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Python VSCode: Installed modules not recognised (closed)

Edit: It's working fine now, it seems there was just something weird going on with VSCode
I am writing a discord bot in Python using Gitpod (which has VSCode Browser as its editor). I have installed Pycord 2.0 in the workspace using pip (obviously) but VSCode doesn't seem to be recognising it. I also have the Python VSCode extension installed which adds a 'Run' to the editor when a python file is selected. It used to work just fine but since a month ago it stopped working and the 'Run Code' button is running some sort of Python installation where none of the modules I installed are there. It also doesn't show any code hints for the modules.
I have tried pip show py-cord and changing the selected VSCode python interpreter accordingly. I've also tried changing th interpreter and installing Pycord into that interpreter but none of that worked.
I am running Gitpod on an iPad 6 (model A1893, iPadOS 15.6.1) in Safari
Does anyone know what might be wrong?
Thanks :)
~ R2509

Many developers have multiple python versions installed, and multiple environments with the same python versions, but different libraries installed. Therefore, we need to specify which python compiler VSCode needs to use.
Check on the bottom right of your VSCode, there should be a number down there representing an installation of python.
Upon clicking on it, VSCode will open a window on the top part, allowing you to select which of the many pythons you have installed you want to use. Find the one where you installed your libraries, and you should be good to go.

Method one:
Use pip show Pycord to see where you installed the package Pycord
then choose that environment
Method Two:
Choose a python version you want to use ( Ctrl+Shift+P --> Python:Select Interpreter )
Create a new terminal activation environment
Install the package using pip install pycord in the new terminal
As a suggestion:
you can use a virtual environment to better manage python versions and various packages.
# Create a virtual environment named .venv
python -m venv .venv
# Activate this virtual environment
.venv\scripts\activate

Installing packages in python and setting up the working environment

I've been coding with R for quite a while but I want to start learning and using python more for its machine learning applications. However, I'm quite confused as to how to properly install packages and set up the whole working environment. Unlike R where I suppose most people just use RStudio and directly install packages with install.packages(), there seems to be a variety of ways this can be done in python, including pip install conda install and there is also the issue of doing it in the command prompt or one of the IDEs. I've downloaded python 3.8.5 and anaconda3 and some of my most burning questions right now are:
When to use which command for installing packages? (and also should I always do it in the command prompt aka cmd on windows instead of inside jupyter notebook)
How to navigate the cmd syntax/coding (for example the python documentation for installing packages has this piece of code: py -m pip install "SomeProject" but I am completely unfamiliar with this syntax and how to use it - so in the long run do I also have to learn what goes on in the command prompt or does most of the operations occur in the IDE and I mostly don't have to touch the cmd?)
How to set up a working directory of sorts (like setwd() in R) such that my .ipynb files can be saved to other directories or even better if I can just directly start my IDE from another file destination?
I've tried looking at some online resources but they mostly deal with coding basics and the python language instead of these technical aspects of the set up, so I would greatly appreciate some advice on how to navigate and set up the python working environment in general. Thanks a lot!

Python uses a different way of installing packages. Python has a thing named venv which stands for Virtual Environment. You install all of your packages in venv. Usually for each new project you make a new venv.
By using Anaconda on windows you install everything within the anaconda environment that you have specified.
python -m pip install "modulename" is a command that will install modulename to your default venv. You will be able to use this module when no other venv is specified. Here is the docs page. And here is a tutorial on how to use venv
By default python uses the same directory you have your code in. e.g. C:/Users/me/home/mypythonfile.py will run in C:/Users/me/home/ and will be able to access files in this directory. However you can use ../ to navigate directories or you can specify an absolute path to file you want to open e.g. with open("C:/system32/somesystemfile.sys") as file

Going over the technical differences of conda and pip:
So Conda is a packaging tool and installer that aims to do more than what pip does; handle library dependencies outside of the Python packages as well as the Python packages themselves. Both have many similar functionalities as well, you can install packages or create virtual environments with both.
It is generally advisable to generally have both conda and pip installed since there are some packages which might not be available with conda but with pip and vice versa.
The commands to install in both the ways is easy enough, but one thing to keep in mind is that
conda stores packages in the anaconda/pkgs directory
pip stores it in directory under /usr/local/bin/ for a Unix-based system, or \Program Files\ for Windows
You can use both pip or conda inside the jupyter notebook, it will work just fine, but it may be possible that you get multiple versions of the same package.
Most of the times, you will use cmd only to install a module used in your code, or to create environments, py -m pip install "SomeProject" here basically means that the module "SomeProject" will be downloaded in base env.

