Python: venv

1. Introduction

My VS Code asked me if I want to use a virtual environment.  I am not sure what I should do, so I asked ChatGPT about it.  I am using a virtual environment on PythonAnywhere, but I don't know why I need to be asked about it on my local environment.  I didn't know the conversation would be so long.

 

2. VS Code asked me about a virtual environment

When I ran Python code on VS Code, I got the following message:

A virtual environment is not currently selected for your Python interpreter. Would you like to create a virtual environment?

The code itself worked well.  But why did I get this message, and what does it mean?

 

Great question!

The message you saw in VS Code:

"A virtual environment is not currently selected for your Python interpreter. Would you like to create a virtual environment?"

is a reminder — not an error. Your code still runs because Python is installed, but here’s what it really means:

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✅ What is a Virtual Environment?

A virtual environment is a self-contained Python environment that keeps your project's dependencies (like Django, Flask, Pandas, etc.) separate from other projects and from the global Python installation.

---

🤔 Why VS Code shows this message

VS Code is trying to encourage good practice by reminding you to:

• Avoid installing packages globally.

• Keep dependencies isolated per project.

It’s especially useful in web development (like Django) where different projects often require different package versions.

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🛠️ What you can do

If you're already using a virtual environment (e.g., one created with venv, poetry, or virtualenv), you can:

1. Activate it in the terminal (manually).

2. Or click "Select Interpreter" in VS Code (bottom-left corner or Ctrl+Shift+P → Python: Select Interpreter) and pick the correct environment.

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🚀 If you want to create a new virtual environment

Click "Yes" when prompted, or do this manually:

Then in VS Code, select that environment as your interpreter.

 

[MY NOTE]

for GitBash, use:

source venv/Scripts/activate  # in Git Bash on Windows

See 11. Command for GitBash

 

---

 

Would you like help setting up or selecting the correct virtual environment in VS Code?

 

3. What is a virtual environment?

I still don't understand virtual environments.  I am using PythonAnywhere, which gives me a virtual environment, but it is on the cloud.  My VS Code shows many folders and files, and all of them are placed inside the local memory.  If I make a virtual environment for a file, what happens with other files in the folder that holds the file?  Can I make as many virtual environments as I want?

 

Great follow-up! You're asking the right questions. Let’s walk through it step by step so you understand exactly what a virtual environment is, what it affects, and how it behaves—especially in your setup using PythonAnywhere and VS Code on your local machine.

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✅ What is a Virtual Environment (Really)?

A virtual environment (venv) is:

A folder that contains its own Python interpreter, pip, and a private place to install packages just for that project.

It doesn't affect your system Python or other projects. It simply makes sure dependencies stay isolated.

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📁 What Happens in VS Code If You Create a Virtual Environment?

Let's say your VS Code project looks like this:

If you create a virtual environment here using:

You’ll get a venv/ folder inside your project.

🔍 What it affects:

• It does not change your code files.

• It only controls where pip installs packages.

• Any Python file you run inside VS Code (while the venv is selected) will use the packages from venv/.

✅ The rest of your files will still work fine.

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🤔 What If You Already Have a Virtual Environment on PythonAnywhere?

PythonAnywhere gives you a virtual environment on the cloud, usually at:

But your local VS Code doesn't know about it — and cannot use it directly. So, when you're working locally, you should make another virtual environment in your local project.

Each system needs its own venv:

• Local machine → Local venv (for development)

• PythonAnywhere → Cloud venv (for deployment)

You can copy the requirements.txt from local to cloud to keep them in sync.

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🔄 Can I Make Multiple Virtual Environments?

Yes! You can make as many as you want. Just place them in different folders.

Example:

You can even put them outside your project folders if you want to share a venv across projects — though that’s less common.

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✅ Summary

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Would you like help creating and selecting a virtual environment in VS Code right now?

 

4. Global packages

I have already used pip many times.  Are the packages I installed global?  Then, where are they placed now?

 

Great question — and very important! Let's figure out where your installed packages are now, and whether they were installed globally or inside a virtual environment.

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✅ If You Didn't Use a Virtual Environment…

Then yes, any packages you installed using pip install ... were installed globally (i.e., to your system Python environment).

This can lead to problems like:

• Conflicts between projects

• Hard to reproduce bugs on other machines

• Difficulty deploying to environments like PythonAnywhere

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🧭 Where Are Globally Installed Packages Stored?

You can check where pip is currently installing packages by running this in your terminal:

Look for a line like:

Or on Windows:

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🔍 Check If You're Inside a Virtual Environment

Run this in the terminal:

• If you're in a virtual environment, the path will point to something like:

  swift

  /your/project/path/venv/bin/python

• If it points to something like:

  bash

  /usr/bin/python

  or

  makefile

  C:\Python3x\python.exe

  then you're using the global Python.

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🧼 How to Avoid Global Installs Going Forward

To keep things clean, it's a good idea to start using virtual environments:

Then run:

These packages will go only into venv/, and not affect other projects.

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🗂️ How to Check What’s Installed Globally

You can run:

This shows what’s installed in your current environment (global or virtual).

