https://github.com/noahgift/myrepo

continuous integration rep
https://github.com/noahgift/myrepo

build circleci continuous-integration data-science jupyter-notebook nbval pytest python testing

Last synced: 3 days ago
JSON representation

continuous integration rep

• Host: GitHub
• URL: https://github.com/noahgift/myrepo
• Owner: noahgift
• Created: 2017-11-28T16:25:34.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2025-01-10T22:57:24.000Z (about 1 month ago)
• Last Synced: 2025-02-10T15:09:38.142Z (10 days ago)
• Topics: build, circleci, continuous-integration, data-science, jupyter-notebook, nbval, pytest, python, testing
• Language: Jupyter Notebook
• Size: 43.9 KB
• Stars: 50
• Watchers: 7
• Forks: 114
• Open Issues: 2
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
## 🎓 Pragmatic AI Labs | Join 1M+ ML Engineers

### 🔥 Hot Course Offers:

* 🤖 [Master GenAI Engineering](https://ds500.paiml.com/learn/course/0bbb5/) - Build Production AI Systems

* 🦀 [Learn Professional Rust](https://ds500.paiml.com/learn/course/g6u1k/) - Industry-Grade Development

* 📊 [AWS AI & Analytics](https://ds500.paiml.com/learn/course/31si1/) - Scale Your ML in Cloud

* ⚡ [Production GenAI on AWS](https://ds500.paiml.com/learn/course/ehks1/) - Deploy at Enterprise Scale

* 🛠️ [Rust DevOps Mastery](https://ds500.paiml.com/learn/course/ex8eu/) - Automate Everything

### 🚀 Level Up Your Career:

* 💼 [Production ML Program](https://paiml.com) - Complete MLOps & Cloud Mastery

* 🎯 [Start Learning Now](https://ds500.paiml.com) - Fast-Track Your ML Career

* 🏢 Trusted by Fortune 500 Teams

Learn end-to-end ML engineering from industry veterans at [PAIML.COM](https://paiml.com)

# myrepo

[![CircleCI](https://circleci.com/gh/noahgift/myrepo.svg?style=svg)](https://circleci.com/gh/noahgift/myrepo)

This is an example repo of a how to create a Data Science focused Python project.

There is a screencast on this project setup here:

[![Data Science Build Project](http://img.youtube.com/vi/xYX7n5bZw-w/0.jpg)](http://www.youtube.com/watch?v=xYX7n5bZw-w)

This video does a full breakdown of how to use and create a Makefile:

[![How to use Pylint, Nbval and Coverage to test Jupyter Notebooks](https://img.youtube.com/vi/ABaPWYF_Tl8/0.jpg)](https://www.youtube.com/watch?v=ABaPWYF_Tl8)

A few things to do with this project:

* install software: ```make install```

* test code: ```make test```

* lint code: ```make lint```

* run commandline tool:  

```bash

./cli.py --name john 

john-apple

```

* run jupyter notebook:

```

jupyter notebook notebook.ipynb

```

* test jupyter notebook:

```

python -m pytest --nbval notebook.ipynb

```

## Further Information on this topic can be found here:  https://github.com/noahgift/functional_intro_to_python