Described in the hope that it will become knowledge that I have researched to some extent for my own understanding
See Jupyter Official Read the Docs.
The derivation relationship is as follows.
It's hard to tell from the image name, but the minimal-notebook
has a larger image size than the base-notebook
.
The one that is (probably) often used
scipy-notebook
--Additional library sets used for data analysis (pandas, scikit-learn, etc.)datascience-notebook
--scipy-notebook
with additional R and JuliaSo if you only use Python, scipy-notebook
is enough (misunderstood)
There are many image tags in each repository, and it is difficult to know which one to use at first glance.
The rules for image tags seem to have small quirks for each repository, but for example, base-notebook
is as follows as of July 29, 2020.
--The yellow highlighted part (b5abe43c6d31
) is the SHA digest of the container image. There are 6 tags for the same digest.
--In other words, these six are all aliases that point to the same container image.
--The last image Tag (b90cce83f37b
) is also a SHA digest. This is the commit hash on GitHub side.
--The Git commit corresponding to this image Tag is here
As you can see from these, the image tag of base-notebook
is registered as a Python version and version updated for each Jupyter component (Jupyter Notebook, JupyterLab, JupyterHub).
In base-notebook
, various aliases point to one container image, and you can find the image Tag corresponding to the past Python version.
Here, the most used (probably) scipy-notebook
image tags are only commit hashes, and it is difficult to find the image tag corresponding to the target Python version.
base-notebook
and minimal-notebook
, which are the base images for each image tag of scipy-notebook
.After trying some images, it seems that an image tag is created for each minor version of Python (3.6.6, 3.6.7, 3.8.0, ...)?