2013-07-01 18:45:59 +00:00
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---
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language: julia
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author: Leah Hanson
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author_url: http://leahhanson.us
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---
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Julia is a new homoiconic functional language focused on technical computing.
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While having the full power of homoiconic macros, first-class functions, and low-level control, Julia is as easy to learn and use as Python.
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This is based on the current development version of Julia, as of June 29th, 2013.
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```julia
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# Single line comments start with a hash.
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####################################################
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## 1. Primitive Datatypes and Operators
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####################################################
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# Everything in Julia is a expression.
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# You have numbers
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3 #=> 3 (Int64)
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3.2 #=> 3.2 (Float64)
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2 + 1im #=> 2 + 1im (Complex{Int64})
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2//3 #=> 2//3 (Rational{Int64})
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# Math is what you would expect
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1 + 1 #=> 2
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8 - 1 #=> 7
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10 * 2 #=> 20
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35 / 5 #=> 7.0
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5 \ 35 #=> 7.0
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5 / 2 #=> 2.5
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div(5, 2) #=> 2
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2 ^ 2 #=> 4
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12 % 10 #=> 2
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# Enforce precedence with parentheses
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(1 + 3) * 2 #=> 8
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# Bitwise Operators
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~2 #=> -3 # bitwise not
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3 & 5 #=> 1 # bitwise and
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2 | 4 #=> 6 # bitwise or
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2 $ 4 #=> 6 # bitwise xor
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2 >>> 1 #=> 1 # logical shift right
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2 >> 1 #=> 1 # arithmetic shift right
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2 << 1 #=> 4 # logical/arithmetic shift left
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# You can use the bits function to see the binary representation of a number.
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bits(2) #=> "0000000000000000000000000000000000000000000000000000000000000010"
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bits(2.0) #=> "0100000000000000000000000000000000000000000000000000000000000000"
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# Boolean values are primitives
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true
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false
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# Boolean operators
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!true #=> false
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!false #=> true
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1 == 1 #=> true
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2 == 1 #=> false
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1 != 1 #=> false
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2 != 1 #=> true
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1 < 10 #=> true
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1 > 10 #=> false
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2 <= 2 #=> true
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2 >= 2 #=> true
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# Comparisons can be chained
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1 < 2 < 3 #=> true
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2 < 3 < 2 #=> false
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# Strings are created with "
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"This is a string."
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# Character literals written with '
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'a'
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# A string can be treated like a list of characters
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"This is a string"[1] #=> 'T' # Julia indexes from 1
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# $ can be used for string interpolation:
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"2 + 2 = $(2+2)" # => "2 + 2 = 4"
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# You can put any Julia expression inside the parenthesis.
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# Another way to format strings is the printf macro.
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@printf "%d is less than %f" 4.5 5.3 # 5 is less than 5.300000
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####################################################
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## 2. Variables and Collections
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####################################################
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# Printing is pretty easy
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println("I'm Julia. Nice to meet you!")
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# No need to declare variables before assigning to them.
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some_var = 5 #=> 5
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some_var #=> 5
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# Accessing a previously unassigned variable is an error
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some_other_var #=> ERROR: some_other_var not defined
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# Variable Names:
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Some!Other1Var! = 6 #=> 6 # You can use uppercase letters, digits, and exclamation points as well.
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☃ = 8 #=> 8 # You can also use unicode characters
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# A note on naming conventions in Julia:
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# * Names of variables are in lower case, with word separation indicated by underscores ('\_').
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# * Names of Types begin with a capital letter and word separation is shown with CamelCase instead of underscores.
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# * Names of functions and macros are in lower case, without underscores.
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# * Functions that modify their inputs have names that end in !. These functions are sometimes called mutating functions or in-place functions.
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# Arrays store sequences
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li = Int64[] #=> 0-element Int64 Array
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# 1-dimensional array literals can be written with comma-separated values.
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other_li = [4, 5, 6] #=> 3-element Int64 Array: [4, 5, 6]
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# 2-dimentional arrays use space-separated values and semicolon-separated rows.
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matrix = [1 2; 3 4] #=> 2x2 Int64 Array: [1 2; 3 4]
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# Add stuff to the end of a list with push! and append!
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push!(li,1) #=> [1]
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push!(li,2) #=> [1,2]
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push!(li,4) #=> [1,2,4]
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push!(li,3) #=> [1,2,4,3]
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append!(li,other_li) #=> [1,2,4,3,4,5,6]
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# Remove from the end with pop
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pop!(other_li) #=> 6 and other_li is now [4,5]
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# Let's put it back
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push!(other_li,6) # other_li is now [4,5,6] again.
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2013-07-01 20:21:56 +00:00
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li[1] #=> 1 # remember that Julia indexes from 1, not 0!
