Today: tuples, dict.items() output pattern, lambda, map, one-liners

Dict Square Bracket Nesting

Say for our building we have a "temps" dict with a key for each room - 'room1', 'room2', etc. The value for each room is a nested dict of the sensors in the at room 't1', 't2, with the value being the temperature.

>>> d = {'room1': {'t1': 100, 't2': 102}}

Q1 - Access 'room1'

Q: What is an expression to access the nested 'room1' dict?

A: This is what square brackets do, so it's dict[key], or in this case: d['room1']

Q2 - Access 't1' in 'room1'

Q: What is an expression to get the temperature of sensor 't1' in 'room1'?

A: The square brackets work left-to-right. So the expression d['room1'] points to the inner, nested dict. You can add another pair of brackets on the right to access inside the nested dict"

>>> d = {'room1': {'t1': 100, 't2': 102}}
>>> 
>>> d['room1']             # access nested
{'t1': 100, 't2': 102}
>>> 
>>> d['room1']['t1']       # access ['t1'] inside nested
100

Q3: Average Temperature

Q: Write an expression to compute the average temperature of average temp of t1 and t2 in room1?

Answer:

>>> # As above, this accesses one temp
>>> d['room1']['t1']
100
>>>
>>> # Compute average
>>> (d['room1']['t1'] + d['room1']['t2']) / 2
101.0

Q4: Average Temperature With Var

Can store a reference to the nested dict in a var, then use that. We typically do it this way.

>>> # Get a reference to room1 dict, store in var
>>> temps = d['room1']
>>> (temps['t1'] + temps['t2']) / 2
101.0
>>>

Tuples

For more detail see guide Python Tuples

• Written with parenthesis
  e.g. (1, 2, 'a')
  e.g. ('Alex Smith', 12432255)
• Similar to list:
  len(), [ ] work the same
• Fixed size, typically small
• Sometimes have different types inside
• Immutable - no change, no append

>>> t = ('a', 13, 42)
>>> t[0]
'a'
>>> t[2]
42
>>> len(t)
3
>>> t[0] = 'b'
TypeError: 'tuple' object does not support item assignment

Tuple Optional Parenthesis

It's possible to omit the parenthesis when writing a tuple. We will not do this in CS106A code, but you can write it if you like and it is allowed under PEP8. We will write our code more spelled-out, showing explicitly when creating a tuple.

>>> t = 1, 4     # This works
>>> t
(1, 4)
>>> t = (4, 5)   # I prefer it spelled out lik this
>>> t            # PEP8 says parenthesis optional
(4, 5)

Tuple Assignment = Shortcut

Here is a neat sort of trick you can do with a tuple. This is a shortcut for the use of =, assigning multiple variables in one step. This is just a little trick, not something you need to use.

>>> (x, y) = (3, 4)
>>> x
3
>>> y
4

• It's an error if the two sides are not the same len
• Works with lists too
• A bit obscure, you do not need to use this feature
• But handy sometimes (below)

Tuples vs. List

They look so similar, but have some real differences. When do you use a list and when a tuple?

When To Use List?

• List contains many elements, possibly a large number
• Number of elements maybe not known ahead of time
• Want .append() to add more
• Typically elements are all the same type
  Same-type is not a Python requirement, but it's a good practice
• List Examples:
• Store many urls - list of strings
  ['http://foo.com', 'http://kitten.org/bleh', ...]
• Store many weights - list of floats
  [34.5, 12.0, 16, ...]
• Store many filenames - list of strings
  ['poem.txt', 'jokes.html', ... ]

When To Use Tuple?

• Tuple contains a small, fixed number of elements
• The number of elements is known ahead of time
• Elements may not all be the same type
• Store sunet and id number together - tuple
  ('sally22', 123456)
• Store 3 float x,y,z coordinates all together - tuple
  (4, 5.2, 6.1)
• Store filename of an mp3 file and its length in seconds together - tuple
  ('happy.mp3', 240)

Revisit Dict, now that we have tuples

Dict Output Pattern #1

Say we have a dict loaded up with data

>>> d = {'a': 'alpha', 'g': 'gamma', 'b': 'beta'}

Here is the dict-print code we used before. This is a fine, standard pattern you can continue to use. But we are going to look at another way.

