Reproducible Research Template

This folder contains a basic template file and folder structure for reproducible resreach in Python. It is based on [https://github.com/airqo-platform/AirQo-experiments/tree/master/reproducibility-template]. It consists of the following folders and files:

data/

raw/

Mandatory

• Must contain eiter the raw data used for this research, or a reference to that data if it cannot be uploaded (e.g. it's too big or it's confidential).

clean/

Optional

• If the analysis is not performed directly on raw data, this folder should contain "clean" (munged, combined) data.

models/

Optional

• If the analysis includes a model output files, e.g. a .pkl of a neural network, store them here.

notebooks/

Optional

• Must contain Jupyer notebooks.
• There must (at a minimum) be clear seperation of function between data download, data munging and analysis. In the case of Jupyter notebooks these may be seperate headings, for scripts they may be seperate files.

scripts/

Optional

• Must contain Python scripts.
• There must (at a minimum) be clear seperation of function between data download, data munging and analysis. In the case of Jupyter notebooks these may be seperate headings, for scripts they may be seperate files.
• ToDo: Structure for tests and Python modules.

LICENSE

Mandatory

• If this folder is not in a repository which already has a license, an appropriate license is essential.

readme.md

Mandatory

• Instructions to run the code, for example:

Clone this repository:

git clone https://github.com/airqo-platform/AirQo-experiments.git

Change directory to this folder:

cd reproducibility-template

Create and activate clean conda enviroment:

conda create --force -n reproducibility-template python=3.6
conda activate reproducibility-template

Install requirements:

pip install -r requirements.txt

Execute code:

python code/01_get_data.py
python code/02_clean_data.py
python code/03_analysis.py

requirements.txt

This file must list the package requirements needed to execute the code in code/.

Substitute environment.yml for requirements.txt, if appropriate. If using Jupyter notebooks, instructions may be better embedded within the notebook file.