc.

On it

[MihirsinhChauhan]

I'm interested to working on refactoring of tutorial for Time series classification.
Any suggestions for me

[fkiraly]

@MihirsinhChauhan, thanks! Truth is, there already have been gradual updates over time, so what would be helpful:

• work through the tutorial and check whether all is clear
  • any suggestions for improvement, record in a new issue
  • we can then discuss and turn into actions
• 2nd step or alt option: check more recent tutorials from conferences/workshops, on new features, in the github.com/sktime organization. See whether the new content from there could be distributed across the existing notebooks, or makes sense to add as a new notebook.

[tunglinwood]

Hay @fkiraly, I would like to contribute to sktime for my GSOC as well.

1. Could you help to assign any Good First Issue to me? I have little Python coding experience. But I have walked through the example notebooks on Binder.
2. I work for 8hrs/day throughout workdays in GMT+8, Taipei. So you can consider me a full-time contributor.
3. I would like to work extensively with other harder tasks if desired, of course, up to your assignment.

Thank you so much.

P.s. I implemented the command line pydocstyle sktime/ --config=setup.cfg | grep ./ | cut -d ':' -f1 | uniq but nothing really comes into information of docstrings needed to be complete. Do I miss something here?

[sohamchatterjee50]

Hey @fkiraly
I would love to cotribute to this project. I have professional exeperience as a Fraud Analyst at a FinTech company and as an Applied Scientist at Amazon. Currently I am pursuing my Masters in AI from University of Amsterdam.

1. I can work for 16 hrs per week.
2. We have some research courses on Deep Learning and Foundation Models.

I would love to contribute to the Foundation Models project, which will be an enriching reseach experience for me.

[fkiraly]

Welcome to sktime, @tunglinwood, @sohamchatterjee50.
Consider applying for mentoring: https://github.com/sktime/mentoring

Also, you can look on discord in the workstream channels for your preferred topics.

[fkiraly]

I implemented the command line pydocstyle sktime/ --config=setup.cfg | grep ./ | cut -d ':' -f1 | uniq but nothing really comes into information of docstrings needed to be complete. Do I miss something here?

@tunglinwood, not sure, can you kindly explain what you are trying to do?