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how do I get python to recognize modules installed in virtual environment?

I'm having trouble getting python in vs code to work properly. There were problems for a while (i dove right in with a workspace folder) so I decided to set up everything from scratch by starting a new project/workspace folder.
so far I've been having a few issues. The latest is this: despite creative a virtual environment as instructed on the vs code website, I can't get python to recognize that I've already installed the modules I want to use.
How do I fix this? (please see attached picture.
towards the bottom you can see that the virtual environment already has matplotlib, but python wouldn't recognize the module anyway

Create your virtual environment (e.g I used venv module to create a virtual env called TEST : $python3 -m venv TEST
From VS code go to Command Palette and type Python: Select Interpreter
And then you can choose the location of the desired interpreter (in my case the one from TEST virtual environment
You can always test your virtual environment from the terminal, e.g TEST env
Bash
From Cmd/Powershell normally you should run:
TEST\Scripts\activate.bat

Make VS Code terminal match debug environment on a Mac

I'm teaching a beginners python class, the environment is Anaconda, VS Code and git (plus a few extras from a requirements.txt).
For the windows students this runs perfectly, however the mac students have an existing python (2.7) to contend with.
The windows students (i.e. they have a windows computer), their environment when they debug matches their console environment. However the mac students seem to be locked to their 2.7 environment.
I've tried aliasing, as suggested here and here
alias python2='python'
alias python='python3'
alias pip2='pip'
alias pip='pip3'
I've modified the .bash_profile file
echo 'export PATH="/Users/$USER/anaconda3/bin:$PATH"' >>.bash_profile
Both of these seem to work perfectly to modify their Terminal environments, when launched externally to VS Code. Neither seem to do anything to the environment launched from [cmd]+[`].
I've also tried conda activate base in the terminal, which seems to have no effect on a python --version or a which python
They can run things using python 3, but that means that they need to remember that they are different to the other 2/3 of the students. It's othering for them, and more work for me!
The students are doing fine, launching things from their external terminal, but it would streamline things greatly if the environments could be as consistent as possible across the OSs.
Whilst they are complete beginners, they can run a shell script. They currently have one that installs pip requirements and vs code extensions.
Is there a configuration that will keep the terminal in line with the debug env?

In my opinion the best practice is to create Python virtual environments (personally I love using conda environments, especially on Mac where you stuck with unremovable old Python version). Then VSCode will automatically (after installing very powerful Python extension) find all your virtual environments. This way you will teach your students a good practice of handling Python zoo a.k.a. package incompatibilities. Terminal environments settings will be consistent with VSCode, without being dependent on unneeded any more aliases. Obviously, virtual environments are OS independent, so you will be more consistent and remove unnecessary confusion between different students.
The additional bonus of the virtenvs is that you can create one exactly according to your requirements.txt and switch from one to another with a single click (in terminal it takes two commands: deactivate -> activate).
You can read more about how to handle Python virtual environments on VSCode site

Given the aliases are run just once and are not persistent in .bash_profile, python targets the default interpreter rather than the expected conda python3 interpreter.
Try to symlink conda's python3 executable to capture the python namespace
ln -sf /Users/$USER/anaconda3/bin/python3 /Users/$USER/anaconda3/bin/python
This will create or update the symlink. Use the same approach for pip and pip3.

Python in vscode let's you select which interpreter will be used to run the scripts.
It is in settings under "python.pythonPath", just set it to point to the interpreter of choice.
It can be set on a project basis as well (which is how you ensure that a project that has a virtual environment will execute using that interpreter and packages), you just select Workspace in the settings pane and add the desired python interpreter there.

Activate virtualenv from a system running a different python version [duplicate]

This question already has answers here:
How to recreate a virtual env in python
(2 answers)
Closed 3 years ago.
I have two computers (running Ubuntu) that have access to one server. The shared home directory of the two computers is on the server.
On computer (A) python 3.5 is installed, on computer (B) python 3.7 is installed. I created a virtualenv from computer (B) on the shared home directory (using python 3.7).
Now although it is possible to activate that virtualenv from computer (A) it does not use the "virtualenv-python 3.7" but the system's python 3.5. So technically the virtualenv is activated but effectively it is not.
Note that the VIRTUAL_ENV path is set correctly.
I thought that virtualenv-folder is a fully enclosed environment, not even needing any python installed on the system. So why is it not working?

A virtualenv doesn't have a full Python installation. Instead, it links to an installation present on the system (FYI that link is in <env>/lib/orig-prefix.txt). The env's directory tree has some stubs and special logic but it uses the bulk from that installation.
So if you run activate on a system that doesn't have the same Python at the same path as the one virtualenv was created for, that script won't work correctly. It might happen to hook to something else present at the same path but this is not a supported scenario so all bets are off.
If you need a "fully enclosed environment", you may want to take a look at pyenv which does exactly that -- installs a full Python under your home dir. (Or you can just install Python from source to somewhere under your home dir -- but pyenv makes it easy to switch to that installation and back.)

