Introduction: This workshop will be based on: Python - Miniconda - Conda - Pip
This is a custom Confluence template that is intended to be re-used in the creation of workshops presented by ARCC on the Wiki. All of the content in these sections is intended to be replaced by the author of the workshop. The first step in this style guide is to ensure that the the page is in wide mode to maximize the real estate for content when possible. The Title of the Page should be the same as the Title of the workshop and this section should include a quick intro to the topic, why it’s important for ARCC users, and what users should expect to get out of this workshop. Next should be a Table of Contents macro in vertical format. The Table is intended to be used as an agenda section for presenter mode as well as navigation for non-presenting viewing so that users can find the documentation and navigate to what they need to brush up on. Finally, at the end of each section, there should be a divider to indicate the separation of “slides”
| Table of Contents | ||
|---|---|---|
|
Headers and Sections
...
Code Examples
...
Two Column Tables are nice ways to separate content/ Background info along with a code example on the same “Slide”. Please notice the table width. This should stop scroll bars from appearing
Bullets are nice to include for distinct points
yep
they
sure
are
This is 14 lines
...
| Code Block |
|---|
Please use the "code snippet" in the + button when creating code examples.
Also please do not go past the width of the table.
This is to prevent scroll bars appearing This is the Max number of code lines to show an example
|
Straight Code - No context
| Code Block |
|---|
Limit to 16 lines in the example. This is the end |
Same Thing With Images
...
Two Column Tables are nice ways to separate content/ Background info along with an image example on the same “Slide”. Please notice the table width. This should stop scroll bars from appearing
Bullets are nice to include for distinct points
yep
they
sure
are
This is 14 lines
...
...
Alternatively No Table
...
Finally The End
...
Link to Previous sub-module or Home Module
...
discuss how the various Python related tools work together on the cluster and introduce a series of best practices for managing these environments.
Course Goals:
Understand where pip installs packages within a user’s home folder with respect to different versions of Python.
Understand how to use pip to install a package within a conda environment.
Demonstrate how to create a conda environment, with pip installs, that can be shared across a project.
Demonstrate creating a module file to load a conda/python environment.
Demonstrate extending a conda environment to act as a kernel within the Jupyter service.
Suggested Best Practices.
...
| Warning |
|---|
This is not a workshop on learning the Python language, but on using Python, Pip and Conda explicitly on the ARCC clusters (not on desktops). Users should be familiar with Python, using pip, and creating conda environments. |
| Note |
|---|
Notes:
|
...
Sections
Python Pip Installs on the Cluster: Understand where pip installs packages within a user’s home folder with respect to different versions of Python.
Pip Install within a Conda Environment: Understand how Conda’s pip works with a User’s Python pip package Installs.
Create a Shared TensorFlow Conda Environment: General process for creating and sharing a conda environment under a project.
Create a Module File to Load Your Conda Environment: Demonstrate creating a module file to load a Conda environment.
Extend Conda Environment to Jupyter Kernel: Demonstrate extending a Python related conda environment in to Juypter kernel.
Jupyter Python Packages and Issues: When using Jupyter how are python packages managed?
Conda and Pip Environments and Reproducibility: Introduce ideas and practices to assist in managing the reproducibility of environments created using Conda and Pip.
Python, Conda and Pip: Suggested Best Practices: Suggest best practices bringing together concepts from the workshop.
Python, Conda and Pip: Exercise: Provide an exercise to work through that puts together the various concepts covered within this workshop.
Python, Conda and Pip: Summary: Summary of this workshop.
...
All Trainings | Next |