Jupyter :: Anaconda :: getting started
Posted: Sat Jan 16, 2021 4:01 pm
hi there dear community
want to Use Jupyter Notebook - i look for a easy way for a beginner to get started with Jupyter Notebooks
should i install Anaconda -
Anaconda - one of the most widely used Python distribution for data science and comes pre-loaded with all the most popular libraries and tools.
question: is there a lightweight version of Anaconda: guess that it is called conda or miniconda?!
which prerequsites (hardware) are needed to run
a. Anadona
b. Jupiter
i would love to hear from you
btw: found some awesome github ressoures for Python and Jupiterlab
https://github.com/vinta/awesome-python
https://github.com/mauhai/awesome-jupyterlab
update and by the way - if we discuss this a bit broader then we have to include Anaconda and docker too:
both of them provide isolated fully-fledged-configurable environment that allows the developers to avoid dependency resolution on any host computers.
Well this is pretty interesting: so we can say that these are different things - both are completely different types of application. However they do have some kind of overlap in terms of providing consistent software-systems across different platforms. So here first of all some ideas bout the conda-concept:
Conda; Conda attempts to do this by providing code binaries and a compatible ecosystem within environments. Conda can be called somewhat a package manager used for the installation and uninstallation written in Python, but which can manage applications in multiple languages
that said we have a look at Docker: Docker is a containerization of a system-application above a very very minimal Linux kernel (minimized). Docker isolates individual programs in containers so they don’t step on each others toes.
Some Docker images use Conda as their primary dependency installation step, and there are now tools that auto-create
We can say that Docker images are somewhat based on Conda-packages. Docker’s concept of a registry is the very same as a package manager, except they deal in images and Dockerfiles rather than releases and source code.
from a Meta-level we d say that they both do quite the same thing and job and that they do it in quite different ways. That saind the question of chhoosing some of them sounds like a request for a discussion of things like:
You can say Conda a package manager, in the kind of NPM or Yarn. Otherwise Docker is container platform that let us package our environment in a isolated container-system
want to Use Jupyter Notebook - i look for a easy way for a beginner to get started with Jupyter Notebooks
should i install Anaconda -
Anaconda - one of the most widely used Python distribution for data science and comes pre-loaded with all the most popular libraries and tools.
question: is there a lightweight version of Anaconda: guess that it is called conda or miniconda?!
which prerequsites (hardware) are needed to run
a. Anadona
b. Jupiter
i would love to hear from you
btw: found some awesome github ressoures for Python and Jupiterlab
https://github.com/vinta/awesome-python
https://github.com/mauhai/awesome-jupyterlab
update and by the way - if we discuss this a bit broader then we have to include Anaconda and docker too:
both of them provide isolated fully-fledged-configurable environment that allows the developers to avoid dependency resolution on any host computers.
Well this is pretty interesting: so we can say that these are different things - both are completely different types of application. However they do have some kind of overlap in terms of providing consistent software-systems across different platforms. So here first of all some ideas bout the conda-concept:
Conda; Conda attempts to do this by providing code binaries and a compatible ecosystem within environments. Conda can be called somewhat a package manager used for the installation and uninstallation written in Python, but which can manage applications in multiple languages
that said we have a look at Docker: Docker is a containerization of a system-application above a very very minimal Linux kernel (minimized). Docker isolates individual programs in containers so they don’t step on each others toes.
Some Docker images use Conda as their primary dependency installation step, and there are now tools that auto-create
We can say that Docker images are somewhat based on Conda-packages. Docker’s concept of a registry is the very same as a package manager, except they deal in images and Dockerfiles rather than releases and source code.
from a Meta-level we d say that they both do quite the same thing and job and that they do it in quite different ways. That saind the question of chhoosing some of them sounds like a request for a discussion of things like:
You can say Conda a package manager, in the kind of NPM or Yarn. Otherwise Docker is container platform that let us package our environment in a isolated container-system