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A repository for submitting completed exercises from the UN-OG-Training material

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UN-OG-Training-Submit

This is repository is for users of the United National OG-Core Overlapping Generations Model Training (https://eapd-drb.github.io/UN-OG-Training/) to submit their assignments. This repository can also serve as a platform for asking questions about the training material and exercises.

How to submit your exercises

  1. Fork and clone this repository (https://github.com/EAPD-DRB/UN-OG-Training-Submit). See the Git and GitHub tutorial section of the training material for more on forking and cloning.
  2. In a branch on your fork of the repository, create a subfolder in the appropriate directory under the ./submissions/ folder uwith the name of your GitHub handle. As an example, you can find a submission from Richard Evans using his GitHub handle (rickecon) as the directory name. Note that this example is in the Philippines subfolder (./submissions/PHL/rickecon/). Please put your submission in the appropriate subfolder of the ./submissions/folder.
  3. In the directory with the name of your GitHub handle, include your completed exercises as either Jupyter notebooks or Python scripts in subfolders of the Chapter of the material from which the exercises came. For example, in the submission by Richard Evans (./submissions/PHL/rickecon), he has a subfolder named Ch1_IntroToPython. In that folder is a Jupyter notebook and Python scripts representing his answers to the 15 exercises from this chapter--problems 1-8 from the BYU ACME "Introduction to Python" chapter and problems 1-7 from the BYU ACME "Unix Shell 1: Introduction" chapter. We recommend you use a Jupyter notebook as much as possible to give solutions to the exercises. For these notebooks, you may want to use the Conda environment un-og-training-probs found in the environment_probs.yml conda environment specification markdown file. You can create this conda environment by navigating to the UN-OG-Training repository directory on your local machine and typing: conda env create -f environment_probs.yml.
  4. Submit your exercises in this format as a pull request to this repository. We will merge these submissions in, and they will be visible to us and to anyone else using the UN OG Training material.

The goal

Our hope and goal is that this repository will become the forum through which users of the UN OG Training material will interact and ask questions and improve the content.

  • We encourage users to ask questions about the material by posting an Issue in the Issues tab. If you want a particular user to participate in answering the question, you can use the "@" sign. We encourage users of this site to first ask questions of their colleague's using the material and to work on the answers together. The maintainers of this materials will answering harder questions that the users were not able to solve on their own.
  • We enourage larger discussions of more general interest to be made as threads in the Discussions tab.

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