audit-labs/tutorials
Learn how to perform data analysis, scripting, automation, and more!
clone: git clone https://gitbay.org/audit-labs/tutorials.git
54aaa07bf2603bff25047ce786e9fa4783e395e6
unsigned
author: christian <hello@cleberg.net> · 2026-01-27T22:15:56Z
README.md | 135 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 135 insertions(+) new file mode 100644 @@ -0,0 +1,135 @@ +# audit-labs/tutorials + +Learn how to perform data analysis, scripting, automation, and more using reproducible Jupyter Notebooks. + +[](https://mybinder.org/v2/gh/audit-labs/tutorials/HEAD) +[]() +[]() + +Table of contents +- [Project overview](#project-overview) +- [Who this is for](#who-this-is-for) +- [What's included](#whats-included) +- [Getting started](#getting-started) + - [Prerequisites](#prerequisites) + - [Quick start — using Binder (no local setup)](#quick-start---using-binder-no-local-setup) + - [Run locally (recommended)](#run-locally-recommended) + - [Run in Google Colab](#run-in-google-colab) + - [Run with Docker](#run-with-docker) + - [Run headless / export notebooks](#run-headless--export-notebooks) +- [Best practices for notebooks](#best-practices-for-notebooks) +- [Contributing](#contributing) +- [License & Code of Conduct](#license--code-of-conduct) +- [Contact / Support](#contact--support) + +## Project overview +This repository contains interactive tutorials and example notebooks designed to teach practical skills in data analysis, scripting, automation, and related topics using Jupyter Notebooks. Each notebook demonstrates concepts through hands-on examples so you can follow along and adapt the patterns to your own projects. + +## Who this is for +- Data analysts and engineers learning reproducible workflows. +- Developers who want to prototype automation or analysis in notebooks. +- Students and instructors seeking ready-made examples for teaching. + +## What's included +- A collection of Jupyter Notebook tutorials (look in the repository root or `notebooks/` folder for .ipynb files). +- Guidance and examples that demonstrate common patterns for data ingestion, transformation, visualization, and basic automation. + +(If your repo has a specific folder layout or important notebooks, consider adding a short list here with links to the most important notebooks.) + +## Getting started + +### Prerequisites +- Python 3.10+ (3.10 recommended) +- Git (to clone the repo) +- JupyterLab or Jupyter Notebook (for local development) + +Optional: +- Conda (recommended for reproducible environments) +- Docker (for containerized runs) + +This repository is licensed under the GNU General Public License v3.0 (GPL-3.0). See the included LICENSE file for details. + +### Quick start — using Binder (no local setup) +To run the notebooks in your browser with no local install, use Binder: + +- Launch Binder: https://mybinder.org/v2/gh/audit-labs/tutorials/HEAD + +Binder will respect `environment.yml` or `requirements.txt` if present; this repository includes an `environment.yml` to produce a reproducible environment. + +### Run locally (recommended) + +1. Clone the repository + ```bash + git clone https://github.com/audit-labs/tutorials.git + cd tutorials + ``` + +2. Create and activate an environment + + Using conda (recommended): + ```bash + conda env create -f environment.yml + conda activate audit-tutorials + ``` + + Or with pip and virtualenv: + ```bash + python -m venv venv + source venv/bin/activate # macOS / Linux + venv\Scripts\activate # Windows + pip install --upgrade pip + pip install -r requirements.txt + ``` + +3. Install JupyterLab (if not already) + ```bash + pip install jupyterlab + jupyter lab + ``` + Or run the classic notebook server: + ```bash + jupyter notebook + ``` + +4. Open the notebooks in the browser and follow the cells. + +### Run in Google Colab +To open a notebook in Colab: +- Navigate to the notebook file on GitHub, then use "Open in Colab" or open via: + https://colab.research.google.com/github/audit-labs/tutorials/blob/HEAD/path/to/notebook.ipynb +- Colab will run in the cloud; you may need to pip-install extra dependencies at the top of the notebook using `!pip install ...`. + +### Run with Docker +You can run the notebooks inside a Docker container using Jupyter's base images: +``` +docker run -p 8888:8888 -v "$(pwd)":/home/jovyan/work jupyter/base-notebook:latest +``` +Then open `http://localhost:8888` and navigate to `work/`. + +### Run headless / export notebooks +To execute notebooks and export them programmatically: +``` +pip install nbconvert nbclient +jupyter nbconvert --to html --execute path/to/notebook.ipynb +``` +This is useful for CI pipelines and automated report generation. + +## Best practices for notebooks +- Keep notebooks focused: one concept or analysis per notebook. +- Include a short README or top-level markdown cell describing purpose and inputs. +- Avoid long-running data downloads inside notebooks—prefer referencing local sample data or scripts. +- Use version control: commit notebooks regularly. Consider tools like `nbstripout` or `nbdime` to manage diffs. +- Parametrize notebooks for reproducibility (e.g., use papermill for parameterized runs). + +## Contributing +See CONTRIBUTING.md for contribution guidelines. + +## License & Code of Conduct +This project is licensed under the GNU General Public License v3.0 (GPL-3.0). See [LICENSE](./LICENSE) for details. + +Please review CODEOFCONDUCT.md for expected behavior when contributing. + +## Contact / Support +For questions or help, open an issue in this repository or contact the maintainers listed in the repository settings. + +--- \ No newline at end of file