How to Set Up the Development Environment for Python?

Recently, a member of the New York Python user group asked me how to set up the development environment for Python. I explained everything in a detailed session, and I am going to explain how to set up the development environment for Python here in detail.

Table of Contents

Set Up the Development Environment for Python

Follow the step-by-step tutorial on setting up a Python development environment.

1. Install Python

The first step is to install Python on your system. Python can be downloaded from the official Python website. Here’s how to do it:

Download the Installer:

Go to the Python downloads page.
Select the version that suits your operating system (Windows, macOS, or Linux).
Download the installer.

Run the Installer:

Open the downloaded file.
On Windows, ensure you check the box that says “Add Python to PATH” before clicking “Install Now.”
Follow the prompts to complete the installation.

Verify Installation:

Open a command prompt or terminal.
Type python --version or python3 --version to check that Python has been installed correctly.

I also write a complete tutorial of Python installation steps with screenshots.

2. Install an Integrated Development Environment (IDE)

An IDE is a software application that provides options to programmers for software development. Here are some popular IDEs for Python:

PyCharm:

PyCharm is a powerful IDE specifically for Python.
Download and install PyCharm from the JetBrains website.
Follow the setup instructions to configure PyCharm for the first time.

Visual Studio Code:

Visual Studio Code is a lightweight but powerful source code editor.
Download and install it from the official website.
Install the Python extension for Visual Studio Code to add support for Python.

Jupyter Notebook:

Ideal for data science and machine learning projects.
Install Jupyter Notebook using pip: pip install notebook.
Start Jupyter Notebook by typing jupyter notebook in your terminal.

There are even some Online Python environments you can use to run the code.

https://www.online-python.com/

3. Set Up a Virtual Environment

Virtual environments are crucial for managing dependencies and avoiding conflicts between different projects. Here’s how to set one up:

Create a Virtual Environment:
- Open your command prompt or terminal.
- Navigate to your project directory.
- Run python -m venv myenv (replace “myenv” with your preferred environment name).

Activate the Virtual Environment:
- On Windows: myenv\Scripts\activate
- On macOS/Linux: source myenv/bin/activate

Deactivate the Virtual Environment:
- Simply type deactivate in your terminal.

4. Install Necessary Packages

Once your virtual environment is set up, you can install the packages you need using pip. For example:

To install Flask: pip install flask
To install Django: pip install django
To install NumPy and Pandas: pip install numpy pandas

You can create a requirements.txt file to keep track of your project’s dependencies. To generate this file, run:

pip freeze > requirements.txt

To install packages from a requirements.txt file, use:

pip install -r requirements.txt

5. Version Control with Git

In Python, using version control is a best practice for any development project. Git is the most widely used version control system.

Install Git:
- Download and install Git from the official website.

Set Up Git:
- Configure your Git username and email:

bash git config --global user.name "Your Name" git config --global user.email "your.email@example.com"

Initialize a Git Repository:
- Navigate to your project directory.
- Run git init to initialize a new Git repository.

Basic Git Commands:
- git add . to stage changes.
- git commit -m "Your commit message" to commit changes.
- git push to push changes to a remote repository.

6. Additional Tools and Extensions

Depending on your project, you might need additional tools and extensions in Python:

Linters and Formatters: Tools like Flake8 and Black can help keep your code clean and readable.
Install Flake8: pip install flake8
Install Black: pip install black
Docker: For containerizing your applications.
Install Docker from the official website.
Database Management Tools: Tools like PostgreSQL, MySQL, and MongoDB are commonly used in Python projects.

Conclusion

I hope you have a complete idea of what is required for Python development. I have explained in detail how to set up a development environment for Python.