To see the exact path of a package:

Look at the Location: field.

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✅ Summary

---

 

Let me know if you'd like help setting up your first virtual environment and moving your dependencies into it.

5. Why venv venv?

Why are there two "venv" in this command? 

python -m venv venv

 

Excellent question!
The command:

looks like it repeats itself, but each venv actually means something different:

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🧠 Breakdown of the command

So it's saying:

“Use Python to run the venv module, and create a virtual environment inside a folder named venv.”

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📁 What you'll get

After running:

You’ll get this structure:

The folder named venv/ can be anything, like env/, myenv/, djenv/, etc. Example:

will create a folder named myenv/.

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✅ Summary

 

Let me know if you'd like to activate and start using your new virtual environment in VS Code!

6. Where should I put the venv folder?

My folder structure is like this:  Under Documents folder, there are C, C++, Java, PHP, Python, R, etc. folders.  Under the Python folder, there are Altair, Code, Pandas, Django, os, OOP, matplotlib, etc folders.  Where should I put venv/ folder?

 

Thanks for the clear structure! Since you're organizing projects by language and topic, you have a few good options depending on how many Django projects or Python projects you're planning to run with virtual environments.

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🗂️ Your Structure (simplified)

Documents/

├── Python/

│        ├── Altair/

│        ├── Code/

│        ├── Pandas/

│        ├── Django/

│        ├── os/

│        └── ...

 

✅ Option 1: Create venv/ inside each project folder

This is the most common and recommended way.

Example:

 

Documents/

└── Python/

          └── Django/

                    └── mysite/

                                ├── manage.py

                                ├── myapp/

                                ├── templates/

                                ├── venv/          ← virtual environment for this Django project

 

You would run:

✅ Pros:

• Keeps each project fully isolated

• Easy to delete or recreate just one environment

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🚫 Option 2: Shared venv/ in the Python or Django folder

You could technically do this:

 

Documents/

     └── Python/

                 └── Django/

                             ├── venv/        ← shared virtual environment

                                         └── mysite/

 

But it's not recommended because:

• It mixes your environment with your projects

• It breaks isolation between projects

• You might get dependency conflicts

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✅ Best Practice

Keep one venv/ per project, inside that project folder.

Then, in VS Code, when you open the folder (like mysite/), VS Code will usually detect the local venv/ and activate it automatically.

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🛠️ Bonus Tip: Prevent committing venv to Git

If you're using GitHub, create a .gitignore file in the project folder and add:

This prevents the huge venv folder from being uploaded.

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Let me know if you’d like a quick guide to create, activate, and use your first venv in one of your project folders!

7. Global packages still used?

Suppose there are global packages as well as a local venv.  What happens with the global packages if I choose the local venv?  Are they completely ignored?  Or if there are no conflicts, are global packages still applied?

 

Great question — and a really important one when it comes to Python environments.

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🎯 Short Answer:

When you activate a local virtual environment (venv), only packages installed inside that venv are used.

By default:

• ✅ Global packages are completely ignored.

• ✅ Even if global packages are installed, your local venv won’t see them unless explicitly told to.

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🔍 Why?

The whole point of a virtual environment is isolation — so each project can control its own dependencies and versions without interference from system-wide packages.

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❓But can a venv access global packages?

Yes — but only if you create it that way.

You can run:

This allows the venv to “see” global packages in addition to local ones.

However, this is rarely recommended, because it can lead to:

• hidden dependency conflicts

• unexpected behavior

• hard-to-reproduce bugs

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🧪 Example

Suppose:

• Global environment has numpy installed

• Your project’s venv/ does not have numpy

Then:

• If you just run python -m venv venv → import numpy ❌ will fail inside venv.

• If you run python -m venv venv --system-site-packages → import numpy ✅ will work only because it comes from global packages.

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✅ Best Practice

Stick to local venvs that ignore global packages.

This ensures:

• No surprises

• Clean installs using pip install ...

• Reproducible environments (use requirements.txt)

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Let me know if you want help checking whether a package is coming from global or local, or how to install and freeze packages in your venv!

8. This file

What is requirements.txt?  

 

Great question!

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✅ What is requirements.txt?

requirements.txt is a plain text file used in Python projects to list all the packages (and their versions) your project depends on.

This allows others — or even you in the future — to easily recreate the exact environment by installing the same dependencies with a single command.

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📦 Example: What it looks like

Each line:

• Specifies a package (Django, requests, etc.)

• Optionally pins a version (==, >=, etc.)

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🛠️ How to create it

Inside your virtual environment, run:

This will save all installed packages and versions into requirements.txt.

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🚀 How to use it

If someone else (or future you) wants to install all required packages into a fresh virtual environment:

This reads the file and installs each package listed.

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💡 Why it's important

• Makes your project reproducible

• Avoids “works on my machine” problems

• Required by many platforms (like Heroku, PythonAnywhere, etc.)

---

 

Let me know if you'd like help creating one for your project or trimming it down to only essential packages!

