I need help with this lab assignment it must be in python Dave Jeffery will be a
ID: 3732077 • Letter: I
Question
I need help with this lab assignment it must be in python
Dave Jeffery will be at a conference on March 16, 2018.
Class will meet in ARSC 124 at the normal time to work on Lab 9. Blackboard will record your activity.
You need to:
Work through the dictionary example code (below) using the Python Shell
Download the Lab 9 starting Python file
Change the author and date
Document input, output, and calculations
Work as a class to develop a plan on how to solve the problem. Use the white board to develop ideas. Your design should include a dictionary that has each word as the key and the value should be a list of the lines where the word occurs.
Document your design in the Python comments
Begin writing the Python code to implement your design
Lab 9 Practice
# Create a Dictionary and add entries
fun = {}
fun["open"] = "Open a file and return a stream"
fun["print"] = "Prints values to a stream"
fun["int"] = "Convert a string or number to an integer"
fun["len"] = "Return the number of items"
fun["junk"] = "Junk. To be deleted"
# Display the contents of an entry in the dictionary
print(fun["open"])
print(fun["int"])
# Remove entries in a dictionary
fun.pop("junk")
# Loop through a dictionary
for key in fun:
print(key + "() ", fun[key])
# Display all of the keys in a list
list(fun.keys())
# Display all of the values in a list
list(fun.values())
"""
Program: Lab9Start
Author: <author>
Date: <date>
Description:
Lab 9 is to read in a text file and provide a list of the unique
words in the file and the line numerbs where those words appear.
=============
ANALYSIS
=============
Input:
Output:
Calculations:
=============
DESIGN
=============
1.
2.
3.
4.
5.
6.
7.
"""
# Request the input file name
# Open the input file and initialize dictionary of unique words
# Add the unique words in the file to the dictionary
# Print the unique words in alphabetical order along
# with their line numbers
# Close all files
'''
Python Quick Reference
https://github.com/justmarkham/python-reference
By Kevin Markham (kevin@dataschool.io)
http://www.dataschool.io
Table of Contents:
Imports
Data Types
Math
Comparisons and Boolean Operations
Conditional Statements
Lists
Tuples
Strings
Dictionaries
Sets
Defining Functions
Anonymous (Lambda) Functions
For Loops and While Loops
Comprehensions
Map and Filter
'''
### IMPORTS ###
# 'generic import' of math module
import math
math.sqrt(25)
# import a function
from math import sqrt
sqrt(25) # no longer have to reference the module
# import multiple functions at once
from math import cos, floor
# import all functions in a module (generally discouraged)
from csv import *
# define an alias
import datetime as dt
# show all functions in math module
dir(math)
### DATA TYPES ###
# determine the type of an object
type(2) # returns 'int'
type(2.0) # returns 'float'
type('two') # returns 'str'
type(True) # returns 'bool'
type(None) # returns 'NoneType'
# check if an object is of a given type
isinstance(2.0, int) # returns False
isinstance(2.0, (int, float)) # returns True
# convert an object to a given type
float(2)
int(2.9)
str(2.9)
# zero, None, and empty containers are converted to False
bool(0)
bool(None)
bool('') # empty string
bool([]) # empty list
bool({}) # empty dictionary
# non-empty containers and non-zeros are converted to True
bool(2)
bool('two')
bool([2])
### MATH ###
# basic operations
10 + 4 # add (returns 14)
10 - 4 # subtract (returns 6)
10 * 4 # multiply (returns 40)
10 ** 4 # exponent (returns 10000)
5 % 4 # modulo (returns 1) - computes the remainder
10 / 4 # divide (returns 2 in Python 2, returns 2.5 in Python 3)
10 / float(4) # divide (returns 2.5)
# force '/' in Python 2 to perform 'true division' (unnecessary in Python 3)
from __future__ import division
10 / 4 # true division (returns 2.5)
10 // 4 # floor division (returns 2)
### COMPARISONS AND BOOLEAN OPERATIONS ###
# assignment statement
x = 5
# comparisons (these return True)
x > 3
x >= 3
x != 3
x == 5
# boolean operations (these return True)
5 > 3 and 6 > 3
