-
-
Notifications
You must be signed in to change notification settings - Fork 125
Update setup instructions #342
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
base: main
Are you sure you want to change the base?
Conversation
Thank you!Thank you for your pull request 😃 🤖 This automated message can help you check the rendered files in your submission for clarity. If you have any questions, please feel free to open an issue in {sandpaper}. If you have files that automatically render output (e.g. R Markdown), then you should check for the following:
Rendered Changes🔍 Inspect the changes: https://github.com/datacarpentry/image-processing/compare/md-outputs..md-outputs-PR-342 The following changes were observed in the rendered markdown documents:
What does this mean?If you have source files that require output and figures to be generated (e.g. R Markdown), then it is important to make sure the generated figures and output are reproducible. This output provides a way for you to inspect the output in a diff-friendly manner so that it's easy to see the changes that occur due to new software versions or randomisation. ⏱️ Updated at 2025-04-06 09:10:41 +0000 |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Thanks @tobyhodges - looks good! I tried this out on my Windows laptop, and all worked well 😄 I left a few comments below.
@datacarpentry/image-processing-curriculum-maintainers - it would be great if you could try this out too, especially if you're on mac/linux
Co-authored-by: Kimberly Meechan <24316371+K-Meech@users.noreply.github.com>
Co-authored-by: Kimberly Meechan <24316371+K-Meech@users.noreply.github.com>
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Looks good to me - thanks @tobyhodges ! I'll leave this open for a while longer, in case the other maintainers have any input
@datacarpentry/image-processing-curriculum-maintainers - do feel free to add any further comments / suggestions, otherwise I'll merge this PR at the end of this week |
@@ -7,7 +7,7 @@ Before joining the workshop or following the lesson, please complete the data an | |||
|
|||
## Data | |||
|
|||
The example images used in this lesson are available on [FigShare](https://figshare.com/). | |||
The example images and a description of the Python environment used in this lesson are available on [FigShare](https://figshare.com/). | |||
To download the data, please visit [the dataset page for this workshop][figshare-data] | |||
and click the "Download all" button. | |||
Unzip the downloaded file, and save the contents as a folder called `data` somewhere you will easily find it again, |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Unzip the downloaded file, and save the contents as a folder called `data` somewhere you will easily find it again, | |
Unzip the downloaded file, and save the contents as a folder called `data` somewhere you will easily find it again, |
1. Download and install the latest [MiniForge distribution of Python](https://conda-forge.org/download/) for your operating system. | ||
If you already have a Python 3 setup that you are happy with, you can continue to use that (we recommend that you make sure your Python version is current). | ||
The next step assumes that `conda` is available to manage your Python environment. | ||
2. Setup an environment to work in during the lesson. |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
2. Setup an environment to work in during the lesson. | |
2. Set up an environment to work in during the lesson. |
opposed to the one with Python 2). If you wish to use an existing | ||
installation, be sure to upgrade your scikit-image to at least 0.19. | ||
You can upgrade to the latest scikit-image using the shell command that follows. | ||
1. Download and install the latest [MiniForge distribution of Python](https://conda-forge.org/download/) for your operating system. |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I'm not sure it's obvious that, on Unix-like platforms, you need to run
bash Miniforge3-$(uname)-$(uname -m).sh
from the terminal to install Miniforge... I would add a line about this. Is it obvious on Windows? I guess so, if you need to double-click what you just downloaded.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Yes - on Windows it's an .exe
file, so you just double-click the downloaded file.
@@ -83,9 +74,9 @@ e.g. your Desktop or a folder you have created for using in this workshop. | |||
|
|||
## Instructions for Windows | |||
|
|||
Launch the Anaconda Prompt program and type `jupyter lab`. | |||
Launch the MiniForge Prompt program and type `jupyter lab`. |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Launch the MiniForge Prompt program and type `jupyter lab`. | |
Launch the Miniforge Prompt program and type `jupyter lab`. |
cf. README at https://github.com/conda-forge/miniforge
opposed to the one with Python 2). If you wish to use an existing | ||
installation, be sure to upgrade your scikit-image to at least 0.19. | ||
You can upgrade to the latest scikit-image using the shell command that follows. | ||
1. Download and install the latest [MiniForge distribution of Python](https://conda-forge.org/download/) for your operating system. |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
1. Download and install the latest [MiniForge distribution of Python](https://conda-forge.org/download/) for your operating system. | |
1. Download and install the latest [Miniforge distribution of Python](https://conda-forge.org/download/) for your operating system. |
I just tried on Linux x86_64, I downloaded the $ mv ~/Downloads/environment.yml .
$ conda env create -f environment.yml
Solving environment: failed
CondaValueError: Malformed version string '~': invalid character(s).
$ cat environment.yml
name: dc-image
channels:
- conda-forge
dependencies:
- python>=3.11
- jupyterlab
- numpy
- matplotlib
- scikit-image
- ipympl
- imageio I tried editing the file by removing the Python version, but got the same error. 🤔 |
This updates the setup instructions for Python workshops. A recent blog post provides more context for this change. Specifically, this PR updates the instructions to reflect that we recommend Miniforge instead of Anaconda Python.
One of the most important changes here is to include an
environment.yml
for learners to use to create an environment that they can work in during the workshop/while following the lesson. When this PR is ready to merge, I will release a new version of the example data on FigShare that contains the environment file. Since I guess it will be helpful for testing purposes -- and because it is probably a good idea to keep a copy in the lesson repo too -- you can find my proposed version of that file in this PR.