Free Online Python IDE: Run Python 3.11 to 3.14 in Your Browser
PythonMastery is a free, browser-based Python IDE powered by Pyodide (WebAssembly). It runs Python 3.13 by default, and the editor can switch to 3.14, 3.12 or 3.11.
Why use PythonMastery?
- New Choose your Python version: run your code on Python 3.14, 3.13, 3.12 or 3.11. Click the status line above the output to switch. Share links keep the version. The lessons, examples and notebook stay on 3.13, the version their outputs were checked on. What changed between versions →
- A route from zero to employable: the Python roadmap draws the lessons as a transit map: one line everyone rides, then Web, Data, ML and AI, or Automation, each ending in a project you build, plus what you can safely ignore for now.
- Embed it anywhere: turn any code into a box your readers can run, on your blog or course page, or a “Run in PythonMastery” badge for a GitHub README. How to embed Python →
- A real editor, in a tab: the tools you’d expect from a desktop
IDE: live syntax checking, find and replace, code folding, tabs that import each other
(
import helpersjust works), completion for the names in your own code,input()and a Stop button in every browser (Safari and iPhone too), a Recipes menu of ready-made code, auto-saved history you can roll back, an expand view for focus, and a nudge to take a break after 90 minutes. - Nothing to install: Python runs in this tab through WebAssembly. Open the page and start writing code. You don't need an account or an email.
- Your code and data stay on your device: code runs in your browser, uploaded files stay in your browser’s storage, and share links carry the code inside the URL. We have no upload endpoint, so there is nothing for us to see.
- Data science and ML, in the tab: NumPy, pandas, Matplotlib and scikit-learn are built in, and XGBoost, LightGBM and statsmodels run too. Train a RandomForest on a CSV you upload. PyTorch and TensorFlow are the honest exceptions: neither has a WebAssembly build. Working with your own data →
- A notebook: cells share one session, plots render inline, and
.ipynbfiles go in and out. Seven practice datasets load with one line. - Charts you can touch: Matplotlib as crisp images, Plotly live, so you can rotate a 3D scatter or zoom into a cluster.
- 222 lessons in 17 tracks: from your first variable to a neural network trained from scratch, including 60 Python errors explained and fixed. Also 195 Python programs with code and output, 31 tips, 26 short answers to “how do I…?” questions, 24 printable cheat sheets, and exercises in the Tutorial Lab.
- Made for phones and tablets: the same editor and lessons on any screen, with touch selection, three themes including Eye Saver, and weather in the background that matches your sky.
Frequently Asked Questions
- Can I run Python in a browser without installing anything?
- Yes. PythonMastery uses Pyodide, a WebAssembly version of CPython, to run Python entirely in your browser. No installation of Python, pip, or any tool is needed.
- Which Python version does it use, and can I change it?
- Python 3.13 by default. In the editor, click the status line above the output (it says Python 3.13.2 Ready) to switch to Python 3.14, 3.12 or 3.11. The editor remembers your choice. The lessons, examples, Tutorial Lab and notebook always run Python 3.13, the version their outputs were checked on. What changed between the versions.
- Is my Python code private and secure?
- Your code stays private. It runs in your browser and is never sent to our servers, so we have no access to what you write or run. We collect a few basic things, such as page views and any feedback you send, to keep the site working well. The privacy policy lists all of it.
- What Python libraries are available online?
- NumPy, pandas, SciPy, Matplotlib, scikit-learn, XGBoost, LightGBM, statsmodels, Pillow, SymPy and NetworkX are built into the runtime and need no install at all. Seaborn, Plotly, Pydantic and hundreds of other pure-Python packages install in seconds via micropip. PyTorch and TensorFlow are the main exceptions: neither has a WebAssembly build, so they cannot run in any browser.
- Can I train machine learning models in the browser?
- Yes. scikit-learn runs natively, so you can load a dataset, split it into train and test, fit a RandomForest or a linear regression, and score it, all in the tab, with no GPU and no account. XGBoost and LightGBM work too. For deep learning specifically, our network-from-scratch lesson trains a two-layer neural network in NumPy to 97% accuracy on handwritten digits in about a second.
- Can I upload my own CSV or dataset?
