Today: python copying/nesting, better/shorter code, flex-arrow drawing example
#Use comments to fill in information that is useful or interesting and not clear from the code itself. These are not needed too often, since frequently the code is readable enough on its own with good function and variable names.
1. Avoid repeating what the code says. Don't do this:
i = i + 1 # Add 1 to i
2. Could mention what a line accomplishes - not so obvious sometimes - describing the higher-level goal of the code:
# Increase i to the next multiple of 10
i = 10 * (i // 10 + 1)
3. Could mention the goal of a group lines, framing what goal the next 8 lines accomplish. Can also use blank lines to separate logical stages from each other.
# Advance i to end of email address
i = at + 1
while i < len(s) and ....
...
1. Say we have a word variable. The following if-statement will work perfectly for CS106A, and you probably wrote it that way before, and it's fine and we will never mark off for it.
if word == None: # Works fine, not PEP8
print('Nada')
2. However, there is a very old rule in PEP8 that comparisons to the value None should be written with the is operator. This is an awkward rule, but we are stuck with it. You may have noticed PyCharm complaining about the above form, so you can write it as follows and it works correctly and is PEP8:
if word is None: # Works fine, PEP8
print('Nada')
if word is not None: # "is not" variant
print('Not Nada')
Very important limitation:
3. The is operator is different from == for most non-None values like strings and ints and lists and it is not reliable. Therefore:
Never use the is operator for values other than None.
Never, never, never, never.
Only use is with None as above. If you use it with other values, it will lead to horrific, weekend-ruining bugs.
There's a longer explanation about this awkward "is" rule in the guide page above.
>>> a = 'Python' >>> b = 'Py' >>> >>> a[;2] 'Py' >>> >>> a[:2] == b # == works True >>> >>> a[:2] is b # "is" does not work False >>> >>> x = none >>> x is None # "is" works with None True >>>
See Python copy/is chapter for the details.
Not showing any new python, but showing moves and patterns you may not have thought of to shorten and clean up your code.
Many of these techniques involve leveraging variables to clean up the code.
I'm going to show you a v1 form of the code that is suboptimal and then how to write it better. Nobody should feel bad for writing the suboptimal form, as it's en easy enough path to go down by accident.
first_n(s, n): Given a string s and an int n. The n parameter will be one of 1, 2, 3, 4. Return a string of the first n chars of s. If s is not long enough to provide n chars, return None.
'Python', 1 -> 'P' 'Python', 2 -> 'Py' 'Python', 3 -> 'Pyt' 'Python', 4 -> 'Pyth' 'Py', 3 -> None
Here is v1 which works perfectly, but is not the best.
def first_n(s, n):
if len(s) < n:
return None
if n == 1:
return s[:1]
if n == 2:
return s[:2]
if n == 3:
return s[:3]
if n == 4:
return s[:4]
Note: we don't need an if/elif here, since the "return" exits the function when an if-test succeeds.
When n is 1, want an 1 in the slice. When n is 2, want an 2 in the slice. How can we get that effect?
The variable n points to one of the values 1, 2, 3, 4 when this function runs.
Therefore, in your code, if there is a spot where you need a value that appears in a variable or parameter, you can just literally write that variable there.
def first_n(s, n):
if len(s) < n:
return None
return s[:n]
If n is 1, uses 1 in the slice. If n is 2, it uses 2, and so on. Use the variable itself, knowing that at run-time, Python will evaluate the variable, pasting in whatever value it points to.
We mentioned this strategy before. It's a common CS106A technique.
Your algorithm has a few values flowing through it. Pick a value out and put it in a well-named variable. Use the variable on the later lines.
1. Helps readability - the named variable helps all the later lines read out what they do.
2. In the style of divide-and-conquer, computing a value that is part of the solution and storing it in a variable - you have picked off and solved a smaller part of the problem, and then put that behind you to work on the next thing.
Q: Given a list lst, what is the index of the first element in the list?
A: 0
Q: Given a list lst, what is the index of the last element in the list?
A: len(lst) - 1
For example, if the length is 10, the first element is at 0, the last element is at 9. This is just zero-based indexing showing up again.
Essentially:
nums[0] -> low nums[len(nums) 1] -> high Adjust numbers outside of low..high range [0, 7, -2, 12, 3, -3, 5] -> [0, 5, 0, 5, 3, 0, 5]
Given nums, a list of 1 or more numbers. We'll say the first number in the list is the desired lower bound (low), and the last number is the desired upper bound (aka high). Change the list so any number less than low is changed to low, and likewise for any number greater than high. Return the changed list. Use for/i/range to loop over the elements in the list. Use an add-var strategy to introduce variables for the bounds.
Here is a v1 solution that works, but I would never write it this way.
def low_high(nums):
for i in range(len(nums)):
if nums[i] < nums[0]:
nums[i] = nums[0]
if nums[i] > nums[len(nums) - 1]:
nums[i] = nums[len(nums) - 1]
return nums
This code is not especially readable. The many details on each line make it hard to see what is going on.
