Real syntax, real object model, and a real live interpreter running in your browser.
Python has no braces — blocks are defined purely by indentation (4 spaces is convention). Core built-in types include int, float, str, bool, list, dict, tuple, and set.
name = "Ada"
age = 29
is_active = True
scores = [90, 85, 78]
if age >= 18:
print(f"{name} is an adult")
else:
print(f"{name} is a minor")
for loops in Python iterate directly over items in a sequence — there's no manual index management needed. range(n) generates a sequence of numbers when you do need a counter.
fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
print(fruit.upper())
for i in range(3):
print(f"Iteration {i}")A list comprehension builds a new list in a single, readable expression instead of a multi-line loop. Dictionaries store key-value pairs and are the backbone of most Python data handling.
numbers = [1, 2, 3, 4, 5]
squares = [n * n for n in numbers]
evens = [n for n in numbers if n % 2 == 0]
user = {"name": "Priya", "age": 24}
user["role"] = "engineer"
Functions are defined with def. Parameters can have default values, and Python supports both positional and keyword arguments, which makes function calls self-documenting.
def greet(name, greeting="Hello"):
return f"{greeting}, {name}!"
print(greet("Sam"))
print(greet("Sam", greeting="Welcome"))
A class is a blueprint for objects. __init__ is the constructor, called automatically when an object is created. Subclasses inherit behavior from a parent class and can override methods to specialize it.
class Animal:
def __init__(self, name):
self.name = name
def speak(self):
return f"{self.name} makes a sound"
class Dog(Animal):
def speak(self):
return f"{self.name} says Woof!"
print(Dog("Rex").speak())
try/except catches exceptions so one failure doesn't crash the whole program. The with statement (a context manager) guarantees resources like files are closed automatically, even if an error occurs inside the block.
try:
result = 10 / 0
except ZeroDivisionError as e:
print(f"Error: {e}")
with open("notes.txt", "w") as f:
f.write("Saved safely, file closes automatically.")This sandbox runs an actual CPython-compatible interpreter (Pyodide, compiled to WebAssembly) — not a simulation. Edit the code and click Run. The first run downloads the interpreter, so it may take a few seconds to initialize.
JSON is the standard format for exchanging data between services. The built-in json module converts between JSON text and native Python objects: json.loads() parses a JSON string into a dict/list, and json.dumps() serializes Python objects back into JSON text.
import json
raw = '{"name": "Priya", "skills": ["python", "sql"]}'
data = json.loads(raw)
print(data["skills"][0]) # "python"
data["active"] = True
print(json.dumps(data, indent=2))
A virtual environment is an isolated Python installation for a single project, so its dependencies don't conflict with other projects. pip is the standard tool for installing packages from PyPI into that environment.
python3 -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install requests
pip freeze > requirements.txt