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Julia for Python Programmers

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Julia for Python Programmers

Here are a few scattered notes on Julia, especially on how it differs from Python.

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One of my clients is writing software in Julia so I’m picking up the language. I looked at Julia briefly when it first came out but haven’t used it for work. My memory of the language was that it was almost a dialect of Python. Now that I’m looking at it a little closer, I can see more differences, though the most basic language syntax is more like Python than any other language I’m familiar with.

Here are a few scattered notes on Julia, especially on how it differs from Python.

  • Array indices in Julia start from 1, like Fortran and R, and unlike any recent language that I know of.
  • Like Python and many other scripting languages, Julia uses # for one-line comments. It also adds #= and =# for multi-line comments, like /* and */ in C.
  • By convention, names of functions that modify their first argument end in !. This is not enforced.
  • Blocks are indented as in Python, but there is no colon at the end of the first line, and there must be an end statement to close the block.
  • Julia uses elseif as in Perl, not elif as in Python.
  • Julia uses square brackets to declare a dictionary. Keys and values are separated with =>, as in Perl, rather than with colons, as in Python.
  • Julia, like Python 3, returns 2.5 when given 5/2. Julia has a // division operator, but it returns a rational number rather than an integer.
  • The number 3 + 4i would be written 3 + 4im in Julia and 3 + 4j in Python.
  • Strings are contained in double quotes and characters in single quotes, as in C. Python does not distinguish between characters and strings, and uses single and double quotes interchangeably.
  • Julia uses function to define a function, similar to JavaScript and R, where Python uses def.
  • You can access the last element of an array with end, not with -1 as in Perl and Python.

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Topics:
python ,big data ,julia ,data science programming

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