def test_get_content_lines(verbose):
"""Test a3.get_content_lines()"""
# A generic line that can be pasted into any function;
# retrieves the name of current function from its frame on the stack.
# Each item in the list returned by inspect.stack() is a call frame.
# You can print out the frame at the top of the stack by:
# print(str(inspect.stack()[0])
tester_name = inspect.stack()[0][3]
print("Running " + tester_name + "()")
test_cases = {
# Different operating systems have different ways of dealing with
# subdirectories, which is what os.path.join helps us deal with.
# See section 14.4 "Filenames and paths" of the text.
add_sources_to_fname('shortest.txt'):
["abc abcabc natural language processing\n", "3 o'clock bc!d\n"],
add_sources_to_fname('short.txt'): [
"here is a small piece of text a small piece of text a small piece of text here is a small piece of text at nine o'clock in the morning\n"
],
add_sources_to_fname('shortest_commented.txt'):
["abc abcabc natural language processing\n", "bc!d bc!d\n"],
}
for test_input in test_cases:
if verbose:
print("\tTesting " + str(test_input))
expected = test_cases[test_input]
ca.assert_equals(expected, a3.get_content_lines(test_input))
# For longer files, rough check that we get the right number of lines
test_cases = {
add_sources_to_fname('imbeciles.txt'): 33 - 6,
add_sources_to_fname('lonely_as_a_cloud.txt'): 29 - 2,
add_sources_to_fname('2013_obama.txt'): 184,
}
for test_input in test_cases:
if verbose:
print("\tTesting " + str(test_input))
expected = test_cases[test_input]
ca.assert_equals(expected, len(a3.get_content_lines(test_input)))
def test_track_topic(verbose):
""" Test a3.track_topic() """
# This code presumes that a3.get_content_lines(), a3.convert_lines_to_string(),
# and a3.convert_lines_to_paragraphs() are all implemented correctly.
tester_name = inspect.stack()[0][3]
print("Running " + tester_name + "()")
# Single-document examples from specification
test_cases = {
# Need the comma in ("abc",) to convince Python that "abc" is an item
# in a one-element tuple, not a sequence to be turned into ('a', 'b', 'c')
("abc abcabc a a", ("abc",)): round3(1/4),
("abc abcabc a a", ("ABC", "a")): round3(2/4),
("ab abab a a", ("ABC", "a", "ab", "v", "abab")): round3(4/4),
}
for test_input in test_cases:
docs_list = [test_input[0]]
vocab_list = list(test_input[1])
if verbose:
print("\tTesting " + str((docs_list, vocab_list)))
ca.assert_equals([test_cases[test_input]], a3.track_topic(docs_list, vocab_list))
# Just one document, vary the vocabulary lists
linelist = a3.get_content_lines(add_sources_to_fname("shortest.txt"))
docs_list = [a3.convert_lines_to_string(linelist)]
vocab_tuples = {
("abc",): [round3(1/8)], # Need the comma to convince Python "abc" is a tuple
# item, not a sequence to be turned into ('a', 'b', 'c')
("abcab",): [round3(0)],
("abc", "o'clock", "bipedal", "abcabc", "natural"): [round3(5/8)],
tuple(a3.convert_lines_to_string(linelist).split(),): [round3(1)] # All the words
}
for key in vocab_tuples:
vocab_list = list(key)
if verbose:
print("\tTesting " + str((docs_list, vocab_list)))
ca.assert_equals(vocab_tuples[key], a3.track_topic(docs_list, vocab_list))
# Several documents, each corresponding to a stanza (paragraph)
linelist = a3.get_content_lines(add_sources_to_fname("imbeciles.txt"))
docs_list = a3.convert_lines_to_paragraphs(linelist)
len_list = [] # Stores the lengths of each document checked for length
for doc in docs_list:
len_list.append(len(doc.split()))
vocab_tuples = {
("cheese", "continuous"): [round3(1/len_list[0]),
round3(1/len_list[1]),
0.,
0.],
# Should be case-sensitive, where these docs have been downcased
("cheese", "Continuous"): [round3(1/len_list[0]), 0., 0., 0.],
# Should not pick up commented lines
("cheese", "Harry"): [round3(1/len_list[0]), 0., 0., 0.],
("cheese", "imbeciles"): [round3(2/len_list[0]),
0.,
0.,
round3(1/len_list[3])],
("the",): [round3(3/len_list[0]),
round3(3/len_list[1]),
round3(3/len_list[2]),
round3(2/len_list[3])],
("the", "a", "an"): [round3((3 + 3 + 0)/len_list[0]),
round3((3 + 2 + 0)/len_list[1]),
round3((3 + 2 + 0)/len_list[2]),
round3((2 + 0 + 0)/len_list[3])]
}
for key in vocab_tuples:
vocab_list = list(key)
if verbose:
print("\tTesting " + str((docs_list, vocab_list)))
#TODO: NOTICE THE NESTED indices!! Ask the students to do?