Introduce variables low and high to store those intermediate values, using the variables on the later lines. This is much more readable.
def low_high(nums):
low = nums[0]
high = nums[len(nums) - 1]
for i in range(len(nums)):
if nums[i] < low:
nums[i] = low
if nums[i] > high:
nums[i] = high
return nums
Which is easier to write without bugs, knowing that you might sometimes forget a -1 or get < and > backwards.
v1:
if nums[i] > nums[len(nums) - 1]:
nums[i] = nums[len(nums) - 1]
v2:
if nums[i] > high:
nums[i] = high
The version building on the variable is (a) readable and (b) easier to write correctly the first time. Readability is not just about reading, it's about writing it with fewer bugs as you are typing.
On our lecture examples we do this constantly - pulling some intermediate value into a well-named variable to use on later lines.
Your computation has natural partial results. Storing these in variables with good names make better code.
Say your code is not working, and you are trying to fix it, and you are running out of ideas. There is some long line of code, and you are not sure if it is right. Try pulling a part of that computation out, looking at just that bit carefully, and storing it in a variable.
What was a long horizontal line, you stretch out vertically into an increased number of shorter lines, better able to concentrate on one part at a time.
Notice that v1 is short but wide. In contrast, v2 is longer because of the 2 added lines to set the variables, but more narrow since the later lines have less on therm.
Say we want to set alarm differently for weekends, something like this:
if not is_weekened:
alarm = '9:00 am'
else:
alarm = 'off'
The above code is fine. Here I will propose a slightly shorter way way will use often. (1) Initialize (set) the variable to its common, default value first. (2) Then an if-statement detects the case where the var should e set to a different value.
alarm = '9:00 am'
if is_weekend:
alarm = 'off'
if case-1:
lines-a
...
...
if case-2:
lines-b
...
...
grounded(minutes, is_birthday): Given you came home minutes late, how many days of grounded are you. If minutes is an hour or less, grounding is 5, otherwise 10. Unless it is your birthday, then 30 extra minutes are allowed. Challenge: change this code to be shorter, not have so much duplicated code.
The code below works correctly. You can see there is one set of lines for the birthday case, and another set of similar lines for the not-birthday case. What exactly is the difference between these two sets of lines?
def grounded(minutes, is_birthday):
if not is_birthday:
if minutes <= 60:
return 5
return 10
# is birthday
if minutes <= 90:
return 5
return 10
1. Set limit first. 2. Then unified lines below use limit, work for all cases.
def grounded(minutes, is_birthday):
limit = 60
if is_birthday:
limit = 90
if minutes <= limit:
return 5
return 10
ncopies: word='bleh' n=4 suffix='@@' -> 'bleh@@bleh@@bleh@@bleh@@' ncopies: word='bleh' n=4 suffix='' -> 'bleh!bleh!leh!bleh!'
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.
Change this code to be better / shorter. Look at lines that are similar - make a unified version of those lines.
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
Solution: use logic to set an ending variable to hold what goes on the end for all cases. Later, unified code uses that variable vs. separate if-stmt for each case. Alternately, could use the suffix parameter as the variable, changing it to '!' if it's the empty string.
def ncopies(word, n, suffix):
result = ''
ending = suffix
if ending == '':
ending = '!'
for i in range(n):
result += word + ending
return result
> 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.
match(): 'abcd' 'adddd' -> 'ad' 01234
Code before unify:
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
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
Introduce a technique we'll need soon.
for i/range vs. whileThe for/i/range form is great for going through numbers which you know ahead of time - a common pattern in real programs. If you need to go through 0..n-1 - use for/i/range, that's exactly what it's for.
for i in range(n):
# i is 0, 1, 2, .. n-1
while Loop - FlexibleBut we also have the while loop. The "for" is suited for the case where you know the numbers ahead of time. The while is more flexible. The while can test on each iteration, stop at the right spot. Ultimately you need both forms, but here we will switch to using while.
It's possible to write the equivalent of for/i/range as a while loop instead. This is not a good way to go through 0..n-1, but it does show a way to structure a while loop.
Here is the while-equivalent to for i in range(n)
i = 0 # 1. init
while i < n: # 2. test
# use i
i += 1 # 3. increment loop-bottom
# (easy to forget this line)
double_char() written as a while. The for-loop is the correct approach here, so we are just showing how a "for" can written with "while".
1. Init i = 0
2. Test i < n
3. Increment i += 1 (loop bottom)
def while_double(s):
result = ''
i = 0
while i < len(s):
result += s[i] + s[i]
i += 1
return result
Maybe get to this
i < lengthWith zero based indexing, if we are increasing an index variable i, then i < length is the easy test that i is a valid index; that it is not too big.
Look at our old 'Python' str example
If we are increasing an index number, 5 is the last valid index. When we increase it to 6 it's past the end of the string. The length here is 6, so in effect i < 6 checks that i is valid if we are increasing i.
If we are decreasing i, then i >= 0 is the valid check, since 0 is the first index.