5 > 3 or 5 < 3
not False
False or not False and True # evaluation order: not, and, or
### CONDITIONAL STATEMENTS ###
# if statement
if x > 0:
print('positive')
# if/else statement
if x > 0:
print('positive')
else:
print('zero or negative')
# if/elif/else statement
if x > 0:
print('positive')
elif x == 0:
print('zero')
else:
print('negative')
# single-line if statement (sometimes discouraged)
if x > 0: print('positive')
# single-line if/else statement (sometimes discouraged)
# known as a 'ternary operator'
'positive' if x > 0 else 'zero or negative'
### LISTS ###
## properties: ordered, iterable, mutable, can contain multiple data types
# create an empty list (two ways)
empty_list = []
empty_list = list()
# create a list
simpsons = ['homer', 'marge', 'bart']
# examine a list
simpsons[0] # print element 0 ('homer')
len(simpsons) # returns the length (3)
# modify a list (does not return the list)
simpsons.append('lisa') # append element to end
simpsons.extend(['itchy', 'scratchy']) # append multiple elements to end
simpsons.insert(0, 'maggie') # insert element at index 0 (shifts everything right)
simpsons.remove('bart') # search for first instance and remove it
simpsons.pop(0) # remove element 0 and return it
del simpsons[0] # remove element 0 (does not return it)
simpsons[0] = 'krusty' # replace element 0
# concatenate lists (slower than 'extend' method)
neighbors = simpsons + ['ned', 'rod', 'todd']
# find elements in a list
simpsons.count('lisa') # counts the number of instances
simpsons.index('itchy') # returns index of first instance
# list slicing [start:end:step]
weekdays = ['mon', 'tues', 'wed', 'thurs', 'fri']
weekdays[0] # element 0
weekdays[0:3] # elements 0, 1, 2
weekdays[:3] # elements 0, 1, 2
weekdays[3:] # elements 3, 4
weekdays[-1] # last element (element 4)
weekdays[::2] # every 2nd element (0, 2, 4)
weekdays[::-1] # backwards (4, 3, 2, 1, 0)
# alternative method for returning the list backwards
list(reversed(weekdays))
# sort a list in place (modifies but does not return the list)
simpsons.sort()
simpsons.sort(reverse=True) # sort in reverse
simpsons.sort(key=len) # sort by a key
# return a sorted list (does not modify the original list)
sorted(simpsons)
sorted(simpsons, reverse=True)
sorted(simpsons, key=len)
# insert into an already sorted list, and keep it sorted
num = [10, 20, 40, 50]
from bisect import insort
insort(num, 30)
# create a second reference to the same list
same_num = num
same_num[0] = 0 # modifies both 'num' and 'same_num'
# copy a list (two ways)
new_num = num[:]
new_num = list(num)
# examine objects
num is same_num # returns True (checks whether they are the same object)
num is new_num # returns False
num == same_num # returns True (checks whether they have the same contents)
num == new_num # returns True
### TUPLES ###
## properties: ordered, iterable, immutable, can contain multiple data types
## like lists, but they don't change size
# create a tuple
digits = (0, 1, 'two') # create a tuple directly
digits = tuple([0, 1, 'two']) # create a tuple from a list
zero = (0,) # trailing comma is required to indicate it's a tuple
# examine a tuple
digits[2] # returns 'two'
len(digits) # returns 3
digits.count(0) # counts the number of instances of that value (1)
digits.index(1) # returns the index of the first instance of that value (1)
# elements of a tuple cannot be modified
digits[2] = 2 # throws an error
# concatenate tuples
digits = digits + (3, 4)
# create a single tuple with elements repeated (also works with lists)
(3, 4) * 2 # returns (3, 4, 3, 4)
# sort a list of tuples
tens = [(20, 60), (10, 40), (20, 30)]
sorted(tens) # sorts by first element in tuple, then second element
# returns [(10, 40), (20, 30), (20, 60)]
# tuple unpacking
bart = ('male', 10, 'simpson') # create a tuple
(sex, age, surname) = bart # assign three values at once
### STRINGS ###
## properties: iterable, immutable
# create a string
s = str(42) # convert another data type into a string
s = 'I like you'
# examine a string
s[0] # returns 'I'
len(s) # returns 10
# string slicing is like list slicing
s[:6] # returns 'I like'