# Check each float in the resulting list
result = a3.track_topic(docs_list, vocab_list)
for ind in range(len(docs_list)):
ca.assert_floats_equal(vocab_tuples[key][ind], result[ind])
def test_convert_lines_to_paragraph(verbose):
"""Test a3.convert_lines_to_paragraphs"""
tester_name = inspect.stack()[0][3]
print("Running " + tester_name + "()")
test_cases = {} # Start with empty dictionary
# test_file is the name of a file containing lines to
# extract and make into a test input (i.e., a list of lines)
# for convert_lines_to_paragraphs()
test_file = add_sources_to_fname('short_stanzas.txt')
expected = []
stanza = "1st line of 1st stanza"
expected.append(stanza)
stanza = "1st line of 2nd stanza"
expected.append(stanza)
stanza = "1st line of 3rd stanza"
stanza += " 2nd line of 3rd stanza"
stanza += " 3rd line of 3rd stanza"
expected.append(stanza)
test_cases[test_file] = expected
# We are using a list because hidden from students at submission time we
# have multiple implementations.
fns_to_test = [a3.convert_lines_to_paragraphs]
for convertfn in fns_to_test:
print("testing " + convertfn.__name__)
for test_file in test_cases:
if verbose:
print("\tTesting " + str(test_file))
expected = test_cases[test_file]
test_input = a3.get_content_lines(test_file)
ca.assert_equals(expected,
convertfn(test_input))
test_input = []
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals([], convertfn(test_input))
test_input = ["\n", "\n"] # all lines blank
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals([], convertfn(test_input))
# ends with multiple blank lines
test_input = ["\n", "\n", "just one content line", "\n"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["just one content line"],
convertfn(test_input))
# embedded newline
test_input = ["I'm\ntricky",
"and you can be too \n",
"\n",
"stay in school"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["I'm\ntricky and you can be too", "stay in school"],
convertfn(test_input))
test_file = add_sources_to_fname('lonely_as_a_cloud.txt')
if verbose:
print("\tTesting file " + str(test_file))
test_input = a3.get_content_lines(test_file)
result = convertfn(test_input)
ca.assert_equals(result[0], "i wandered lonely as a cloud that floats on high o'er vales and hills when all at once i saw a crowd a host of golden daffodils beside the lake beneath the trees fluttering and dancing in the breeze")
ca.assert_equals(result[1], 'continuous as the stars that shine and twinkle on the milky way they stretched in never ending line along the margin of a bay ten thousand saw i at a glance tossing their heads in sprightly dance')
ca.assert_equals(result[2], 'the waves beside them danced but they out did the sparkling waves in glee a poet could not but be gay in such a jocund company i gazed and gazed but little thought what wealth the show to me had brought')
ca.assert_equals(result[3], 'for oft when on my couch i lie in vacant or in pensive mood they flash upon that inward eye which is the bliss of solitude and then my heart with pleasure fills and dances with the daffodils')
def test_track_topic(verbose):
""" Test a3.track_topic() """
