Welcome to the Brane Tutorials repository! This repository contains step-by-step tutorials, source codes, and video recordings to help you learn and master Brane—a framework for creating and managing workflows.
Each tutorial in this repository is designed to guide you through a specific feature of Brane, starting from basic workflows to more advanced concepts like inter-package communication. Whether you're new to Brane or looking to deepen your knowledge, you'll find valuable resources here.
| Tutorial | Description |
|---|---|
| 1. Hello World | Learn how to create and run your first "Hello World" workflow in Brane. |
| 2. First Package | Discover how to create your first Brane package with Python and use it in a workflow. |
| 3. Inter-Package Communication | Explore how to connect multiple Brane packages to pass information seamlessly between them. |
To get started with the tutorials:
- Clone this repository to your local machine:
git clone https://github.com/soreana/brane-tutorials.git - Navigate to the tutorial you're interested in and follow the instructions in its
README.md.
Below is a list of planned future tutorials, covering advanced topics to enhance your Brane skills:
| Tutorial | Concept | Skills Covered |
|---|---|---|
| Handling Inputs and Outputs | Build a package that takes user input, processes it, and returns an output. Example: Factorial calculation. | Adding input parameters, modifying Python code for dynamic inputs, testing with various inputs. |
| Data Processing Workflow | Create a package for data extraction, transformation, and loading (ETL). Example: Scraping and processing data. | Handling dependencies like requests or pandas, defining multiple tasks, structuring modular code. |
| Package with External Libraries | Build a package using external Python libraries. Example: Generating plots with Matplotlib or Seaborn. | Specifying library dependencies in container.yml, including complex Python scripts, visualizing results. |
| Combining Packages with APIs | Interact with external APIs in a package. Example: Fetching weather data and displaying forecasts. | Adding API calls, handling keys securely, parsing and using API responses. |
| Machine Learning Workflow | Create a package for ML tasks like training models or making predictions. Example: Housing price predictions. | Including ML libraries like Scikit-learn, working with model files, combining ML with data processing packages. |
If you have any feedback or ideas for additional tutorials, please feel free to open an issue or submit a pull request. Contributions are always welcome!
Happy learning, and enjoy exploring Brane!