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Publications Calendar Research Teaching Zoom LDS

Publications Calendar Research Teaching Zoom LDS

Tuples

• Tuples are like lists but
  • are immutable,
  • are created with ( ) instead of [ ],
  • elements are still accessed with [ ],
  • changing an element, like t[1]=55 gives an error.

t = (1.1, 2.2, 3.3)

• For a tuple with just a single element:
  • Use this: t = (1.1,)
  • Not this: t = (1.1)
• The trailing comma is needed, otherwise t is just 1.1, not a tuple holding 1.1 as the first element.
• For multiple elements, a trailing comma is valid but not required: t = (1, 2, 3,)
  • Lists can also have trailing commas: L = [1, 2, 3,]

Tuple unpacking (mutiple assignment)

• (this works for lists too)

t = (1, 2.5 , -3)         # make a tuple

x, y, z   = t             # unpack the tuple "into" x, y, and z
x, y, z   = 1, 2.5, -3    # same thing
(x, y, z) = t             # same thing
(x, y, z) = (1, 2.5, -3)  # same thing

print(f"x = {x}")
print(f"y = {y}")
print(f"z = {z}")

Note, we used this in returning more than one thing from a function

import numpy as np
def add_and_multiply(x, y):
    return x+y, x*y            # returning a tuple

s, p = add_and_multiply(3,4)   # unpack the tuple into s, p
t = add_and_multiply(3,4)      # t is a tuple


print(s, p)
print(t)

*args

Packing

You can pass an arbitrary number of arguments to a function using the *args parameter.

• The passed arguments get packed into a a tuple called args.

def multiply(*args):
    m = 1
    for a in args:
        m *= a
    return m

print(multiply(1,2,3))
print(multiply(1,2,3,4,5,6))

6
720

Unpacking

Similarly, you can unpack a tuple into several function arguments by by unpacking a tuple.

def print_profile(name, age, hair):
    print(f"name: {name}")
    print(f"age:  {age}")
    print(f"hair: {hair}")

person = ('David', 48, 'brown')

print_profile(*person)              # the tuple person is unpacked into parameters name, age, hair

name: David
age:  48
hair: brown

Dictionaries

• Dictionaries are like lists but
  • are created with { } instead of [ ],
  • use key:value pairs
  • elements are accessed with [key] instead of by [i] for some integer index i,
  • Below, we use strings as the keys, but they can be anything.
• Click here for more information

import numpy as np
mw = {
      "CO2":12.011+15.999*2,
      "H2O":1.0079*2+15.999,
      "O2" :15.999*2,
      "N2" :14.0067*2,
     }

print("mw of o2 is ", mw["O2"])

funcs = {np.sin:"what up sin?", np.log10:np.tanh}  # evil!

mw of o2 is  31.998

Functions:

• mw.keys()
• mw.values()
• mw.items()
• len(mw)

for k in mw.keys():      
    print(k, mw[k])

CO2 44.009
H2O 18.0148
O2 31.998
N2 28.0134

for v in mw.values():
    print(v)

44.009
18.0148
31.998
28.0134

for k, v in mw.items():
    print(k,v)
    
mw.items()

CO2 44.009
H2O 18.0148
O2 31.998
N2 28.0134

dict_items([('CO2', 44.009), ('H2O', 18.0148), ('O2', 31.998), ('N2', 28.0134)])

Check if present

if "H2" in mw:
    print("H2 is there")
else:
    print("H2 is not there")
    

Add items

• mw["new_key"] = newValue

print(mw)

mw["H2"] = 1.0079*2

print(mw)

{'CO2': 44.009, 'H2O': 18.0148, 'O2': 31.998, 'N2': 28.0134}
{'CO2': 44.009, 'H2O': 18.0148, 'O2': 31.998, 'N2': 28.0134, 'H2': 2.0158}

Delete items

• del mw["some_key"]
• mw.pop("some_key")
• mw.popitem() deletes the last inserted item

print(mw)
mw.popitem()
print(mw)

{'CO2': 44.009, 'H2O': 18.0148, 'O2': 31.998, 'N2': 28.0134, 'H2': 2.0158}
{'CO2': 44.009, 'H2O': 18.0148, 'O2': 31.998, 'N2': 28.0134}