- Yes. Press Upload and pick a CSV, JSON, Excel sheet, image,
PDF or a whole project as a
.zip. You can pick several at once. The file lands where Python can read it by name, soopen("sales.csv")works with no path and nothing imported, andpd.read_csv("sales.csv")works too. pandas loads by itself when you import it. You can then clean it, chart it, and train a model on it. The working with your own data lesson walks through the encoding and delimiter traps real exports arrive with. - Where is my uploaded data stored?
- In your own browser, on your own device. Never on our servers. We have no upload endpoint and no database. The file is handed to the Python runtime running inside your tab. It is kept in your browser's storage so it is still there when you come back tomorrow, and it stays until you remove it: the × on the file, the Clear data files button, or clearing this site's data in your browser. That button removes your data files only. Your code, theme and lesson progress are not changed. Our privacy policy sets out every way those files go away.
- Can I write a program with more than one file?
- Yes. Open a tab per file and they import each other, so
import helpersresolves to thehelpers.pytab exactly as it would on your own machine. Download everything as a.zip, or share the whole project as one link. The code travels inside the link itself, not through our servers, so we never store anything you share. - Is there a Jupyter-style notebook?
- Yes. The Notebook gives you cells that share one Python
session, so a DataFrame you load in the first cell is still there in the tenth.
Tables and plots render inline, your work autosaves in the browser, and you can
import or export a standard
.ipynbfile. No login. - Are there datasets to practice on?
- Seven, ready to load with one line: housing prices, daily weather, retail orders, films, student results, subscription churn, and one deliberately messy signup file for cleaning practice. See Practice datasets.
- Can I create charts and visualizations in the browser?
- Yes, both still and interactive. Matplotlib works fully, including 3D surface plots, and renders as high-resolution PNG images inline, with options to download or copy. Plotly figures render live rather than as pictures: you can drag to rotate a 3D scatter plot or a loss surface, or zoom into a cluster.
- Does it work on mobile devices?
- Yes. PythonMastery is fully responsive and works on phones and tablets. The editor supports native touch selection with drag handles, and the layout adapts to portrait and landscape orientations.
- Can I put runnable Python on my own website or blog?
- Yes. Write the code in the playground, open Share (or Share+ for several files) and press Embed code: you get one line of HTML that shows a box your readers can edit and run inside your page. For GitHub there is a “Run in PythonMastery” README badge. Free, no account, and the code runs in the reader’s browser. Step-by-step guide.
- Is this Python online compiler free?
- Yes. No paid plans, no feature paywalls, no account. There are no ads today. If they come, they’ll be labelled and everything stays free.
- Can I learn Python for free here?
- Yes. Python Academy offers structured learning paths from beginner to advanced, covering Python fundamentals, data science, machine learning and AI. All of it is free and runs in the browser. Not sure where to start? The Python roadmap puts the paths in order, from your first line of code to a project you can show an employer.
- I got a Python error I don’t understand. Can you explain it?
- Paste the traceback into the error finder. It takes you to the page that fixes it (60 common errors are written up), or explains the error and points at the line of your code to look at. When a run fails in the editor or a lesson, the Explain this error link does the same in one click. It all runs in your browser. Your error is sent to us only if you choose to send it.
- Are there printable Python cheat sheets?
- Yes: 15 free one-page PDF cheat sheets, from strings, lists and dictionaries to regex, dates, type hints and argparse. Every example on them is run against Python before the sheet is published, and each sheet ends with the mistakes people often make. Free to print and share.
- Can I use input() in the browser?
- Yes. PythonMastery supports Python's input() function with an inline text field in the console. You can build interactive programs that ask the user for input, with no pop-ups or workarounds.
- Can I stop a running Python script?
- Yes. Click the Stop button to interrupt execution at any time. It works for infinite loops, long computations, and even input() prompts. If a graceful stop isn't possible, the environment automatically restarts.
Our Mission
Plenty of people learn to code on a phone, a shared computer, or a laptop they aren't allowed to install anything on. We built PythonMastery with them in mind, and that made it better for everyone: open a browser, and Python is there.
The editor, the notebook and all 222 lessons are free, and they work the same on a phone or tablet as on a desktop. The lessons are written to be read: real examples, real numbers, and honest notes on where Python falls short.
222 is where we are, not where we stop. Here's what shipped most recently, and your feedback decides what comes next. Wondering whether this is still worth learning when a model can write the code? We wrote an honest answer, including the parts that argue against us.