>>> for key in sorted(d.keys()):
...     print(key, d[key])
... 
a alpha
b beta
g gamma

Revisit Dict Output: keys() values() items()

• How to get data out of dict?
• 1. d.keys(), or sorted(d.keys())
• 2. d.values() - collection of just values (same order as d.keys())
• 3. d.items() - look at this one below
• These are all "list-like" collections
  The list-like collections work with for-loop and in
  But they are not lists, no [], no .append()
• If need a list, use list() to covert like this
  list(d.keys())

>>> d = {'a': 'alpha', 'g': 'gamma', 'b': 'beta'}
>>>
>>> d.keys()
dict_keys(['a', 'g', 'b'])
>>> sorted(d.keys())
['a', 'b', 'g']
>>>
>>> d.values()
dict_values(['alpha', 'gamma', 'beta'])
>>> 

dict.items()

• d.items() is collection of key/value pairs, each a tuple len-2
• d.items() returns all the dict data keys + values
• sorted(d.items()) - sorts the pairs by key - useful form

>>> d = {'a': 'alpha', 'g': 'gamma', 'b': 'beta'}
>>> 
>>> d.items()          # (key, value) tuples - all the data
dict_items([('a', 'alpha'), ('g', 'gamma'), ('b', 'beta')])
>>> 

Sorting With Tuples

• Sorting of tuples
• 1. Sorts on tuple[0] first across all tuples
• 2. If tuple[0] is the same between two elements
  Fall back to sorting on tuple[1] and so on
• Lets us combine multiple data items for sorting
• Say we have len-2 tuples of the form: ('ca', 'palo alto')
• Try sorting these tuples

>>> cities = [('tx', 'houston'), ('ca', 'palo alto'), ('ca', 'san jose'), ('tx', 'austin'), ('ca', 'aardvark')]
>>> 
>>> sorted(cities)
[('ca', 'aardvark'), ('ca', 'palo alto'), ('ca', 'san jose'), ('tx', 'austin'), ('tx', 'houston')]
>>> 
>>> sorted(cities, reverse=True)
[('tx', 'houston'), ('tx', 'austin'), ('ca', 'san jose'), ('ca', 'palo alto'), ('ca', 'aardvark')]

sorted(d.items())

Recall that d.items() is a list of len-2 (key, value) tuples in random order:

>>> d.items()                      # random order
[('a', 'alpha'), ('g', 'gamma'), ('b', 'beta')]

Since sorting of tuples goes by [0] first, and [0] here is the key, the len-2 tuples are in effect sorted by key:

>>> sorted(d.items())              # sorted by key
[('a', 'alpha'), ('b', 'beta'), ('g', 'gamma')]

So it just sorts by the key first. The sorting in this case just uses the key in each tuple, [0], never needing to look at [1], since the key values are all different.

Dict Output Code #2-Almost

• Say we want to output a dict
• Use sorted(dict.items() instead of dict.keys()
  Get (key, value) len-2 tuples
• Items has all the data in one step - nice
• item[0] is key, item[1] is value
• You can use this form, but there's a shortcut below

>>> for item in sorted(d.items()):
...     print(item[0], item[1])
... 
a alpha
b beta
g gamma

Dict Output Code #2

Recall the shortcut

>>> (a, b) = (6, 7)
>>> a
6
>>> b
7

Can use a similar shortcut inside a for loop. Since we are looping over tuples len-2, can specify two variables, and the loop unpacks each tuple into the variables, here key and value:

>>> for key, value in sorted(d.items()):
...     print(key, value)
... 
a alpha
b beta
g gamma

The above phrase is the second way to do dict output, using .items().

It's handy that the .items() gets all the data, so and we don't need to look up the value in the loop. Also it's nice that the key and value are unpacked into the variables in the loop. This is just a shortcut, nothing you need to use.

Look at the wordcount.py example - both the sorted(d.keys()) and sorted(d.items()) phrases are shown for printing out a dict.

Map/Lambda - Advanced Hacker Features

Map - a short way to transform a list - handy, but not super important

Lambda - an important way to package some code. Today we'll use map() to explore how lambda works

Lambda - Dense and Powerful

Lambda code is dense. Another way of saying that it is powerful. Sometimes you feel powerful with computer code because the code you write is long. Sometimes you feel even a little more powerful, because the code you write is short!

Dense One-Liner Code Solutions

There is something satisfying about solving a real problem with 1 line of code. The 1-liner code is so dense, we'll will write it a little more deliberately. See how this works below!

What is a def?

Consider the following "double" def. What does this provide to the rest of the program?

def double n:
    return n * 2

The def sets up the name of the function, and associates it with that body of code. Later line can refer to this function by name. The drawing below shows a form of this - the name "double" now points to this black-box of code that anybody can call.

double() - How Many Params? How Many Outputs?

Answer: takes in one parameter value. Returns one value.

>>> # Normally don't def a function in the interpreter.
>>> # But it works for little demos like this.
>>>
>>> def double(n):
...   return n * 2
... 
>>> 
>>> double(10)
20
>>> double(144)
288

1. map(fn, list-like)

• map() takes in:
• 1. Takes in a reference to a function
• 2. Takes in any list-like collection
• Runs that function over the list
• Calling the passed-in function once for each element
• Gathers the outputs into a list-like which is returned

A visual of what map() does

map(double, [1, 2, 3, 4, 5]) -> [2, 4, 6, 8, 10]

Aside: map() Result + list()

• The result that map() returns is not a list exactly and does not display clearly in the interpreter
• Therefore we call it like this in the interpreter
• list(map(...))
• Thus making a list of the map() result so it prints out correctly
• This use of list() is not needed generally, we're just doing it here for the printing

map() Examples

>>> # We have a "double" def
>>> def double(n):
...   return n * 2
... 
>>>
>>> map(double, [1, 2, 3, 4, 5])
<map object at 0x7f9a25969910>     # why we need list()
>>> 
>>> list(map(double, [1, 2, 3, 4, 5]))
[2, 4, 6, 8, 10]
>>> 
>>> list(map(double, [3, -1, 10]))
[6, -2, 20]
>>> 
>>> list(map(double, range(20)))
[0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38]
>>> 

map() Example 2 - exclaim()

Say we have an exclaim(s) function that takes in a string and returns it uppercase with an exclamation mark at the end. Use map to run exclaim() over a list of strings.

