Today: Idiomatic phrases, "reverse" chronicles, Better/shorter code invariant, more string functions, unicode

Midterm Monday 10/25 7pm

Today - Better / Shorter / Cleaner

Today, I'll show you some techniques where we have code that is already correct, but we can write it in a better, shorter way. It's intuitively satisfying to have a 10 line thing, and shrink it down to 6 lines that reads better.

Technique: Better/Shorter - Unify Cases

> Better problems

Shorter Code - Better Code

Unify Cases with a Variable

speeding() Example

> speeding()

speeding(speed, birthday): Compute speeding ticket fine as function of speed and birthday boolean. Rule: speed under 55, fine is 100, otherwise 200. If it's your birthday, the allowed speed is 5 mph more. Challenge: change this code to be shorter, not have so many distinct paths.

The code below works correctly. You can see there is one set of lines each for the birthday/not-birthday cases. What exactly is the difference between these two sets of lines?

def speeding(speed, birthday):
    if not birthday:
        if speed < 50:
            return 100
        else:
            return 200
    else:  # is birthday
        if speed < 55:
            return 100
        else:
            return 200

Unify Cases Solution

speeding() Better Unified Solution

def speeding(speed, birthday):
    # Set limit var
    limit = 50
    if birthday:
        limit = 55
    
    # Unified: limit holds value to use.
    # One if-stmt handles all cases
    if speed < limit:
        return 100
    return 200

Demo/Exercise ncopies()

> ncopies()

Change this code to be better / shorter. Look at lines that are similar - make an invariant.

ncopies(word, n, suffix): Given name string, int n, suffix string, return n copies of string + suffix. If suffix is the empty string, use '!' as the suffix. Challenge: change this code to be shorter, not have so many distinct paths.

Before:

def ncopies(word, n, suffix):
    result = ''
    
    if suffix == '':
        for i in range(n):
            result += word + '!'
    else:
        for i in range(n):
            result += word + suffix
    return result

ncopies() Unified Solution

Solution: use logic to set "suffix" to hold the suffix to use for all cases. Later code just uses suffix vs. separate if-stmt for each case.

def copies(word, n, suffix):
    result = ''
    # Set suffix if necessary to value to use
    if suffix == '':
        suffix = '!'
 
    # Unified: one loop, using suffix
    for i in range(n):
        result += word + suffix
    return result

Demo/Exercise match()

> match()

match(a, b): Given two strings a and b. Compare the chars of the strings at index 0, index 1 and so on. Return a string of all the chars where the strings have the same char at the same position. So for 'abcd' and 'adddd' return 'ad'. The strings may be of any length. Use a for/i/range loop. The starter code works correctly. Re-write the code to be shorter.

Before:

def match(a, b):
    result = ''
    if len(a) < len(b):
        for i in range(len(a)):
            if a[i] == b[i]:
                result += a[i]
    else:
        for i in range(len(b)):
            if a[i] == b[i]:
                result += a[i]
    return result

match() Shorter Solution

def match(a, b):
    result = ''
    # Set length to whichever is shorter
    length = len(a)
    if len(b) < len(a):
        length = len(b)

    for i in range(length):
        if a[i] == b[i]:
            result += a[i]

    return result

String - More Functions

See guide for details: Strings

Thus far we have done String 1.0: len, index numbers, upper, lower, isalpha, isdigit, slices, .find().

There are more functions. You should at least have an idea that these exist, so you can look them up if needed. The important strategy is: don't write code manually to do something a built-in function in Python will do for you. The most important functions you should have memorized, and the more rare ones you can look up.

s.startswith() s.endswith()

These are very convenient True/False tests for the specific case of checking if a substring appears at the start or end of a string. Also a pretty nice example of function naming.

>>> 'Python'.startswith('Py')
True
>>> 'Python'.startswith('Px')
False
>>> 'resume.html'.endswith('.html')
True

String - replace()

>>> s ='this is it'
>>> s.replace('is', 'xxx')  # returns changed version
'thxxx xxx it'
>>> 
>>> s.replace('is', '')
'th  it'
>>> 
>>> s        # s not changed
'this is it'

Recall: s.foo() Does Not Change s

Recall how calling a string function does not change it. Need to use the return value...

# NO: Call without using result:
s.replace('is', 'xxx')
# s is the same as it was


# YES: this works
s = s.replace('is', 'xxx')

String - strip()

>>> s = '   this and that\n'
>>> s.strip()
'this and that'

String - split()

>>> s = '11,45,19.2,N'
>>> s.split(',')
['11', '45', '19.2', 'N']
>>> 'apple:banana:donut'.split(':')
['apple', 'banana', 'donut']
>>> 
>>> 'this    is     it\n'.split()  # special whitespace form
['this', 'is', 'it']

String - join()

>>> foods = ['apple', 'banana', 'donut']
>>> ':'.join(foods)
'apple:banana:donut'

String - format()

>>> 'Alice' + ' got score:' + str(12)     # old: + and str()
'Alice got score:12'
>>>
>>> '{} got score:{}'.format('Alice', 12) # new: format()
'Alice got score:12'
>>> 

String Unicode

In the early days of computers, the ASCII character encoding was very common, encoding the roman a-z alphabet. ASCII is simple, and requires just 1 byte to store 1 character, but it has no ability to represent characters of other languages.

