Running Python code can be done both online and offline, depending on your requirements. Here are ways to run Python code in both scenarios:
Online
Online Code Editors: Platforms like
replit (https://replit.com/languages/online-python-compiler)
OnlineGDB (https://www.onlinegdb.com/online_python_compiler),
pynative (https://pynative.com/online-python-code-editor-to-execute-python-code/)
Programiz (https://www.programiz.com/python-programming/online-compiler/)
JDoodle (https://www.jdoodle.com/python3-programming-online)
allow you to write and execute Python code directly in your web browser. They provide a convenient online environment.
Notebooks in the Cloud:
Services like
Google Colab (https://colab.google/)
Azure Notebooks (https://www.databricks.com/)
Jupyter Notebooks (https://jupyter.org/try-jupyter/lab/index.html)
allowing you to write and run Python code in a collaborative and interactive environment.
Running the sample code on jupyter notebook online
Offline
Local Development Environment:
Install a Python interpreter on your local machine using tools like
Anaconda (https://docs.anaconda.com/free/anaconda/install/index.html)
Miniconda (https://docs.conda.io/projects/miniconda/en/latest/)
or directly from the official Python website (https://www.python.org/downloads/)
You can follow the steps and run Python scripts in your terminal or command prompt.
Integrated Development Environments (IDEs): Use IDEs like
PyCharm PyCharm Installation
Visual Studio Code (https://code.visualstudio.com/download)
These tools offer features like code completion, debugging, and project management.
Command Line / Terminal: Execute Python scripts from the command line or terminal by navigating to the script's directory and using the python command followed by the script name.
python script_name.py
Remember that for offline execution, you need to have Python installed on your local machine, while online platforms provide an environment without requiring local installations.
Choose the method that best suits your needs based on factors like collaboration, resource requirements, and development preferences.