>>> def exclaim(s):
...   return s.upper() + '!'
... 
>>>
>>> list(map(exclaim, ['hi', 'woot', 'donut']))
['HI!', 'WOOT!', 'DONUT!']
>>> 
>>> list(map(exclaim, ['meh']))
['MEH!']

Thus Far - Ok

The map() function saves us some boilerplate - if we have a function, it takes care of the not too difficult job or running it over a list of inputs, giving us a list of outputs. This is a first example of passing a function in to another function as a parameter, which turns out to be an important advanced technique.

Enter the Lambda

Lambda Niche

• In the examples above
• 1. Do the def first, define the name + code we want to use
• 2. Then later in the code, map() refers to that name and maps the code over the list
• If the code is short, it would be nice to do the whole thing in one place
• Read on!
• Dense/Powerful code ahead!

Lambda History

• History: Alonzo Church 1930
  Lambda Calculus
• Church studied computation before computers were invented, used lambda as a notation
• Now lambda is a way to make 1-line function in Python
• Without a def
• Great for places where you need a little function
• Continue to use def for regular functions

Lambda 1-2-3

• "lambda" is a stripped-down syntax to define computation in 1 line
• lambda has the absolute minimum needed
• Below is a lambda which defines code to double a number
• Syntax:
• 1. The word "lambda"
• 2. A single parameter and colon
• 3. An expression defining the output of the lambda, no "return"
• All of today's lambdas will have 1 parameter
  Possible to have different numbers, but 1 is very common
• Lambda is great where you want a tiny function

Here is a lambda that takes in a number, returns double that number

lambda n: 2 * n

Lambda Black Box

It's like the lambda just defines the black box code, not bothering with giving it name.

Lambda works with map()

Want to double a bunch of numbers? Instead of a separate def, write the lambda inside the map() like this:

>>> list(map(lambda n: n * 2, [1, 2, 3, 4, 5]))
[2, 4, 6, 8, 10]

How To Write Lambda - 1, 2, 3

1. "lambda"

Write the word "lambda"

2. Param:

• What is the lambda input?
• Give the lambda param a good name, followed by colon
• A an int - "n:"
• A string - "s:"
• A mass in kilograms - "mass:" or "kg:"
• Having a good name helps with the next step

3. Expression

• Write the expression for the output
• Fit on one line, use the param
• No "return"
• If the code is long .. consider using a "def" see below

Lambda Examples in Interpreter

Do these in interpreter >>>. Just hit the up-arrow to change the body of the lambda.

>>> nums = [1, 2, 3, 4]
>>> 
>>> # n * 10
>>> list(map(lambda n: n * 10, nums))
[10, 20, 30, 40]
>>>
>>> # n * -1
>>> list(map(lambda n: n * -1, nums))
[-1, -2, -3, -4]
>>> 
>>> # 100 - n
>>> list(map(lambda n: 100 - n, nums))
[99, 98, 97, 96]
>>>
>>>

Lambda String Examples

Have a list of strings. Map a lambda over this list. What is the parameter to the lambda? One string. Whatever the lambda returns, that's what makes up the list of results.

>>> strs = ['Banana', 'apple', 'Zebra', 'coffee', 'Donut']
>>> 
>>> list(map(lambda s: s.lower(), strs))
['banana', 'apple', 'zebra', 'coffee', 'donut']
>>> 
>>> list(map(lambda s: s[0], strs))
['B', 'a', 'Z', 'c', 'D']
>>> 
>>> # Works with strings - change param name to "s"
>>> list(map(lambda s: s.upper() + '!', ['hi', 'ho', 'meh']))
['HI!', 'HO!', 'MEH!']
>>>

Examples / Exercises - Map Lambda

These are true one-liner exercises. We'll do a few of them in class, and you can look at the others in the lambda1 section.

Solve these with a 1-line call to map() for each. Do not call list(), that was needed in the interpreter, but here just map() works.

> lambda1 exercises

For reference, here is the syntax for our "double" example:

map(lambda n: 2 * n, [1, 2, 3, 4, 5])

Do these: squared(), diff21() (int)

> squared exercises

> diff21 exercises

Then strings: first2x(), first_up() (str)

> first2x exercises

> first_up exercises