1. Computation with strings 3 Day 4 - 9/07/16
LING 3820 & 6820
Natural Language Processing
Harry Howard
Tulane University

2. Course organization http://www.tulane.edu/~howard/NLP/
Schedule of assignments
Is there anyone here that wasn't here last week?
NLP, Prof. Howard, Tulane University
07-Sep-2016

3. Scripts for the example code
How to use a script in Spyder
NLP, Prof. Howard, Tulane University
07-Sep-2016

4. §4. Computation with strings
What is a string?
A string is a sequence of characters delimited between single or double quotes.
NLP, Prof. Howard, Tulane University
07-Sep-2016

5. Practice 2
1. Write the code to perform the changes given below on these two strings, but try to using slicing rather than stripping:
>>> S = 'ABCDEFGH' >>> s = 'abcdefgh'
a. Make the first 3 characters of S lowercase.
>>> S[:3].lower()
b. Make the last 4 characters of s uppercase.
>>> s[4:].upper()
c. Create a string from the first 4 characters of S and the last 4 characters of s and then switch its case.
>>> S[:4]+s[4:].swapcase()
'ABCDEFGH'
>>> (S[:4]+s[4:]).swapcase()
'abcdEFGH'
d. Concatenate both strings and slice out every even character.
>>> (S+s)[1::2]
e. Concatenate both strings and reverse the order of the characters.
>>> (S+s)[::-1]
f. Retrieve the index of ‘E’ and ‘h’.
>>> S.index('e')
>>> s.index('h')
NLP, Prof. Howard, Tulane University
07-Sep-2016

6. Practice 2, cont.
Slice the string ‘Nov. 1, 1957’ into month (a string), day (an integer), and year (an integer).
month = str[:3]
day = int(str[5])
year = int(str[-4:])
Use this sort of embedded index/find() to slice the following strings out of E:
E[E.find('ab'):2]
E[E.rfind('bc'):E.rfind('d')]
E[E.find('d'):]
NLP, Prof. Howard, Tulane University
07-Sep-2016

7. Practice 2, cont.
5 a) s[:s.find('tion')]
b) p[p.find('anti'):] returns whole word
c) s.strip('tion'), p.strip('anti')
6) w2[len('anti'):], w1[:-len('tion')]
7) What is the longest sequence of operators that you can make?
NLP, Prof. Howard, Tulane University
07-Sep-2016

8. Practice 3
1. Show which of len(), sorted(), and set() takes the most time to process.
>>> timeit.timeit(f3)
>>> timeit.timeit(f4)
>>> timeit.timeit(f5)
NLP, Prof. Howard, Tulane University
07-Sep-2016

9. Practice 3, cont.
In Operator iteration there is a line with the expression L[2:6].capitalize().upper(). Show whether it is faster for Python to process it as it is, or broken into its more-easily-readable parts.
>>> timeit.timeit(f6)
>>> timeit.timeit(f7)
NLP, Prof. Howard, Tulane University
07-Sep-2016

10. Practice 3, cont.
3. Recall the discussion of the default precedence of * and + in Operator precedence. Perhaps * comes first because it is quicker to process than +. Test this hypothesis by writing a function for either combination of * and + and time them to see which runs faster.
>>> timeit.timeit(f8)
>>> timeit.timeit(f9)
NLP, Prof. Howard, Tulane University
07-Sep-2016

11. Practice 4
# 1. Combine them into a single string with proper spacing for two sentences. Check it with print.
>>> lim = L1+' '+L2+' '+L3+' '+L4+' '+L5
>>> print lim
# 2. Now combine them into a single string so that each one prints out on its# own line. This is very hard to do, but the answer is hidden in line 20 above.
>>> lim2 = L1+' '+L2+'\n'+L3+' '+L4+' '+L5
>>> print lim2
# Finally, modify the string you developed in #2 so so it prints out to the conventional form of limericks, [NEW!] five lines with the third and forth indented by two spaces.
>>> lim3 = L1+'\n'+L2+'\n '+L3+'\n '+L4+'\n'+L5
>>> print lim3
NLP, Prof. Howard, Tulane University
07-Sep-2016

12. 4.6.4. Practice 5 Which of these are illegitimate names?:
Mutability prevents you from slicing a character into a string, but there is still a sneaky way of transforming ‘name’ into ‘game’. Do you recall it?
>>> 'name'.replace('n','g')
NLP, Prof. Howard, Tulane University
07-Sep-2016

13. Practice 6
Take a look at English terms with diacritical marks, select a (lowercase) word with a non-ascii character in it and see if you can print it to the console as uppercase.
NLP, Prof. Howard, Tulane University
07-Sep-2016

14. Next time Finish §4 and remaining practices.
NLP, Prof. Howard, Tulane University
07-Sep-2016