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This repository contains sample pipelines developed using Ploomber.
Note: We recommend you to go through the first tutorial to learn the basics of Ploomber.
Use Colab:
Or run locally:
pip install ploomber
# list examples
ploomber examples
# download example with name
ploomber examples --name {name}
# example
ploomber examples --name templates/mlflowEach example contains a README.md file that describes it; a README.ipynb is also available with the same contents but in Jupyter notebook format and with command outputs. In addition, files for pip (requirements.txt) and conda (environment.yml) are provided for local execution.
Starting points for common use cases. Use them to ramp up a project quickly.
{% for e in templates %}
{{e.idx}}. {{e.path}} {{e.description}}
{% endfor %}
Short and to-the-point examples showing how to use a specific feature.
{% for e in cookbook %}
{{e.idx}}. {{e.path}} {{e.description}}
{% endfor %}
In-depth tutorials for learning. These are part of the documentation.
{% for e in guides %}
{{e.idx}}. {{e.path}} {{e.description}}
{% endfor %}
The simplest way to get started with Ploomber is via the Spec API, which allows you to describe pipelines using a pipeline.yaml file, most examples on this repository use the Spec API. However, if you want more flexibility, you may write pipelines with Python.
The templates/python-api/ directory contains a project written using the Python API. And the python-api-examples/ includes some tutorials and more examples.
In Ploomber 0.21, we introduced a simplified API to write pipelines in a single Jupyter notebook (or .py) file. This is a great option for small projects.
You can find the examples in the micro-pipelines/ directory.