Our Slack Community Guidelines

Welcome to DataTalks.Club 🤗

Thank you for joining our community! We hope you’ll like it here.

DataTalks.Club is a place to talk, learn, discuss, and share. To make our discussion more organized, we need to follow community guidelines.

Table of contents:

Taking part in discussions

Be respectful and remember that there’s a human on the other side of the screen. We do not have our own code of conduct, but we follow the Python Software Foundation one. Please read the “Inappropriate Behavior” section.

Some examples of inappropriate behaviour:

  • Judging the question or the person asking the question (“this is a stupid questions and everyone who can read docs knows the answer”)
  • Soliciting any kind of personal information (such as marital status, phone number, address, etc)
  • Continued one-on-one communication after requests to cease

Use threads. They help to keep the discussions more organized.

  • When asking a question, put everything in one message. If there’s a code snippet, put it inside the thread.
  • When asking multiple questions, break them down into multiple messages, so they could be answered in separate threads.
  • Avoid using the “also send to channel” feature unless it’s really necessary.

Do not double post — select the best channel for your message and post it only once.

If possible, avoid asking questions in DM. If you ask your question in a public channel, others will also benefit from the answers.


Default channels:

  • #announcements — for community-wide announcements
  • #general — for general discussions
  • #shameless-promotion — for promoting your work (see the promotion section for more information about promoting your work)

You can also join other channels:

  • #book-of-the-week – to talk about books with book authors (check the books page for more information)
  • #career – for career discussions (switching from one role to something data-related, being better at work, etc)
  • #datascience – for talking about data science, machine learning, algorithms, training process, and ml-related libraries
  • #engineering – for discussing the engineering aspects of data science: data engineering, ML engineering, MLOps, and so on
  • #events – to talk about events (not just our events, but events in other communities as well)
  • #process – how to organize our work
  • #projects – to discuss your side projects, find collaborators or do something together
  • #jobs – for jobs
  • #ai-memes-for-ai-peeps – for pictures and memes
  • #random – for chit-chat about pretty much anything

This is not a complete list of channels. To check the list of all the available channels, use this:

Try to use channels when possible. For example, instead of using #general for asking a question about machine learning, use #datascience.


Promoting your work is welcome — for both companies and individuals. We have a special channel for that — #shameless-promotion. You can use it for sharing social media links, blog posts, and anything else. Please don’t use other channels for that.

To promote your events, you can share them in #events, but #shameless-promotion is also fine.

We do not welcome unsolicited promotional messages in DM. Violating it will result in a ban without a warning. Instead, use the #shameless-promotion channel, and if somebody is interested in your services, they will reach out to you. If you get unsolicited promotional messages in DM, report it to Alexey Grigorev.

If you represent a company, indicate your affiliation if you suggest using your services when answering questions.


If you’re looking for colleagues, use the #jobs channel.

To make it easier for others to judge if a position is relevant for them, please mention:

  • City / Country
  • Relocation support
  • Possibility to work remotely

And don’t forget to include contact details and the link to the job description :)

Since we’re a data community, please make sure the positions are related to data or to software development.

Examples of relevant positions:

  • Data/product analyst
  • Data scientist
  • Machine learning engineer
  • Data engineer
  • Analytics engineer
  • Developer advocate
  • Software engineer / Python developer

Examples of not relevant positions:

  • Accountants and bookkeepers

Homework help

In general, we’d be happy to help with your homework, provided that you show genuine effort from your side and you are clear about the source of your question.

Copy-pasting an exercise and expecting others to jump in and solve it for you might be a long shot — don’t be surprised if nobody answers. To increase your chances of getting an answer, consult this answer from StackOverflow.

The same applies to interview take-home assignments. We’re happy to help, but be transparent about it.

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