 

9. Upload requirements.txt onto GitHub

So you can upload requirements.txt onto GitHub, instead of the venv folder, right?

 

Exactly — you're absolutely right ✅

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🔁 Upload requirements.txt — Not the venv/ Folder

When you're uploading your Django or Python project to GitHub, the best practice is:

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🔧 Why not upload venv/?

• It's very large (can be hundreds of MB)

• It's specific to your system and OS

• It's automatically reproducible using requirements.txt and pip

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✅ Typical Workflow:

1. Create venv/ and activate it locally

2. Install packages using pip install ...

3. Run:

   bash

   pip freeze > requirements.txt

4. Add this line to .gitignore:

   venv/

5. Commit and push requirements.txt to GitHub

6. On another machine:

   • Clone the repo

   • Run python -m venv venv

   • Activate the venv

   • Run pip install -r requirements.txt

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Let me know if you'd like help setting up .gitignore or writing a simple README.md for your GitHub project!

 

10. Is disc space okay?

I wonder it might take too much disc space if you create a venv folder for each project because packages are very large.  Do you still think it is the best practice to create a venv for each project?  

 

That's a very smart question, and you're right to be thinking about disk space.

Here’s the full picture:

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🧠 Why we recommend one venv per project

Despite the disk space cost, yes — it's still best practice for these key reasons:

✅ 1. Isolation

Each project has:

• Its own dependencies

• Specific versions that won't clash with other projects

This avoids version conflicts like:

Project A needs Django 4.2, but Project B breaks with anything above Django 3.2.

✅ 2. Reproducibility

Each virtual environment:

• Matches requirements.txt

• Makes deployment and collaboration easier

• Prevents "it works on my machine" problems

✅ 3. Stability

You can upgrade or test libraries in one project without affecting others.

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💾 Disk Space: Yes, it adds up

A typical virtual environment is around 100–200 MB, but could be larger depending on the packages.

🛠️ Ways to reduce the pain:

• Use --system-site-packages when creating a venv to share global packages (not recommended unless you're careful):

  bash

  python -m venv --system-site-packages venv

• Delete and recreate venv/ only when needed.

• Use tools like pipenv or Poetry that manage environments more efficiently.

• Use conda (if using Anaconda), which manages environments more flexibly but also uses more space.

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🧪 Tradeoff Summary:

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🚀 Bottom line

Unless you're really tight on disk space or managing dozens of small scripts, a venv per project is worth it.

 

Let me know if you want help finding your biggest environments or cleaning unused ones!

 

11. Command for GitBash

You said:

python -m venv venv

source venv/bin/activate # On Mac/Linux

venv\Scripts\activate # On Windows

I am using GitBash on a Windows machine.  Which line of code should I use, the 2nd one or the 3rd one?

 

Great question — since you're using Git Bash on a Windows machine, the correct command is:

✅ Explanation:

• On Windows, virtual environment activation scripts are located in venv/Scripts/

• In Git Bash, you use the Unix-style source command, not the Windows venv\Scripts\activate (which is for Command Prompt)

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✅ Summary for Git Bash on Windows:

Once activated, your terminal prompt will change to show the active environment like:

 

Let me know if you see any errors or want to test if activation worked!

 

12. deactivate

(1)

How can I return to the global environment?

 

To return to the global environment (i.e., deactivate your virtual environment), simply run:

✅ This works in Git Bash, Command Prompt, PowerShell, Linux, or macOS — it's a cross-platform command.

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💡 What it does:

• It removes the virtual environment from your current shell session.

• Your prompt will return to normal (no more (venv) prefix).

• Python and pip will go back to using the global installation.

 

Let me know if you'd like to confirm you're out of the virtual environment!

 

(2)

In that case, does the venv still exist?

 

Yes — the venv still exists even after you run deactivate.

✅ What deactivate does:

It only exits the virtual environment for your current terminal session. It does not delete anything.

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🧾 What stays after deactivate:

• The venv/ folder is still on your disk.

• All installed packages in the virtual environment are still there.

• You can reactivate it anytime with:

  bash

  source venv/Scripts/activate # in Git Bash on Windows

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🗑️ To permanently delete the virtual environment:

If you really want to remove it:

Or on Command Prompt or PowerShell:

 

Let me know if you'd like help checking what’s inside your venv or safely removing it.

 

13. PowerShell

What about PowerShell?  My VS Code uses PowerShell as its terminal.  Can I use the same command as GitBash?

python -m venv venv

source venv/Scripts/activate

 

Good question — PowerShell and Git Bash use different commands to activate a virtual environment.

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✅ For PowerShell (used by default in VS Code on Windows):

Note the dot and space (. .\venv\Scripts\Activate.ps1) — that’s how you run a script in PowerShell.

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❌ source won’t work in PowerShell

source is a Unix/Linux/Git Bash command. PowerShell doesn’t recognize it.

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🛡️ Possible Permission Issue in PowerShell:

If you see an error like:

You can fix it temporarily (just for the current session) by running:

Then activate again:

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Let me know if you want to switch your VS Code terminal to Git Bash or keep using PowerShell — I can help with either!