A Python shell is probably the first place you start running Python scripts. While this is great, running a Python script is not the only option.
As your Python journey progresses, you'd need to run scripts in different ways. Each one has its own set of advantages and disadvantages.
Here is a summary of the six main ways to run a Python script.
1. Interactive interpreter
You can run Python code directly in the interactive interpreter, a command-line interface that allows you to type and execute code one line at a time. To start the interpreter, open a terminal and type
python. This will enter the interactive interpreter, and you can start writing and executing code.
- The interactive interpreter allows you to test small snippets of code quickly and easily without creating and saving a script file.
- It can help experiment with code snippets and see how they behave in real-time.
- The interactive interpreter can be a good tool for learning and exploring the Python language, as it allows you to try out different code examples and see their output immediately.
- The interactive interpreter is unsuitable for larger codebases, as it does not provide the same level of organization and structure as a script file or an IDE.
- It can be difficult to save and reuse code written in the interactive interpreter, as it is not committed to a file.
- The interactive interpreter does not provide many features available in IDEs, such as debugging tools, code completion, and syntax highlighting, which can make writing and testing code more efficient.
2. Script file
You can also save your code in a file with a
.py extension and run it from the command line. To run a script, open a terminal and navigate to the directory where the script is located. Then type
python script.py, where
script.py is the name of your script.
- Script files allow you to organize and structure your code in a more structured way than the interactive interpreter.
- Script files can be saved, shared, and reused, making it easier to collaborate with other developers or use code in different projects.
- Many IDEs and text editors provide features such as debugging tools, code completion, and syntax highlighting that can make writing and testing code more efficient.
- Running a script from a file requires you to open a terminal, navigate to the correct directory, and run the script using the
pythoncommand. This can be more time-consuming than the interactive interpreter, mainly if you are testing small code snippets.
- If you make changes to a script file, you will need to save it and rerun it to see the changes, which can be slower than using the interactive interpreter.
- Script files are not well-suited for interactive tasks such as data visualization or exploration, as they do not provide an interactive environment.
To write and run Python scripts, you can use an integrated development environment (IDE) such as PyCharm, IDLE, or Visual Studio Code. IDEs provide a text editor, a debugger, and other tools to help you write and test your code more efficiently.
- IDEs provide a more structured and organized environment for writing and testing code than the interactive interpreter or a simple text editor.
- Many IDEs provide features such as debugging tools, code completion, and syntax highlighting that can make writing and testing code more efficient.
- IDEs often provide a project management system that allows you to organize and manage multiple files and libraries in a single project.
- IDEs often provide integration with version control systems such as Git, making it easier to collaborate with other developers and track changes to your code.
- IDEs can be more complex and resource-intensive than text editors or interactive interpreters, making them slower to start up and use.
- IDEs often have a steeper learning curve than more straightforward text editors or interactive interpreters, as they have more features and functionality to learn.
- Some IDEs may have a subscription or licensing cost, which may be a barrier for some users.
- IDEs may not be as well-suited for simple tasks such as running small scripts or testing snippets of code, as they may provide more functionality than is necessary in these cases.
Related: Debug Python Scripts Like a Pro
4. Jupyter notebooks
Jupyter notebooks are web-based interactive environments that allow you to write and run Python code and include text, images, and other media in a single document. Jupyter notebooks are handy for data science and machine learning tasks, allowing you to visualize your data and results more interactively.
- Jupyter notebooks provide an interactive environment for running Python code, which can be helpful for data exploration and visualization tasks.
- Jupyter notebooks allow you to mix code, text, images, and other media in a single document, which can help present results and explain your work.
- Jupyter notebooks are web-based, which means you can access them from any device with a web browser, making them convenient for remote work or collaboration.
- Jupyter notebooks support multiple languages, which means you can use them for tasks beyond just Python programming.
- Jupyter notebooks can be slower to start and use than the interactive interpreter or a simple text editor, as they are web-based and provide more functionality.
- Jupyter notebooks do not provide the same level of organization and structure as a script file or an IDE, making them less suitable for larger projects or codebases.
- Jupyter notebooks can be more challenging to share and reuse than script files, as they are not saved in a plain text format and may include additional metadata.
- Jupyter notebooks do not provide many advanced debugging tools in IDEs, making debugging more difficult.
5. Web servers
- Web servers allow you to build and deploy web applications that can serve dynamic content to clients.
- Web servers can handle multiple requests concurrently, making them suitable for tasks such as serving a high traffic volume or handling real-time data.
- Web frameworks such as Django and Flask provide a range of tools and libraries that can make it easier to build and deploy web applications.
- Building and deploying web applications can be more complex and time-consuming than running simple scripts or programs.
- Web servers require additional infrastructures, such as a web server and a database, which can increase the complexity and cost of your setup.
- Web servers are not suitable for tasks that do not require a web interface or do not need to serve dynamic content to clients.
- Web servers may not provide the same level of performance and scalability as other types of servers, such as application servers or database servers, which may be more suitable for specific tasks.
6. Scheduled tasks
You can use tools such as the built-in
cron utility on Unix-like systems or the Task Scheduler on Windows to schedule your Python scripts to run at regular intervals or specific times. This can be useful for tasks such as data scraping or backups that need to be performed automatically.
- Scheduled tasks allow you to automate repetitive or time-consuming tasks, such as data scraping or backups, without requiring manual intervention.
- Scheduled tasks can be set up to run at regular intervals or specific times, which can be helpful for tasks that need to be performed at particular times or regularly.
- Scheduled tasks can run scripts on a server, even when you are not logged in or connected to the server, which can be helpful for tasks that need to be performed in the background.
- Scheduled tasks require additional setup and configuration, which can be more time-consuming than running a script manually.
- Scheduled tasks can be challenging to troubleshoot and debug if they fail, as they are not run interactively and may not provide helpful error messages.
- Scheduled tasks may not be suitable for tasks that require user input or interaction, as they are designed to run automatically in the background.
- Scheduled tasks may not be able to run if the system is shut down or if there are network or power issues, which can cause problems if the task is critical or time-sensitive.