README: About pyOpenSci peer review metrics

This is a dashboard created using mystmd . Myst-md is a community developed tool that makes it easier for scientists to create fully reproducible (and interactive) workflows and reports that are easily shared.

How to use this repository

To work with this repository do the following:

1. Create & activate a fresh Python environment.

mamba env create -f environment.yml
mamba activate pyos-myst

2. Create a .env file

Copy the .env-default file in this repository, and rename it to ".env". This is the file in which you'll paste your GitHub access token.

3. Configure your GitHub access token

This dashboard leverages pyOpenSci's package pyosMeta to obtain contributor and peer review metadata. To use this package, the user needs to supply a GitHub access token, which can be obtained from their GitHub account. Click on your profile image and navigate to "Settings", and then "Developer Settings".

Create a new fine-grained personal access token, adding a name, expiration, description, and ensure the "Repository Access" is set to "Public Repositories (read-only)". No other configuration needed. At the bottom of the page, click "Generate token".

Once the token has been generated, copy the token string and paste it into the ".env" file next to GITHUB_TOKEN=. You are now configured to work with the information harvested using pyosMeta.

4. Install nodejs

mamba install -c conda-forge "nodejs>=20,<21" mystmd

3. Install required packages

Inside of the pyos-myst environment, install required packages.

mamba install -c conda-forge "nodejs>=20,<21" mystmd
pip install -r requirements.txt

5. Local preview

Finally preview this locally:

Run myst to create and run a local live server that will update as you update your code / workflows.

To build the html files and run code use:

myst build --execute to execute code`

To build a local server that runs and executes code: myst start --execute

When i tried to use md files to executive code (which is preferred) it couldn't find the kernel

🪐 Jupyter server did not start Unable to instantiate connection to Jupyter Server

If we use juyter then we want to ensure

jupyterlab_myst is installed to be able to use eval statements

myst start --execute to run and execute code.

To run - jupyterlab_myst

Environment

use the environment.yml file

>> myst

you will get:

Welcome to the MyST Markdown CLI!! 🎉 🚀

myst init walks you through creating a myst.yml file.

You can use myst to:

 - create interactive websites from markdown and Jupyter Notebooks 📈
 - build & export professional PDFs and Word documents 📄

Learn more about this CLI and MyST Markdown at: https://mystmd.org


✅ Project already initialized with config file: myst.yml
✅ Site already initialized with config file: myst.yml

? Would you like to run myst start now? (Y/n) y

📖 Built README.md in 32 ms.
📖 Built 03-leah.ipynb in 32 ms.
📚 Built 4 pages for project in 147 ms.


        ✨✨✨  Starting Book Theme  ✨✨✨



🔌 Server started on port 3000!  🥳 🎉


        👉  http://localhost:3000  👈

Build using Nox

You can use nox to build the dashboard locally. Nox will create an environment for you with all needed dependencies.

To start, install nox:

Using pip:

python -m pip install nox

or pipx for global install:

pipx install nox

Build a static html website

To build the html version of the dashboard use

nox -s build

Build a live local server dashboard

To build the dashboard as a local server that will update as you update the files use:

nox -s serve

One a mac you can use ctrl + d to stop a live server.

Contributors ✨

Thanks goes to these wonderful people (emoji key):

kaiyamag 💻 👀

Elise Hinman 💻 👀

This project follows the all-contributors specification. Contributions of any kind welcome!