https://github.com/dnyfzr/docs

📚 Learning Resources
https://github.com/dnyfzr/docs

data-engineering devops software-engineering

Last synced: 5 days ago
JSON representation

📚 Learning Resources

• Host: GitHub
• URL: https://github.com/dnyfzr/docs
• Owner: DNYFZR
• Created: 2022-03-14T15:13:57.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-05-07T12:51:04.000Z (6 months ago)
• Last Synced: 2024-05-07T13:43:24.105Z (6 months ago)
• Topics: data-engineering, devops, software-engineering
• Homepage: https://dnyfzr.github.io/docs/
• Size: 6.41 MB
• Stars: 8
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md

Awesome Lists containing this project

README

        
 📚 Developer Resources 





**Page** | **Content**

-- | --

[Software Development](docs/pages/software_development.md) | Links to Python, Java, Scala, R, Git, CLI, RegEx and many other resources

[Apache](docs/languages/apache.md) | Links to Apache tooling

[JVM](docs/languages/jvm.md) | Guides for learning JVM languages

[Python](docs/languages/python.md) | Python study resources

[Rstats](docs/languages/rstats.md) | Intro / adv. R materials

[Rust](docs/languages/rust.md) | Learning resources for Rust

[SQL](docs/languages/sql.md) | SQL & database resources

[Azure](docs/cloud/azure.md) | Azure cloud blogs, links and tools

[Data Engineering](docs/pages/data_engineering.md) | Links to resources to learn Data & Analytics Engineering tools, methods and worlflows

[Machine Learning](docs/pages/machine_learning.md) | Links to resources for learning data analytics, data science and machine learning

[Data Sources](docs/pages/data_cave.md) | API & dataset resources grouped by topic

[Cheat Sheet Library](docs/pages/cheat_sheets.md) | A range of cheat sheets for Python, SQL, Data Science & Visual Studio Code

This project has been build using mkdocs & the mkdocs-material theme.

- The site is configured using the [mkdocs.yml](/mkdocs.yml)

- Site pages are managed via the [docs](/docs/) directory

- Build is managed via [GitHub Actions](https://github.com/DNYFZR/Resources/actions)




Python has been used to create a development environment, and to install the mkdocs packages within it :

````ps1

# Set up & install

python -m venv 

cd /scripts

./activate

python -m pip install -U pip

python -m pip install mkdocs mkdocs-material

# Setup project

cd ../../

mkdocs new 

# Launch mkdocs local server 

cd 

mkdocs serve

````