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  • # Simple arithmetic
>>> 1 / 2
0.5
>>> 2 ** 3
8
>>> 17 / 3  # true 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.

  • # 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

  • # 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

  • # 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

  • # Simple output (with Unicode)
>>> print("Hello, I'm Python!")
Hello, I'm Python!

# Input, assignment
>>> name = input('What is your name?\n')
>>> print(f'Hi, {name}.')
What is your name?
Python
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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Generating realistic location data for users for testing or modeling simulations is a hard problem. Current approaches just create random locations inside a box, placing users in waterways or on top of buildings. This inability to make accurate, synthetic location data stifles a lot of innovative projects that require diverse and complex datasets to fuel their work.

Using Python with Gretel.ai to Generate Synthetic Location Data by Alex Watson, co-founder and CPO, Gretel.ai

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