s[7:] # returns 'you'
s[-1] # returns 'u'
# basic string methods (does not modify the original string)
s.lower() # returns 'i like you'
s.upper() # returns 'I LIKE YOU'
s.startswith('I') # returns True
s.endswith('you') # returns True
s.isdigit() # returns False (returns True if every character in the string is a digit)
s.find('like') # returns index of first occurrence (2), but doesn't support regex
s.find('hate') # returns -1 since not found
s.replace('like', 'love') # replaces all instances of 'like' with 'love'
# split a string into a list of substrings separated by a delimiter
s.split(' ') # returns ['I', 'like', 'you']
s.split() # equivalent (since space is the default delimiter)
s2 = 'a, an, the'
s2.split(',') # returns ['a', ' an', ' the']
# join a list of strings into one string using a delimiter
stooges = ['larry', 'curly', 'moe']
' '.join(stooges) # returns 'larry curly moe'
# concatenate strings
s3 = 'The meaning of life is'
s4 = '42'
s3 + ' ' + s4 # returns 'The meaning of life is 42'
# remove whitespace from start and end of a string
s5 = ' ham and cheese '
s5.strip() # returns 'ham and cheese'
# string substitutions: all of these return 'raining cats and dogs'
'raining %s and %s' % ('cats', 'dogs') # old way
'raining {} and {}'.format('cats', 'dogs') # new way
'raining {arg1} and {arg2}'.format(arg1='cats', arg2='dogs') # named arguments
# string formatting
# more examples: https://mkaz.tech/python-string-format.html
'pi is {:.2f}'.format(3.14159) # returns 'pi is 3.14'
# normal strings versus raw strings
print('first line second line') # normal strings allow for escaped characters
print(r'first line first line') # raw strings treat backslashes as literal characters
### DICTIONARIES ###
## properties: unordered, iterable, mutable, can contain multiple data types
## made of key-value pairs
## keys must be unique, and can be strings, numbers, or tuples
## values can be any type
# create an empty dictionary (two ways)
empty_dict = {}
empty_dict = dict()
# create a dictionary (two ways)
family = {'dad':'homer', 'mom':'marge', 'size':6}
family = dict(dad='homer', mom='marge', size=6)
# convert a list of tuples into a dictionary
list_of_tuples = [('dad', 'homer'), ('mom', 'marge'), ('size', 6)]
family = dict(list_of_tuples)
# examine a dictionary
family['dad'] # returns 'homer'
len(family) # returns 3
'mom' in family # returns True
'marge' in family # returns False (only checks keys)
# returns a list (Python 2) or an iterable view (Python 3)
family.keys() # keys: ['dad', 'mom', 'size']
family.values() # values: ['homer', 'marge', 6]
family.items() # key-value pairs: [('dad', 'homer'), ('mom', 'marge'), ('size', 6)]
# modify a dictionary (does not return the dictionary)
family['cat'] = 'snowball' # add a new entry
family['cat'] = 'snowball ii' # edit an existing entry
del family['cat'] # delete an entry
family['kids'] = ['bart', 'lisa'] # dictionary value can be a list
family.pop('dad') # remove an entry and return the value ('homer')
family.update({'baby':'maggie', 'grandpa':'abe'}) # add multiple entries
# access values more safely with 'get'
family['mom'] # returns 'marge'
family.get('mom') # equivalent
family['grandma'] # throws an error since the key does not exist
family.get('grandma') # returns None instead
family.get('grandma', 'not found') # returns 'not found' (the default)
# access a list element within a dictionary
family['kids'][0] # returns 'bart'
family['kids'].remove('lisa') # removes 'lisa'
# string substitution using a dictionary
'youngest child is %(baby)s' % family # returns 'youngest child is maggie'
### SETS ###
## properties: unordered, iterable, mutable, can contain multiple data types
## made of unique elements (strings, numbers, or tuples)
## like dictionaries, but with keys only (no values)
# create an empty set
empty_set = set()
# create a set
languages = {'python', 'r', 'java'} # create a set directly
snakes = set(['cobra', 'viper', 'python']) # create a set from a list
# examine a set
len(languages) # returns 3
'python' in languages # returns True
# set operations
languages & snakes # returns intersection: {'python'}
