Setting up Python on your local machine is simple, but a few best practices can make development much smoother and easier to maintain.

This guide walks through:

• Installing Python
• Setting up virtual environments
• Configuring VS Code for development
• Managing dependencies with pip
• Running and deploying Python applications

If you're coming from ecosystems like .NET or Node.js, this guide will also clarify how Python handles environments and dependency management.

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Installing Python

Download Python from the official website:

👉 https://www.python.org/downloads/

Steps:

1. Download the latest Python 3.x installer for Windows.
2. Run the installer.
3. Important: Check the option Add Python to PATH.
4. Click Install Now.

Adding Python to PATH allows you to run python commands directly from the terminal.

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Verifying Installation

Open Command Prompt or PowerShell and run:

python --version

Example output:

Python 3.12.2

Check pip (Python’s package manager):

pip --version

Example output:

pip 23.2 from C:\Users\<username>\AppData\Local\Programs\Python\Python312\Lib\site-packages\pip

If both commands work, Python has been installed successfully.

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Your First Python Project

Python development usually starts in one of two ways:

1. Creating a new project
2. Working with an existing repository

Let's start with a new project.

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Creating a New Python App

Step 1 — Create a project folder

Example:

my_python_app

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Step 2 — Create a virtual environment

python -m venv .venv

This creates an isolated Python environment inside:

.venv/

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Step 3 — Activate the virtual environment

Windows:

.venv\Scripts\activate

You should now see:

(.venv)

in the terminal.

Verify activation:

echo %VIRTUAL_ENV%

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Step 4 — Install dependencies

Example:

pip install flask requests

Important:

When pip install runs inside an activated virtual environment, packages are installed locally inside .venv, not globally.

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Step 5 — Freeze dependencies

pip freeze > requirements.txt

Example:

flask==3.0.1
requests==2.31.0

This file ensures other developers or servers can install the exact same dependency versions.

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Working With an Existing Python Project

Most real-world work starts by cloning a repository.

1. Clone the repository

git clone repo-url

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2. Create virtual environment

python -m venv .venv

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3. Activate environment

.venv\Scripts\activate

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4. Install dependencies

pip install -r requirements.txt
pip install -r requirements-dev.txt

Example:

(.venv) C:\Users\ankushzn\Desktop\app_backend>pip install -r requirements-dev.txt

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5. Run the application

Example:

streamlit run helloworld.py

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Virtual Environments

A virtual environment isolates dependencies for a project.

This prevents conflicts between different projects.

Example:

Project A might require:

Django 3

Project B might require:

Django 5

Virtual environments allow both versions to coexist safely.

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Important VS Code Extensions

Install Visual Studio Code along with the following extensions.

Python (Microsoft)

Provides core Python support:

• Interpreter selection
• Debugging
• IntelliSense

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Pylance

High-performance language server providing:

• Autocomplete
• Type checking
• Import suggestions
• Code navigation

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Black

Opinionated code formatter.

Benefits:

• Consistent formatting
• Eliminates style debates
• Automatically formats code on save

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isort

Automatically sorts imports.

Before:

import sys
import requests
import os

After:

import os
import sys
import requests

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Flake8

Linting tool that detects:

• unused imports
• style issues
• potential mistakes

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Python vs Pip

Tool	Purpose
Python	Interpreter that runs .py files
pip	Package manager used to install libraries

Example:

Run Python file:

python app.py

Install dependency:

pip install requests

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Why Sometimes You See python3 or pip3

On systems with both Python 2 and Python 3 installed, commands may differ.

Command	Meaning
python	Default Python interpreter
python3	Explicitly Python 3
pip	Package manager for default Python
pip3	Package manager for Python 3

Most modern Windows systems map python directly to Python 3.

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Python Interpreters

A Python interpreter is simply the python.exe executable that runs Python programs.

You can have multiple interpreters installed:

C:\Python310\python.exe
C:\Python312\python.exe
project.venv\Scripts\python.exe

Each interpreter has its own package environment.

Changing the interpreter simply means telling your IDE or terminal:

Use a different python.exe to run this project.

In VS Code:

Ctrl + Shift + P → Python: Select Interpreter

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Checking Which Python Is Being Used

You can verify the active interpreter using:

where python

Example output:

C:\Users\<username>\project.venv\Scripts\python.exe
C:\Users\<username>\AppData\Local\Programs\Python\Python312\python.exe

The first entry is the one currently used.

Similarly:

where pip

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Why Many Engineers Prefer python -m pip

Instead of:

pip install requests

many engineers prefer:

python -m pip install requests

This guarantees the package installs into the same Python environment as the interpreter you invoked.

For example:

python  → Python 3.12
pip     → Python 3.10

Using python -m pip avoids such mismatches.

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Where Python Gets Installed

Typical Windows installation location:

C:\Users\<username>\AppData\Local\Programs\Python\Python312</code>

Important directories:

Directory	Purpose
python.exe	Python interpreter
Scripts/	CLI tools like pip
Lib/site-packages	Installed packages

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Where pip Installs Packages

Global installation

C:\Users\<username>\AppData\Local\Programs\Python\Python312\Lib\site-packages

Virtual environment installation

project.venv\Lib\site-packages

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How Virtual Environments Work

Running:

python -m venv .venv

creates:

.venv
├── Include
├── Lib
│    └── site-packages
├── Scripts
│    ├── python.exe
│    ├── pip.exe
│    └── activate
└── pyvenv.cfg

When the environment is activated:

.venv\Scripts</code>

is added to the beginning of the system PATH, so python and pip resolve to the local environment versions.

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Packaging for Deployment

Unlike .NET or Node.js, Python applications are usually deployed by recreating environments.

Typical deployment steps:

1. Maintain dependency file

   requirements.txt
   

2. Create environment on server

   python -m venv .venv
   

3. Install dependencies

   pip install -r requirements.txt
   

4. Run application

   python app.py
   

   or

   gunicorn app:app
   

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Summary

A solid Python setup usually includes:

• Installing Python from the official website
• Verifying installation with python --version
• Using virtual environments (venv)
• Managing dependencies with requirements.txt
• Installing helpful VS Code extensions
• Using python -m pip to avoid environment issues

Following these practices keeps Python projects clean, reproducible, and easy to maintain.