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li[end] #=> 6 # end is a shorthand for the last index; it can be used in any indexing expression.
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2013-07-01 18:45:59 +00:00
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# Function names that end in exclamations points indicate that they modify their argument.
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arr = [5,4,6] #=> 3-element Int64 Array: [5,4,6]
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sort(arr) #=> [4,5,6]; arr is still [5,4,6]
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sort!(arr) #=> [4,5,6]; arr is now [4,5,6]
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# Looking out of bounds is a BoundsError
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li[0] # ERROR: BoundsError() in getindex at array.jl:270
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# Errors list the line and file they came from, even if it's in the standard library.
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# If you built Julia from source, you can look in the folder base inside the julia folder to find these files.
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# You can initialize arrays from ranges
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li = [1:5] #=> 5-element Int64 Array: [1,2,3,4,5]
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# You can look at ranges with slice syntax.
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li[1:3] #=> [1, 2, 3]
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# Omit the beginning
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li[2:] #=> [2, 3, 4, 5]
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# Remove arbitrary elements from a list with splice!
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splice!(li,2) #=> 2 ; li is now [1, 3, 4, 5]
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# Concatenate lists with append!
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other_li = [1,2,3]
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append!(li,other_li) # Now li is [1, 3, 4, 5, 1, 2, 3]
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# Check for existence in a list with contains
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contains(li,1) #=> true
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# Examine the length with length
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length(li) #=> 7
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2013-07-01 20:21:56 +00:00
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# Tuples are immutable.
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tup = (1, 2, 3) #=>(1,2,3) # an (Int64,Int64,Int64) tuple.
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tup[1] #=> 1
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tup[0] = 3 # ERROR: no method setindex!((Int64,Int64,Int64),Int64,Int64)
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2013-07-01 18:45:59 +00:00
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2013-07-01 20:21:56 +00:00
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# Many list functions also work on tuples
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length(tup) #=> 3
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tup[1:2] #=> (1,2)
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contains(tup,2) #=> true
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2013-07-01 18:45:59 +00:00
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# You can unpack tuples into variables
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2013-07-01 20:21:56 +00:00
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a, b, c = (1, 2, 3) #=> (1,2,3) # a is now 1, b is now 2 and c is now 3
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2013-07-01 18:45:59 +00:00
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# Tuples are created by default if you leave out the parentheses
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2013-07-01 20:21:56 +00:00
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d, e, f = 4, 5, 6 #=> (4,5,6)
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2013-07-01 18:45:59 +00:00
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# Now look how easy it is to swap two values
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2013-07-01 20:21:56 +00:00
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e, d = d, e #=> (5,4) # d is now 5 and e is now 4
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2013-07-01 18:45:59 +00:00
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# Dictionaries store mappings
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empty_dict = {}
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# Here is a prefilled dictionary
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filled_dict = {"one": 1, "two": 2, "three": 3}
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# Look up values with []
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filled_dict["one"] #=> 1
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# Get all keys as a list
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filled_dict.keys() #=> ["three", "two", "one"]
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# Note - Dictionary key ordering is not guaranteed.
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# Your results might not match this exactly.
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# Get all values as a list
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filled_dict.values() #=> [3, 2, 1]
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# Note - Same as above regarding key ordering.
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# Check for existence of keys in a dictionary with in
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"one" in filled_dict #=> True
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1 in filled_dict #=> False
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# Trying to look up a non-existing key will raise a KeyError
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filled_dict["four"] #=> KeyError
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# Use get method to avoid the KeyError
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filled_dict.get("one") #=> 1
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filled_dict.get("four") #=> None
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# The get method supports a default argument when the value is missing
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filled_dict.get("one", 4) #=> 1
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filled_dict.get("four", 4) #=> 4
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# Setdefault method is a safe way to add new key-value pair into dictionary
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filled_dict.setdefault("five", 5) #filled_dict["five"] is set to 5
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filled_dict.setdefault("five", 6) #filled_dict["five"] is still 5
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# Sets store ... well sets
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empty_set = set()
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# Initialize a set with a bunch of values
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some_set = set([1,2,2,3,4]) # filled_set is now set([1, 2, 3, 4])
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# Since Python 2.7, {} can be used to declare a set
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filled_set = {1, 2, 2, 3, 4} # => {1 2 3 4}
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# Add more items to a set
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filled_set.add(5) # filled_set is now {1, 2, 3, 4, 5}
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# Do set intersection with &
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other_set = set{3, 4, 5, 6}
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filled_set & other_set #=> {3, 4, 5}
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# Do set union with |
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filled_set | other_set #=> {1, 2, 3, 4, 5, 6}
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# Do set difference with -
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{1,2,3,4} - {2,3,5} #=> {1, 4}
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# Check for existence in a set with in
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2 in filled_set #=> True
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10 in filled_set #=> False
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####################################################
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## 3. Control Flow
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####################################################
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# Let's just make a variable
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some_var = 5
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# Here is an if statement. INDENTATION IS SIGNIFICANT IN PYTHON!