languages | snakes # returns union: {'cobra', 'r', 'java', 'viper', 'python'}
languages - snakes # returns set difference: {'r', 'java'}
snakes - languages # returns set difference: {'cobra', 'viper'}
# modify a set (does not return the set)
languages.add('sql') # add a new element
languages.add('r') # try to add an existing element (ignored, no error)
languages.remove('java') # remove an element
languages.remove('c') # try to remove a non-existing element (throws an error)
languages.discard('c') # remove an element if present, but ignored otherwise
languages.pop() # remove and return an arbitrary element
languages.clear() # remove all elements
languages.update(['go', 'spark']) # add multiple elements (can also pass a set)
# get a sorted list of unique elements from a list
sorted(set([9, 0, 2, 1, 0])) # returns [0, 1, 2, 9]
### DEFINING FUNCTIONS ###
# define a function with no arguments and no return values
def print_text():
print('this is text')
# call the function
print_text()
# define a function with one argument and no return values
def print_this(x):
print(x)
# call the function
print_this(3) # prints 3
n = print_this(3) # prints 3, but doesn't assign 3 to n
# because the function has no return statement
# define a function with one argument and one return value
def square_this(x):
return x**2
# include an optional docstring to describe the effect of a function
def square_this(x):
"""Return the square of a number."""
return x**2
# call the function
square_this(3) # prints 9
var = square_this(3) # assigns 9 to var, but does not print 9
# define a function with two 'positional arguments' (no default values) and
# one 'keyword argument' (has a default value)
def calc(a, b, op='add'):
if op == 'add':
return a + b
elif op == 'sub':
return a - b
else:
print('valid operations are add and sub')
# call the function
calc(10, 4, op='add') # returns 14
calc(10, 4, 'add') # also returns 14: unnamed arguments are inferred by position
calc(10, 4) # also returns 14: default for 'op' is 'add'
calc(10, 4, 'sub') # returns 6
calc(10, 4, 'div') # prints 'valid operations are add and sub'
# use 'pass' as a placeholder if you haven't written the function body
def stub():
pass
# return two values from a single function
def min_max(nums):
return min(nums), max(nums)
# return values can be assigned to a single variable as a tuple
nums = [1, 2, 3]
min_max_num = min_max(nums) # min_max_num = (1, 3)
# return values can be assigned into multiple variables using tuple unpacking
min_num, max_num = min_max(nums) # min_num = 1, max_num = 3
### ANONYMOUS (LAMBDA) FUNCTIONS ###
## primarily used to temporarily define a function for use by another function
# define a function the "usual" way
def squared(x):
return x**2
# define an identical function using lambda
squared = lambda x: x**2
# sort a list of strings by the last letter (without using lambda)
simpsons = ['homer', 'marge', 'bart']
def last_letter(word):
return word[-1]
sorted(simpsons, key=last_letter)
# sort a list of strings by the last letter (using lambda)
sorted(simpsons, key=lambda word: word[-1])
### FOR LOOPS AND WHILE LOOPS ###
# range returns a list of integers (Python 2) or a sequence (Python 3)
range(0, 3) # returns [0, 1, 2]: includes start value but excludes stop value
range(3) # equivalent: default start value is 0
range(0, 5, 2) # returns [0, 2, 4]: third argument is the step value
# Python 2 only: use xrange to create a sequence rather than a list (saves memory)
xrange(100, 100000, 5)
# for loop (not the recommended style)
fruits = ['apple', 'banana', 'cherry']
for i in range(len(fruits)):
print(fruits[i].upper())
# for loop (recommended style)
for fruit in fruits:
print(fruit.upper())
# iterate through two things at once (using tuple unpacking)
family = {'dad':'homer', 'mom':'marge', 'size':6}
for key, value in family.items():
print(key, value)
# use enumerate if you need to access the index value within the loop
for index, fruit in enumerate(fruits):
print(index, fruit)
# for/else loop
for fruit in fruits:
if fruit == 'banana':
print('Found the banana!')
