Skillversitas

Python Development Environment

Before starting with Python programming, you need to install Python on your computer. Python is available for various platforms including Windows, macOS, and Linux.

After Python is installed, it is recommended to use a virtual environment for each project. A virtual environment lets you isolate a project's dependencies so that library version conflicts don't occur between projects. Simply run python -m venv my-venv to create one, then activate it with the command source my-venv/bin/activate on macOS/Linux or my-venv\Scripts\activate on Windows.

Package management with pip is also an important skill. You can install libraries from PyPI with pip install library_name, view the list of installed libraries with pip list, and save them to a requirements.txt file with pip freeze > requirements.txt. This file makes collaboration easier, because other team members can install the same dependencies with just pip install -r requirements.txt.

Installation Steps:

  1. Download the installer from python.org/downloads
  2. Run the installer and check "Add Python to PATH"
  3. Click "Install Now" for a standard installation
  4. Verify the installation via terminal/command prompt
  • VS Code — lightweight, powerful Python extensions
  • PyCharm — Python-specific IDE from JetBrains
  • Jupyter Notebook — interactive, great for data science
  • Thonny — lightweight, great for beginners

Code Example

# Verify your Python installation in the terminal
# $ python --version
# Python 3.13.0

# $ pip --version
# pip 24.0 from ...

# Run Python interactively
# $ python
# >>> print("Python is running!")
# Python is running!

Code Explanation

The code above is not Python code that gets executed directly, but terminal commands prefixed with $. The first line checks the installed Python version with python --version. The third line checks the pip version, Python's package manager. The remaining part shows how to enter Python's interactive mode simply by typing python in the terminal. Interactive mode lets you type code line by line and see the results immediately — very useful for quick experiments.

Everyday Example

You want to create a simple data analysis project. First, create a project folder and activate a virtual environment:

mkdir sales-analysis
cd sales-analysis
python -m venv venv
source venv/bin/activate

Once the virtual environment is active, install the libraries you need:

pip install pandas matplotlib
pip freeze > requirements.txt

Now all project dependencies are neatly stored in requirements.txt. Tomorrow, if you want to continue working on another computer, just clone the project and run pip install -r requirements.txt.

Summary

A good development environment is the foundation of productivity. With Python installed, a virtual environment for project isolation, and a suitable IDE, you are ready to build Python applications cleanly and professionally. Be sure to always manage each project's dependencies separately.