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# prints "some var is smaller than 10"
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if some_var > 10:
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print "some_var is totally bigger than 10."
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elif some_var < 10: # This elif clause is optional.
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print "some_var is smaller than 10."
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else: # This is optional too.
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print "some_var is indeed 10."
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"""
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For loops iterate over lists
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prints:
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dog is a mammal
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cat is a mammal
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mouse is a mammal
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"""
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for animal in ["dog", "cat", "mouse"]:
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# You can use % to interpolate formatted strings
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print "%s is a mammal" % animal
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"""
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While loops go until a condition is no longer met.
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prints:
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0
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1
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2
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3
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"""
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x = 0
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while x < 4:
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print x
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x += 1 # Shorthand for x = x + 1
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# Handle exceptions with a try/except block
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# Works on Python 2.6 and up:
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try:
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# Use raise to raise an error
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raise IndexError("This is an index error")
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except IndexError as e:
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pass # Pass is just a no-op. Usually you would do recovery here.
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# Works for Python 2.7 and down:
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try:
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raise IndexError("This is an index error")
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except IndexError, e: # No "as", comma instead
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pass
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####################################################
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## 4. Functions
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####################################################
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# Use def to create new functions
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def add(x, y):
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print "x is %s and y is %s" % (x, y)
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return x + y # Return values with a return statement
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# Calling functions with parameters
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add(5, 6) #=> 11 and prints out "x is 5 and y is 6"
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# Another way to call functions is with keyword arguments
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add(y=6, x=5) # Keyword arguments can arrive in any order.
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# You can define functions that take a variable number of
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# positional arguments
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def varargs(*args):
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return args
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varargs(1, 2, 3) #=> (1,2,3)
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# You can define functions that take a variable number of
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# keyword arguments, as well
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def keyword_args(**kwargs):
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return kwargs
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# Let's call it to see what happens
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keyword_args(big="foot", loch="ness") #=> {"big": "foot", "loch": "ness"}
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# You can do both at once, if you like
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def all_the_args(*args, **kwargs):
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print args
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print kwargs
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"""
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all_the_args(1, 2, a=3, b=4) prints:
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[1, 2]
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{"a": 3, "b": 4}
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"""
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# You can also use * and ** when calling a function
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args = (1, 2, 3, 4)
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kwargs = {"a": 3, "b": 4}
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foo(*args) # equivalent to foo(1, 2, 3, 4)
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foo(**kwargs) # equivalent to foo(a=3, b=4)
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foo(*args, **kwargs) # equivalent to foo(1, 2, 3, 4, a=3, b=4)
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# Python has first class functions
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def create_adder(x):
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def adder(y):
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return x + y
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return adder
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add_10 = create_adder(10)
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add_10(3) #=> 13
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# There are also anonymous functions
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(lambda x: x > 2)(3) #=> True
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# There are built-in higher order functions
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map(add_10, [1,2,3]) #=> [11, 12, 13]
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filter(lambda x: x > 5, [3, 4, 5, 6, 7]) #=> [6, 7]
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# We can use list comprehensions for nice maps and filters
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[add_10(i) for i in [1, 2, 3]] #=> [11, 12, 13]
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[x for x in [3, 4, 5, 6, 7] if x > 5] #=> [6, 7]
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####################################################
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## 5. Classes
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####################################################
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# We subclass from object to get a class.
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class Human(object):
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# A class attribute. It is shared by all instances of this class
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species = "H. sapiens"
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# Basic initializer
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def __init__(self, name):
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# Assign the argument to the instance's name attribute
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self.name = name
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# An instance method. All methods take self as the first argument
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def say(self, msg):
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return "%s: %s" % (self.name, msg)
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# A class method is shared among all instances
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|
# They are called with the calling class as the first argument
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@classmethod
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def get_species(cls):
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return cls.species
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# A static method is called without a class or instance reference
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@staticmethod
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def grunt():
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return "*grunt*"
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|
# Instantiate a class
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|
i = Human(name="Ian")
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|
print i.say("hi") # prints out "Ian: hi"
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j = Human("Joel")
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print j.say("hello") #prints out "Joel: hello"
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# Call our class method
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i.get_species() #=> "H. sapiens"
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|
# Change the shared attribute
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|
Human.species = "H. neanderthalensis"
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|
i.get_species() #=> "H. neanderthalensis"
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|
j.get_species() #=> "H. neanderthalensis"
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# Call the static method
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|
Human.grunt() #=> "*grunt*"
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```
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## Further Reading
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Still up for more? Try [Learn Python The Hard Way](http://learnpythonthehardway.org/book/)
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