The short answer is because on both computers A and B, the path to your python is likely just an alias. You can verify this by following the path on computer B and using the OS's GUI you can see it is a symlink to the actual python installation sitting somewhere else on your machine (probably usr/bin/). For example, on one machine where multiple installations of Python is found, I see that my virtual environment (.virtualenvs/revconnecion/include/python3.6) is an alias to the original /anaconda3/include/python3.6.
Solution:
You can create your virtual environment by specifying the python version itself when creating your environment:
python3.7 -m venv sharedvenv
or:
virtualenv -p python3.7
You can also manually change the symlinks / alias but the above method works better. Using the specific version of Python itself to create the virtual environment leaves no ambiguity and explicit is better than implicit.
Run which python on both Computer A and B to verify that it's pointing to the right version of Python.

Copy Python App to a new Machine?

I have a Python app running on windows that has imports for the following packages:
requests
json
psycopg2
I copy the entire project (I used Pycharms to write the app and import the packages) to a new machine and expected it would work. The new machine is also windows and I'm trying to run my script from the command line (i.e. no Pycharm on the new machine).
Instead, I get an error saying "ModuleNotFoundError: No module named 'requests'"
If I look at the project, I have the directories:
venv
Lib
site-packages
requests
What am I missing/doing wrong?

You have a couple of options here but first the problem. You are exporting your code base to a new machine without the required Modules installed on that machine and/or within your Python project's environment. After you have python installed on your new machine, you need to be sure to point your PyCharm Project to the proper environment.
File > Default Preferences > Project Interpreter
The window that appears on the right will contain a drop down menu labeled Project Interpreter. If you click on the drop down, it should reveal a list of the available Python environments on your machine.
Based on your description of your site-packages directory I would assume you do not have your interpreter pointed the proper environment on your new machine. With that said, you would be better served creating a new virtual python environment on your machine and installing each relevant dependency within that environment.
Take a look at this post here for your first best option on re-creating your old python environment on your new machine.
EDIT: I apologize for not reading the question more thoroughly before answering the questions. If this is running on a Windows machine you will need to double check the environment path python is using. It is very easy to install python at a different PATH than the command line environment is checking on a Windows box. If for example your PATH is pointing to a different version of Python and PIP is installing packages somewhere else this issue can occur. Double check your System PATH for python and which version the command line is running.

On the new machine you must source venv/bin/activate so your path environment variables are set properly. In particular, which python should say venv/bin/python rather than /usr/bin/python. Also, take care to conda env update or pip install -r requirements.txt so you'll have suitable venv libraries on the new machine.

Associating a python project with a virtual environment

been searching for this with no success, i don't know if i am missing something but i have a virtualenv already but how do i create a project to associate the virtualenv with, thanks
P.S. Am on windows

I could be wrong here, but I do not believe that a virtualenv is something that is by its very nature something that you associate with a project. When you use a virtualenv, you're basically saying, "I'm taking this Python interpreter, installing what I want on it, and setting it aside from the Python interpreter that the entire computer uses by default." Virtualenv does not have a concept of a Python "project"; it is just a custom version of a Python interpreter that you run code through. There are tools in IDEs like PyCharm that enable you to associate a project with a virtualenv, but those are another layer on top of the base software.
In order to use a virtualenv with a project, you will need to "activate" it every time you wish to use it. The documentation for activating a virtualenv on Windows is found here.
EDIT:
Saw that you had virtualenvwrapper tagged in your post, so I did a bit of hunting on that. It would appear that there is the mkproject command, which creates a project folder and then associates it with a virtualenv interpreter. Documentation on it can be found here.

Requirements:
Virtual Env
Pycharm
Go to Virtual env and type which python
Add remote project interpreter (File > Default Settings > Project Interpreter (cog) add remote)
You'll need to set up your file system so that PyCharm can also open the project.
NOTE:
do not turn off your virtual environment without saving your run configurations that will cause pycharm to see your run configurations as corrupt
There's a button on the top right that reads share enable this and your run configs will be saved to a .idea file and you'll have a lot less issues

If you already have your virtualenv installed you just need to start using it.
Create your projects virtual environment using virtualenv env_name on cmd. To associate a specific version of python with your environment use: virtualenv env_name -p pythonx.x;
Activate your environment by navigating into its Scripts folder and executing activate.
Your terminal now is using your virtual environment, that means every python package you install and the python version you run will be the ones you configured inside your env.
I like to create environments with the names similar to my projects, I always use one environment to each project, that helps keeping track of which packages my specific projects need to run.
If you haven't read much about venvs yet, try googling about requirements.txt along with pip freeze command those are pretty useful to keep track of your project's packages.

I like Pipenv: Python Dev Workflow for Humans to manage environments:
Pipenv is a tool that aims to bring the best of all packaging worlds (bundler, composer, npm, cargo, yarn, etc.) to the Python world. Windows is a first-class citizen, in our world.
It automatically creates and manages a virtualenv for your projects, as well as adds/removes packages from your Pipfile as you install/uninstall packages. It also generates the ever-important Pipfile.lock, which is used to produce deterministic builds.
Pipenv is primarily meant to provide users and developers of applications with an easy method to setup a working environment.