Each character in a Python string is a unicode character, so characters for all languages are supported. Also, many emoji have been added to unicode as a sort of character.

Every unicode character is defined by a unicode "code point" which is basically a big int value that uniquely identifies that character. Unicode characters can be written using the "hex" version of their code point, e.g. "03A3" is the "Sigma" char Σ, and "2665" is the heart emoji char ♥.

Hexadecimal aside: hexadecimal is a way of writing an int in base-16 using the digits 0-9 plus the letters A-F, like this: 7F9A or 7f9a. Two hex digits together like 9A or FF represent the value stored in one byte, so hex is a traditional easy way to write out the value of a byte. When you look up an emoji on the web, typically you will see the code point written out in hex, like 1F644, the eye-roll emoji 🙄.

You can write a unicode char out in a Python string with a \u followed by the 4 hex digits of its code point. Notice how each unicode char is just one more character in the string:

>>> s = 'hi \u03A3'
>>> s
'hi Σ'
>>> len(s)
4
>>> s[0]
'h'
>>> s[3]
'Σ'
>>>
>>> s = '\u03A9'  # upper case omega
>>> s
'Ω'
>>> s.lower()     # compute lowercase
'ω'
>>> s.isalpha()   # isalpha() knows about unicode
True
>>>
>>> 'I \u2665'
'I ♥'

For a code point with more than 4-hex-digits, use \U (uppercase U) followed by 8 digits with leading 0's as needed, like the fire emoji 1F525, and the inevitable 1F4A9.

>>> 'the place is on \U0001F525'
'the place is on 🔥'
>>> s = 'oh \U0001F4A9'
>>> len(s)
4

Ethics of Generosity and Unicode

Generosity is Good

History of Unicode and Python

The history of ASCII and Unicode is an example of ethics.

ASCII

In the early days of computing in the US, computers were designed with the ASCII character set, supporting only the roman a-z alphabet. This hurt the rest of the planet, which mostly doesn't write in English. There is a well known pattern where technology comes first in the developed world, is scaled up and becomes inexpensive, and then proliferates to the developing world. Computers in the US using ASCII hurt that technology pipeline. Choosing a US-only solution was the cheapest choice for the US in the moment, but made the technology hard to access for most of the world. This choice is somewhere between ungenerous and unethical.

Unicode Technology

Unicode takes 2-4 bytes per char, so it is more costly than ASCII. Cost per byte aside, Unicode is a good solution - a freely available standard. If a system uses Unicode, it and its data can interoperate with the other Unicode compliant systems.

Unicode vs. RAM Costs vs. Moore's Law

The cost of supporting non-ASCII data can be related to the cost of the RAM to store the unicode characters. In the 1950's every byte was literally expensive. An IBM model 360 could be leased for $5,000 per month, non inflation adjusted, and had about 32 kilobytes of RAM (not megabytes or gigabytes .. kilobytes!). So doing very approximate math, figuring RAM is half the cost of the computer, we get a cost of about $1 per byte per year.

>>> 5000 * 12 / (2 * 32000)
0.9375

So in 1950, Unicode is a non-starter. RAM is expensive.

RAM Costs Today

What does the RAM in your phone cost today? Say your phone costs $500 and has 8GB of RAM (conservative). Say the RAM is all the cost and the rest of the phone is free. What is the cost per byte?

The figure 8 GB is 8 billion bytes. In Python, you can write that as 8e9 - like on your scientific calculator.

>>> 500 / 8e9   # 8 GB
6.25e-08
>>> 
>>> 500 / 8e9 * 100  # in pennies
6.2499999999999995e-06

RAM costs nothing today - 6 millionths of a cent per byte. This is the result of Moore's law. Exponential growth is incredible.

Unicode Makes Sense in 1990s

Sometime in the 1990s, RAM was cheap enough that spending 2-4 bytes per char was not so bad, and around then is when Unicode was created. Unicode is a standard way of encoding chars in bytes, so that all the Unicode systems can transparently exchange data with each other.

With Unicode, the tech leaders were showing a little generosity to all the non-ASCII computer users out there in the world.

Generosity and Python Story

With Unicode, there is just one Python that works in every country. A world of programmers contribute to Python as a free, open source software. We all benefit from that community, vs. each country maintaining their own in-country programming language, which would be a crazy waste of duplicated effort.

Ethic: Generosity

So being generous is the right thing to do. But the story also shows, that when you are generous to the world, that generosity may well come around and help you as well.