The document discusses using a Python pipeline pattern for continuous integration and delivery. It recommends writing pipeline code using best practices from software engineering, such as shared library code, abstraction, testing, and established principles like DRY, KISS, and avoiding NIH. Example patterns are provided, such as DockerAccess and PythonBuild, to encapsulate common pipeline tasks.

1. JP Sullivan
Pied Piper Picked a
Python Pipeline Pattern
Released April 2019

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I need a pipeline
https://jenkins.io/images/post-
images/blueocean/pipeline-run.png

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https://jenkins.io/doc/tutorials/build-a-python-app-with-
pyinstaller/
Sample Code and Examples from:

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Just write it, the
steps are simple

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Now add a few
more repositories,
just copy the
pipeline I wrote

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Need to change
something, now I’ve
loads of changes to
make!

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Pipeline as Code –
apply Engineering to it

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Things to consider
• Shared Pipeline Library
• Access Objects
• Considered Abstractions
• TDD and Unit Testing

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Standard Principles
• Ensure you DRY
• Also, KISS
• Avoid NIH
• Ran out of acronyms
• Use standard
approaches where
possible
• Cyclomatic Complexity

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Example Patterns
• DockerAccess
• PyPiAccess
• ArtefactoryAccess
• PythonBuild
• PythonPublish
• JavaBuild
• JavaPublish

11. https://github.com/CiscoDevNet/es-logger