break # exit the loop and skip the 'else' block
else:
# this block executes ONLY if the for loop completes without hitting 'break'
print("Can't find the banana")
# while loop
count = 0
while count < 5:
print('This will print 5 times')
count += 1 # equivalent to 'count = count + 1'
### COMPREHENSIONS ###
# for loop to create a list of cubes
nums = [1, 2, 3, 4, 5]
cubes = []
for num in nums:
cubes.append(num**3)
# equivalent list comprehension
cubes = [num**3 for num in nums] # [1, 8, 27, 64, 125]
# for loop to create a list of cubes of even numbers
cubes_of_even = []
for num in nums:
if num % 2 == 0:
cubes_of_even.append(num**3)
# equivalent list comprehension
# syntax: [expression for variable in iterable if condition]
cubes_of_even = [num**3 for num in nums if num % 2 == 0] # [8, 64]
# for loop to cube even numbers and square odd numbers
cubes_and_squares = []
for num in nums:
if num % 2 == 0:
cubes_and_squares.append(num**3)
else:
cubes_and_squares.append(num**2)
# equivalent list comprehension (using a ternary expression)
# syntax: [true_condition if condition else false_condition for variable in iterable]
cubes_and_squares = [num**3 if num % 2 == 0 else num**2 for num in nums] # [1, 8, 9, 64, 25]
# for loop to flatten a 2d-matrix
matrix = [[1, 2], [3, 4]]
items = []
for row in matrix:
for item in row:
items.append(item)
# equivalent list comprehension
items = [item for row in matrix
for item in row] # [1, 2, 3, 4]
# set comprehension
fruits = ['apple', 'banana', 'cherry']
unique_lengths = {len(fruit) for fruit in fruits} # {5, 6}
# dictionary comprehension
fruit_lengths = {fruit:len(fruit) for fruit in fruits} # {'apple': 5, 'banana': 6, 'cherry': 6}
fruit_indices = {fruit:index for index, fruit in enumerate(fruits)} # {'apple': 0, 'banana': 1, 'cherry': 2}
### MAP AND FILTER ###
# 'map' applies a function to every element of a sequence
# ...and returns a list (Python 2) or iterator (Python 3)
simpsons = ['homer', 'marge', 'bart']
map(len, simpsons) # returns [5, 5, 4]
map(lambda word: word[-1], simpsons) # returns ['r', 'e', 't']
# equivalent list comprehensions
[len(word) for word in simpsons]
[word[-1] for word in simpsons]
# 'filter' returns a list (Python 2) or iterator (Python 3) containing
# ...the elements from a sequence for which a condition is True
nums = range(5)
filter(lambda x: x % 2 == 0, nums) # returns [0, 2, 4]
# equivalent list comprehension
[num for num in nums if num % 2 == 0]
Explanation / Answer
I have written this code in python3.6
Python code:
#!/usr/bin/python3.6
"""
Program: Lab9Start
Author: <author>
Date: <date>
Description:
Lab 9 is to read in a text file and provide a list of the unique
words in the file and the line numerbs where those words appear.
=============
ANALYSIS
=============
Input:
Output:
Calculations:
=============
DESIGN
=============
1.
2.
3.
4.
5.
6.
7.
"""
# Request the input file name
FileName = input("please enter the filename : ")
# Open the input file and initialize dictionary of unique words
d = {}
f = open(FileName, 'r')
# Add the unique words in the file to the dictionary
line_no = 0
for line in f.readlines():
words = line.split()
line_no += 1
for word in words:
if word in d.keys():
d[word] = d[word] + [line_no]
else:
d[word] = [line_no]
# Print the unique words in alphabetical order along
# with their line numbers
for key in sorted(d.keys()):
print("word '{0}' found in line number : {1}".format(key, d[key]))
# Close all files
f.close()
Sample.txt:
sdsd rohit dss
hey how are you
my name is rohit
Output shown after running this program:
-bash-4.2$ python3.6 main.py
please enter the filename : sample.txt
word 'are' found in line number : [2]
word 'dss' found in line number : [1]
word 'hey' found in line number : [2]
word 'how' found in line number : [2]
word 'is' found in line number : [3]
word 'my' found in line number : [3]
word 'name' found in line number : [3]
word 'rohit' found in line number : [1, 3]
word 'sdsd' found in line number : [1]
word 'you' found in line number : [2]