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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.

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Latest: Python 3.14.3

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Einblick reimagines the modern data science workflow in a collaborative data science canvas, rather than a linear notebook. Working in a canvas environment offers many advantages including live collaboration, an expansive visual interface, and a progressive computation engine. In this article, weā€™ll highlight one of the key ways weā€™re saving data scientists timeā€“our operators. Weā€™ll go through a couple of our core operators, why Python is such a crucial part of our software solution, and how we augmented our offerings with a user operator interface. The latter allows users to customize and use their own operators, which can be used in any Einblick canvas, and shared with other Einblick users.

Reimagining data science with Python-based operators in Einblickā€™s visual canvas by Becca Weng

Use Python for…

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The mission of the Python Software Foundation is to promote, protect, and advance the Python programming language, and to support and facilitate the growth of a diverse and international community of Python programmers. Learn more

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