Jupyter :: Anaconda :: getting started

[apollodriver]

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

[nekomatic]

I think you can find everything you need to know at https://www.anaconda.com/products/individual

When I use Python in my day job it's always in a conda environment and I'd strongly recommend it - there are other ways of creating virtual environments for Python but conda works pretty well in my opinion.

If you're not short of disk space I would just go for the Anaconda installer as it gives you an easier way to get started. If you're concerned about disk space and/or you're more comfortable with the command line than GUIs then you might as well just use the miniconda download. In either case I strongly recommend getting used to creating and working with environments as soon as possible - don't start developing stuff in the base environment, always create a new env for a new project. Many of the problems inexperienced users report with Anaconda are caused by installing or upgrading their base environment and finding that that breaks stuff, but if you change something in a project-specific environment and something goes wrong you can just delete the env and re-create it.

I see from a quick search that a few people are using Jupyter with MicroPython, but I haven't tried that.