You could think of conda as python with a variety of additional functionalities, such as certain pre-installed packages and tools, such as spyder and jupyter. Hence, you must be precise when you say:
I've downloaded python 3.8.5 and anaconda3
Does it mean you installed python in your computer and then also anaconda?
In general, or at least in my opinion, using anaconda has advantages for development, but typically you'll just use a simple python installation in production (if that applies to you).
Anaconda has it's own package registry/repository . When you call conda install <package>, it will search for the package there and install it if available. You would better search it first, for instance matplotlib.
pip is a package manager for the Python Package Index. pip also ships with anaconda. Hence, in an anaconda environment you may install packages from either sources (either using pip install or conda install). For instance, pandas from PyPI and pandas from conda. There is no guarantee that packages exist in both sources. You must either search it first or simply try it.
In your first steps, I would suggest you to stick to only one dev env (either simple python or anaconda, recommend the second). Because that simplifies the question: "which python and which pip is executed in the cmd line?". That said, those commands should work as expected in any terminal, it be a simple cmd or an embedded one like in PyCharm or VS Code.
You could inspect that by running (on windows and linux at least):
which python, which pip.
Honestly, this is a question/answer that falls outside the scope of SO and for more info you would better check official websites, such as for anaconda or search for python vs anaconda blogs.

How can I use both Anaconda versions (2.7 & 3.5)?

I was using the Anaconda 3.5 distro in a Windows 10 machine. Due to dependencies in libraries that I want to work with, I had to have the 2.7 version installed as well.
The good news is that the libraries I needed can now work with the 2.7 version smoothly and Visual Studio 2015 automagically detected my new Python environment.
The problem comes when using the command line. Upon issuing the command
conda info --envs
I get
root * C:\Users\norah\Anaconda2
i.e. a single environment (to my understanding and search so far, according to this I should see two envs listed). This means I can't use conda to acquire new packages for my Python3.5 installation, at least not at the command line as I used to since conda only refers to Python2.7. The same goes for the GUI version, Anaconda navigator (I'm not very fond of the GUI version but I tried it out).
There's also no way of launching python3 from the command line since
$python
always fires up python2.7 and issuing $python3 or $python3.5 in the command line doesn't seem to work (nor would adding the path of python3 to the system since the actual executable has the same name as python2 i.e. python.exe)
Is my system taken over by Python2.7? Is anyone here using them both smoothly and if so could you please elaborate on how to do that? Was it a "no no" move to install both versions of Anaconda?

You can make Python 3.5 environment with your Anaconda 2.7:
conda create -n py35 python=3.5
Now, activate it:
activate py35
Finally you can install the desired packages:
conda install numpy
or, the whole anaconda:
conda install anaconda
The advantage of this approach is that you can also create Python 3.4 or 3.6 environments. Furthermore, you can create environments with different combinations and versions of libraries.
Actually, it makes sense to create a new environment for each larger project.

I also despise the virtual environment switch that Anaconda tries to force on us. I prefer to have both executables always instantly available from the command line. I'm pretty sure I had this working on a Windows machine once:
Install Anaconda2 and Anaconda3 to the C:\ drive as "C:\Anaconda2\" and "C:\Anaconda3\" respectively.
Edit your "Path" environment variable (Control Panel -> System and Security -> System -> Advanced system settings -> Environment Variables) and make sure that "C:\Anaconda2;C:\Anaconda2\Scripts;C:\Anaconda2\Library\bin" is in front of "C:\Anaconda3;C:\Anaconda3\Scripts;C:\Anaconda3\Library\bin".
Copy and rename the file "C:\Anaconda3\python.exe" to "C:\Anaconda3\python3.exe".
Copy and rename the file "C:\Anaconda3\Scripts\conda.exe" to "C:\Anaconda3\Scripts\conda3.exe"
Copy and rename any other scripts you might use in "C:\Anaconda3\Scripts\", such as "pip.exe" to "pip3.exe", etc.
Now, when you type "python" or "conda" at the command line you will get the python2 version, and when you type "python3" or "conda3", etc. at the command line you will get the python3 version.

The best way to use both Python 2.7x and Python 3.5x together is Jupyter Notebook.
http://jupyter.org/
You will be able to work on your browser with IPython Notebook style interface which is great for working with scripting languages.
I found some of these videos on YouTube very informative:
1) https://www.youtube.com/watch?v=HW29067qVWk
2) https://www.youtube.com/watch?v=e9cSF3eVQv0
Besides Python 2.7 and 3.5, there are a bunch of other languages that you will be able run with your Jupyter Notebook. The various Kernels are available in this link below:
https://github.com/jupyter/jupyter/wiki/Jupyter-kernels
After installation, as you start your Jupyter Notebook, your browser will open up a new page showing your Home Directory. Among the 4 tabs (Files|Running|Clusters|Conda):
1) The Files tab shows all the files in your Home Directory.
2) Running tab shows all the Notebooks that are running.
3) Clusters tab is provided by IPython parallel.
4) Conda tab is where you need to add the Python version 3.5 (and other languages if needed) to your Jupyter Notebook (If Python 2.7 is default).
If you are interested to try C++ with your Jupyter Notebook, there are a couple of Kernels available.
1) JupyRoot - https://github.com/root-mirror/root/tree/master/bindings/pyroot/JupyROOT
2) Cling - https://github.com/root-mirror/cling

