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  • # Python 3: Fibonacci series up to n
>>> def fib(n):
>>>     a, b = 0, 1
>>>     while a < n:
>>>         print(a, end=' ')
>>>         a, b = b, a+b
>>>     print()
>>> fib(1000)
0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987

    Functions Defined

    The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. More about defining functions in Python 3

  • # Python 3: List comprehensions
>>> fruits = ['Banana', 'Apple', 'Lime']
>>> loud_fruits = [fruit.upper() for fruit in fruits]
>>> print(loud_fruits)
['BANANA', 'APPLE', 'LIME']

# List and the enumerate function
>>> list(enumerate(fruits))
[(0, 'Banana'), (1, 'Apple'), (2, 'Lime')]

    Compound Data Types

    Lists (known as arrays in other languages) are one of the compound data types that Python understands. Lists can be indexed, sliced and manipulated with other built-in functions. More about lists in Python 3

  • # Python 3: Simple arithmetic
>>> 1 / 2
0.5
>>> 2 ** 3
8
>>> 17 / 3  # classic division returns a float
5.666666666666667
>>> 17 // 3  # floor division
5

    Intuitive Interpretation

    Calculations are simple with Python, and expression syntax is straightforward: the operators +, -, * and / work as expected; parentheses () can be used for grouping. More about simple math functions in Python 3.

  • # For loop on a list
>>> numbers = [2, 4, 6, 8]
>>> product = 1
>>> for number in numbers:
...    product = product * number
... 
>>> print('The product is:', product)
The product is: 384

    All the Flow You’d Expect

    Python knows the usual control flow statements that other languages speak — if, for, while and range — with some of its own twists, of course. More control flow tools in Python 3

  • # Simple output (with Unicode)
>>> print("Hello, I'm Python!")
Hello, I'm Python!
# Input, assignment
>>> name = input('What is your name?\n')
What is your name?
Python
>>> print(f'Hi, {name}.')
Hi, Python.

    Quick & Easy to Learn

    Experienced programmers in any other language can pick up Python very quickly, and beginners find the clean syntax and indentation structure easy to learn. Whet your appetite with our Python 3 overview.

Python is a programming language that lets you work quickly and integrate systems more effectively. Learn More

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Get Started

Whether you're new to programming or an experienced developer, it's easy to learn and use Python.

Start with our Beginner’s Guide

Download

Python source code and installers are available for download for all versions!

Latest: Python 3.14.4

Docs

Documentation for Python's standard library, along with tutorials and guides, are available online.

docs.python.org

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Looking for work or have a Python related position that you're trying to hire for? Our relaunched community-run job board is the place to go.

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Prioritizing cutting-edge speed and supporting the rapid growth of Hudson River Trading’s codebase can have unintended effects that require innovative solutions. For those working on our Python codebase, this means addressing “code tangling,” the coupling of unrelated code through unintuitive import cycles. In this article, George Farcasiu, Noah Kim, Jacob Brugh, and Jiahao Li discuss how they mitigate the cost and time burden of this issue by creating new tools to analyze and untangle dependencies efficiently.

Building a Dependency Graph of Our Python Codebase by George Farcasiu, Noah Kim, Jacon Brugh, Jiahao Li

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