Setup and Environment

Overview#

Before writing any Python code, you need a working Python installation and a clean way to manage project dependencies. This notebook covers installing Python, understanding the interpreter, working with virtual environments, and using pip to manage packages. Getting this right early prevents a huge number of headaches later, especially when working on multiple projects with different dependency requirements.

1. Installing Python#

Python is available for Windows, macOS, and Linux. Most modern systems ship with some version of Python 3 pre-installed, but it is best practice to manage your own installation rather than relying on the system version.

After installing, verify the installation:

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python3 --version
pip3 --version

Note on python vs python3#

On many systems, python still refers to Python 2 or is unmapped entirely. Always use python3 and pip3 explicitly unless you have confirmed your python alias points to Python 3.

2. The Python Interpreter#

Python code can be run in two main ways:

1. Interactive mode (REPL) — type python3 in a terminal to get an interactive prompt where you can execute statements one at a time. Useful for quick experiments.
2. Script mode — write code in a .py file and run it with python3 filename.py.

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# Interactive mode
$ python3
>>> print("Hello, Python")
Hello, Python
>>> exit()

# Script mode
$ python3 hello.py

3. Virtual Environments#

A virtual environment is an isolated Python installation for a single project. It ensures that the packages one project depends on do not conflict with the packages another project depends on. Without virtual environments, installing packages globally can quickly lead to version conflicts across projects.

Creating a virtual environment#

Python includes the venv module by default — no extra installation needed.

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# Create a virtual environment named "venv"
python3 -m venv venv

Activating a virtual environment#

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# macOS / Linux
source venv/bin/activate

# Windows (Command Prompt)
venv\Scripts\activate.bat

# Windows (PowerShell)
venv\Scripts\Activate.ps1

Once activated, your terminal prompt typically changes to show the environment name, e.g. (venv) $. Any package you install now with pip goes into this isolated environment, not your system Python.

Deactivating#

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deactivate

4. Managing Packages with pip#

pip is Python's package installer. It downloads packages from the Python Package Index (PyPI) and installs them into the active environment.

requirements.txt#

Most Python projects track dependencies in a requirements.txt file so that the exact environment can be recreated elsewhere.

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# Save current environment's packages
pip freeze > requirements.txt

# Install from a requirements file
pip install -r requirements.txt

Example requirements.txt:

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requests==2.31.0
pandas==2.2.0
python-dotenv==1.0.1

5. Alternative Environment Tools#

While venv and pip are built into Python and sufficient for most cases, larger projects sometimes use additional tooling:

These are optional. A beginner should be fully comfortable with venv and pip before adopting any of these.

6. Recommended Project Structure#

A clean starting layout for a new Python project:

Architecture & Data Flow
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my_project/
├── venv/                 # virtual environment (not committed to git)
├── src/
│   └── my_project/
│       └── __init__.py
├── tests/
├── requirements.txt
├── .gitignore
└── README.md

Add venv/ to .gitignore so the environment itself is never committed — only requirements.txt needs to be shared.

Notes#

• Always activate your virtual environment before installing packages or running your project's code.
• One virtual environment per project is the standard convention.
• Never commit the venv/ folder to version control.
• If a terminal session is closed, the virtual environment deactivates automatically — you must reactivate it in each new session.
• Editors like VS Code can be configured to automatically activate the correct virtual environment per project (select the interpreter from the venv folder).

Best Practices Checklist#

• Install Python 3 from an official or trusted source, not an outdated system default
• Verify installation with python3 --version
• Create a dedicated virtual environment for every new project
• Always activate the virtual environment before installing packages
• Maintain an up-to-date requirements.txt
• Add venv/ (or equivalent) to .gitignore
• Pin package versions for reproducibility in production projects
• Deactivate the environment when switching to a different project