I have python 3.8 installed in my windows 10 machine as system python.
I want to install anaconda. What precautions/steps should I take so that the system python does not interfere with the anaconda installation(which I am doing at a user level) while executing binaries or installing packages?
There are no specific precautions to take: a standard install of Anaconda won't replace the default Python installation of your system, unless you ask for it explicitly during setup.
Afterwards, you will be able to create independent conda environments, each of them having their own Python version and set of packages.
As #Woodford pointed to in eir comment, you will learn a lot by looking at the docs.
I have coded some projects in processing that I would like to continue in python under the python port p5py/p5.
I am using Anaconda as my Python environment, but couldn't find a way of installing p5py/p5 via conda; installing p5py/p5 via pip works, but the library can't be imported into within Spyder in the Anaconda environment.
I have been able to install all libraries on which p5py/p5 depends from within Anaconda, which makes it a bit frustrating that I can't get p5 installed.
I would therefore appreciate any tips for making p5py/p5 importable from with the Anaconda environment.
As performance is currently not a pressing issue to me so suboptimal workarounds would also be of help.
I am new to Python. I am a very old R programmer. One of my PhD courses is performed via Python.
So, I installed Jupyter Notebook; I wrote simple "Hello World" in Jupyter Notebook. I wonder whether I must install Anaconda or not?
I ask this because: I looked at Anaconda's IDE in youtube, and it shows RStudio, Jupyter Notebook, etc. in a bundled manner. In RStudio, one can perform all the package handlings within RStudio.
So, I wondered is there a way to install python packages within Jupyter Notebook, or should I really install Anaconda? What is the benefit of installing Anaconda (besides Jupyter Notebook)?
The packages in python are generally installed with "pip" (or "conda") in the terminal and are then available regardless where you run your script from. Assuming you don't have multiple python versions set up on your PC, they should then all be available in your jupyter-notebook also.
If you don't want to open another window to do this, you can also run BASH code from Jupyter itself, just start the line with an exclamation mark (!)
i.e.
!pip install pandas
The benefits of Anaconda are that it bundles everything you need to at least start your more basic projects (python release, basic packages, IDE) and that you can set-up project-specific environments that do not interfere with your system-wide package installations.
Python packages are not installed with python functions, like it would be the case in R with install.packages("package name"). Instead, an external package manager usually is used to install and possibly compile the package files to a directory where python can import it from.
Anaconda offers (among others) the package manager conda. Most popular is pip. Some Linux distributions also offer python packages via their package manager (e.g. apt on Debian/Ubuntu). All these package managers download packages from their own repositories, so conda install numpy, pip install numpy and apt install python3-numpy all install a package numpy, but from different sources and in possibly different versions.
Jupyter Notebook is a programming environment, where you can execute shell commands with !command, so depending on the system where the Jupyter server is running, you can use !pip install numpy, !conda install numpy or other commands as cells in the Jupyter Notebook you are working in. This will run the command in a shell.
That graphical menu with Jupyter, RStudio etc. you describe is the program "Anaconda Navigator", which is installed with Anaconda. Jupyter is just a Python library, which is pre-installed with Anaconda, but can also be installed via pip, apt and other package managers.
Like Virtualenv, Anaconda also uses the concept of creating environments so as to isolate different libraries and versions. Anaconda also introduces its own package manager, called conda, from where you can install libraries.
Additionally, Anaconda still has the useful interaction with pip that allows you to install any additional libraries which are not available in the Anaconda package manager.
It is a good option for setting up of a better environment for working with jupyter.
As I already have quite a lot of packages installed without installing Anaconda will I have to reinstall them again separately? Or are they accessible in Anaconda environment because I have them preinstalled? There is a similar question which has the answer suggesting installing only miniconda but in my case Anaconda is necessary.
No, anaconda uses completely different environments and whatever downgrading it does, it does it within it's own environments. So, if you are using anaconda environments within your applications, you don't need to reinstall anything but if you are using another environment (like pip only) you need to make sure you have installed all the necessary packages there as well.
Also, if a package is installed using pip and not installed in conda, it will automatically switch to pip so there is no problem there.
I'm pondering switching over to Anaconda from my vanilla Python in OSX. I know Anaconda brings its own NumPy. I was wondering if it was possible to make the GitHub version of NumPy the default version, or if Anaconda only works with its own version.
Anaconda installs python just like it already is on your system, only to a different location. It allows you to choose what packages you want to install. If you want to replace one you can go into the site-packages folder (Anaconda/lib/site-packages) and do so. In my experience, Anaconda was well worth the switch.