# This code presumes that a3.get_content_lines(), a3.convert_lines_to_string(),
# and a3.convert_lines_to_paragraphs() are all implemented correctly.
tester_name = inspect.stack()[0][3]
print("Running " + tester_name + "()")
# Single-document examples from specification
test_cases = {
# Need the comma in ("abc",) to convince Python that "abc" is an item
# in a one-element tuple, not a sequence to be turned into ('a', 'b', 'c')
("abc abcabc a a", ("abc", )):
round3(1 / 4),
("abc abcabc a a", ("ABC", "a")):
round3(2 / 4),
("ab abab a a", ("ABC", "a", "ab", "v", "abab")):
round3(4 / 4),
#STUDENT-ADDED DICTIONARY TEST CASES
#doc just one non-white space character
("a", ("abc", )):
round3(0),
#doc just multiple non white space characters
("abcc", ("abc", )):
round3(0),
#checking if code still right when outlist output is zero
("abcc abccdd sjjnff", ("abc", )):
round3(0),
#checking if code differentiates between case sensitive words
("ABC abccdd sjjnff", ("abc", "abccdd")):
round3(1 / 3),
#checking if function works if all words in docs_list in vocab_list
("abc abccdd", ("abc", "abccdd")):
round3(1),
#common case where outlist value is between 0 and 1
("abc abccdd bbb ccc", ("abc", "abccdd")):
round3(1 / 2),
#doc in doc_list has leading white spaces
(" abc abccdd bbb ccc", ("abc", "abccdd")):
round3(1 / 2),
#doc in doc_list has trailing white spaces
("abc abccdd bbb ccc ", ("abc", "abccdd")):
round3(1 / 2),
#doc in doc_list has leading and trailing white spaces
(" abc abccdd bbb ccc ", ("abc", "abccdd")):
round3(1 / 2),
#document has words with internal punctuation also ensuring that
#full words counted not just portion of words so word abc in vocablist
# should not be found in abcc'dd
("abc abcc'dd bbb ccc", ("abc", "abcc'dd", "abcc")):
round3(1 / 2),
#doc in doc_list has words containing numbers
("ab1c abcc'dd2 bb11b ccc", ("ab1c", "abcc'dd2", "abcc")):
round3(1 / 2),
#vocablist just one item list
("hey abccdd hi", ("hey", )):
round3(1 / 3),
#words in doc in doclist repeated
("hey hey abccdd hi", ("hey", )):
round3(2 / 4),
#words in vocablist repeated
("hey hey abccdd hi", ("hey", "hey")):
round3(2 / 4),
#doc in doclist one very long word with no spaces
("heyheyabccddhi", ("hey", "abcc")):
round3(0),
#vocablist containg string which is just space
("hey abccdd hi", ("hey", " ")):
round3(1 / 3),
#doc in doclist contains multiple spaces of varying lengths between words
("hey ab cc d d hi", ("hey", " ")):
round3(1 / 6),
#target word in vocab_list contains spaces in between string
("hey baby abccdd hi", ("hey ", "baby", "hey baby")):
round3(1 / 4),
#internal punctuation in vocablist and checking odd vocablist
("abc abcbbc'dd bbb ccc", ("abc", "abcbbc'dd", "abcc")):
round3(1 / 2),
#vocablist containing words with numbers and checking even vocablist
("hey1 hey2 abccdd hi", ("hey2", "hey")):
round3(1 / 4),
#target word in vocab_list contains spaces before string
("hey baby abccdd hi", (" hey", "baby", "heybaby")):
round3(1 / 4),
#checking Function case sensitive
("Hey Baby abccdd hi", ("Hey", "baby", "heybaby")):
round3(1 / 4),
#target word in vocab_list contains spaces after string
("hey baby abccdd hi", ("hey", "baby ", "heybaby")):
round3(1 / 4),
#target word in doc contains tabs right infront of it which are
#treated as spaces here spaces here
("hey baby\t abccdd hi", ("hey", "baby", "heybaby")):
round3(2 / 4),
}
for test_input in test_cases:
docs_list = [test_input[0]]
vocab_list = list(test_input[1])
if verbose:
print("\tTesting " + str((docs_list, vocab_list)))
ca.assert_equals([test_cases[test_input]],
a3.track_topic(docs_list, vocab_list))
# Just one document, vary the vocabulary lists
linelist = a3.get_content_lines(add_sources_to_fname("shortest.txt"))
docs_list = [a3.convert_lines_to_string(linelist)]
vocab_tuples = {
("abc", ):
[round3(1 / 8)], # Need the comma to convince Python "abc" is a tuple
# item, not a sequence to be turned into ('a', 'b', 'c')
(
"abcab", ): [round3(0)],
("abc", "o'clock", "bipedal", "abcabc", "natural"):
[round3(4 / 8)], # ... STUDENT-FIXED ERROR ...
tuple(a3.convert_lines_to_string(linelist).split(), ):
[round3(1)] # All the words
}
for key in vocab_tuples:
vocab_list = list(key)
if verbose:
print("\tTesting " + str((docs_list, vocab_list)))
ca.assert_equals(vocab_tuples[key],
a3.track_topic(docs_list, vocab_list))
# Several documents, each corresponding to a stanza (paragraph)
linelist = a3.get_content_lines(add_sources_to_fname("imbeciles.txt"))
docs_list = a3.convert_lines_to_paragraphs(linelist)
len_list = [] # Stores the lengths of each document checked for length
for doc in docs_list:
len_list.append(len(doc.split()))
vocab_tuples = {
("cheese", "continuous"):
[round3(1 / len_list[0]),
round3(1 / len_list[1]), 0., 0.],
# Should be case-sensitive, where these docs have been downcased
("cheese", "Continuous"): [round3(1 / len_list[0]), 0., 0., 0.],
# Should not pick up commented lines
("cheese", "Harry"): [round3(1 / len_list[0]), 0., 0., 0.],
("cheese", "imbeciles"):
[round3(2 / len_list[0]), 0., 0.,
round3(1 / len_list[3])],
("the", ): [
round3(3 / len_list[0]),
round3(3 / len_list[1]),
round3(3 / len_list[2]),
round3(2 / len_list[3])
],
("the", "a", "an"): [
round3((3 + 3 + 0) / len_list[0]),
round3((3 + 2 + 0) / len_list[1]),
round3((3 + 2 + 0) / len_list[2]),
round3((2 + 0 + 0) / len_list[3])
]
}
for key in vocab_tuples:
vocab_list = list(key)
if verbose:
print("\tTesting " + str((docs_list, vocab_list)))
#TODO: NOTICE THE NESTED indices!! Ask the students to do?