How to manage (ana)conda with pycharm 2016.3 in linux

I would like to use Anaconda and the newest Pycharm 2016.3 together. I would like to be able to manage packages in settings->interpreter. If this is not supported, I would like to know the workflow of using these two together. According to another SO question, Pycharm 5 used to have a 'Create conda env' in the interpreter settings, but this seems to be gone now. I have tried:
1) Manually creating a virtual environment with 'conda create --name project numpy' and I add the interpreter ('~/anaconda2/envs/bin/python', the location of python for my created virtual environment. However, pycharm doesn't allow me to add any packages through settings->interpreter. Running an 'import numpy' through the console shows errors that are pointing to /usr/bin/python, not my virtual env python, and an error 'ImportError: cannot import name multiarray'. I'm not sure what package to add using conda from the cli, and the pycharm frontend doesn't add packages
2) I've tried the same as 1) but with my global anaconda python as the interpeter ('~/anaconda2/bin/python') and it doesn't seem to be able to connect to the console.
3) Creating a virtual environment through pycharm directly.
I would like to remove my default pythons (/usr/bin/python2.7/3.5 from the list of interpreters in pycharm) for debugging purposes but it won't let me and it seems to be showing packages that my anaconda virtual env doens't have installed.
Is there a way to manage my VIRTUAL enviornment in Conda using pycharm? If not, what steps do I take to make these two play well together assuming I can't manage it through pycharm interepreters settings.

This is the normal steps that i follow when i use virutalenv with PyCharm
I normally work on ubuntu
First, i always create a separate environment for every project using the command virtualenv "environment_name" from the command line.
Activate the environment using the command - source environment_name/bin/activate in ubuntu.
Suppose if i want to start a django project, i create the project using the command django-admin startproject project_name
Open this project in pycharm.
go to settings-> interpreter in pycharm. choose "add local" interpreter from the settings. It will open a pop-up. Go to the directory of the environment you just created and select the correct python interpreter you want to use.
now if you want to install a new package, you can go to interpreter settings and add package from the pycharm or you can fire up the command line, activate the environment and run pip install package_name. Once the package is installed, it will also show in pycharm.
if you are using Windows OS, use powershell to execute the above commands. The only difference will be in activating the environment. In windows, to activate an env use environment_name/Scripts/activate
EDIT:
Same goes anaconda environments also, the easy way is to manage the environment from the terminal and pycharm will show the packages changes in the interpreter settings.

Here is what I have been doing and it works great. I create a virtual environment separately and when I create a new project in PyCharm, I point the interpreter to the python from the virtual environment. An example is shown in the picture below:

Anaconda overriding python as the default site-packages directory windows 7

from what I remember of middle school, anacondas and pythons are large snakes that overpower their prey, but anacondas are much bigger and heavier, which may be how it is overtaking my python pathway:
I installed psycopg2 with an easy .exe on windows 7 last night, and it worked (to the anaconda path)- but when I tried to start a Django app, it is looking in Python27\lib\site-packages. I allowed Anaconda to add itself to the pathway when I installed it because a post recommending it said to, and I also have Python set up correctly with a windows path variable.
This makes me wonder, should I actually uninstall python2.7.10, since Anaconda came with python 2.7.9 built in, and use the anaconda prompt for everything, and also delete python 2.7 from my path variable in windows? So,exactly
What is the best way to use Anaconda with Django?

I currently spent the weekend trying to tackle a similar issue. I have Anaconda (Miniconda3) installed for analytical work, however I also wanted to work on a Django project. In the end I ended up using an Anaconda virtual environment to work on my project. Here is basically what i did in cmd:
>mkdir mysite
>cd mysite
>conda create -n mysite-env python=3
>activate mysite-env
>conda install django
Basically this created a virtualenv in the envs folder in my Anaconda installation and I can create/work with django without having to worry about multiple python installations. Not sure if this is the best way, but its the way that works for me.

The issue you are having is that you may not have looked into what Anaconda is used for or what it solves. This step was pointed out in the installation steps when it adds Anaconda to your PATH. Being that Anaconda installs Python and has "environments" there is no reason to have 2 versions of the Python installation on your system, but Anaconda allows you to have different versions of Python with environments. Only one can use the "Python" command unless you execute it from the python.exe directory or make a separate alias as the python command and point it to the Anaconda or other Python installation. Again this is pointless as you can create a new environment with your Django project and requirements.
In short, having 2 separate Python installations is pretty much taking away what Anaconda helps solve.

In Windows 10, open Anaconda Navigator, search Not installed for 'django'. Click the check box, then hit Apply.