# Check each float in the resulting list
result = a3.track_topic(docs_list, vocab_list)
for ind in range(len(docs_list)):
ca.assert_floats_equal(vocab_tuples[key][ind], result[ind])
# Leave the following comment line in your submitted code so that the
# graders can easily locate it and thus your additions.
# ..... STUDENT-ADDED NON-DICTIONARY TEST CASES BELOW THIS LINE ....
#STUDENT-ADDED NON-DICTIONARY TEST CASES BELOW
#Empty docs_list
docs_list = []
vocab_tuples = {
#empty docs_list with one item vocab_list
(
"abc", ): [],
#empty docs_list with only spaces in vocab_list
(
" ", ): [],
#empty docs_list with multiple item vocab_list
("abc", "o'clock", "bipedal", "abcabc", "natural"): [],
}
for key in vocab_tuples:
vocab_list = list(key)
if verbose:
print("\tTesting " + str((docs_list, vocab_list)))
ca.assert_equals(vocab_tuples[key],
a3.track_topic(docs_list, vocab_list))
#Docs_list just one item so outlist also one item
docs_list = ["abc hhhh nnnbhb"]
vocab_tuples = {
# docs_list with one item vocab_list
(
"abc", ): [round3(1 / 3)],
#one item docs_list with multiple item vocab_list
("abc", "o'clock", "bipedal", "abcabc", "natural"): [round3(1 / 3)],
}
for key in vocab_tuples:
vocab_list = list(key)
if verbose:
print("\tTesting " + str((docs_list, vocab_list)))
ca.assert_equals(vocab_tuples[key],
a3.track_topic(docs_list, vocab_list))
#Odd- lengthed doclist
docs_list = ["abc hhhh nnnbhb", "bye bye11 bye22", "car is better"]
vocab_tuples = {
#docs_list with one item vocab_list
(
"abc", ): [round3(1 / 3), round3(0),
round3(0)],
#docs_list with multiple item vocab_list
("abc", "o'clock", "bipedal", "bye11", "natural"):
[round3(1 / 3), round3(1 / 3), round3(0)],
}
for key in vocab_tuples:
vocab_list = list(key)
if verbose:
print("\tTesting " + str((docs_list, vocab_list)))
ca.assert_equals(vocab_tuples[key],
a3.track_topic(docs_list, vocab_list))
#Even-lengthed doclist
docs_list = ["abc hhhh nnnbhb", "bye bye11 bye22"]
vocab_tuples = {
#one item vocab_list
(
"abc", ): [round3(1 / 3), round3(0)],
# multiple item vocab_list
("abc", "o'clock", "bipedal", "bye11", "natural"):
[round3(1 / 3), round3(1 / 3)],
}
for key in vocab_tuples:
vocab_list = list(key)
if verbose:
print("\tTesting " + str((docs_list, vocab_list)))
ca.assert_equals(vocab_tuples[key],
a3.track_topic(docs_list, vocab_list))
def test_convert_lines_to_paragraph(verbose):
"""Test a3.convert_lines_to_paragraphs"""
tester_name = inspect.stack()[0][3]
print("Running " + tester_name + "()")
test_cases = {} # Start with empty dictionary
# test_file is the name of a file containing lines to
# extract and make into a test input (i.e., a list of lines)
# for convert_lines_to_paragraphs()
test_file = add_sources_to_fname('short_stanzas.txt')
expected = []
stanza = "1st line of 1st stanza"
stanza += " 2nd line of 1st stanza" # ... STUDENT-FIXED ERROR ...
expected.append(stanza)
stanza = "1st line of 2nd stanza"
expected.append(stanza)
stanza = "1st line of 3rd stanza"
stanza += " 2nd line of 3rd stanza"
stanza += " 3rd line of 3rd stanza"
expected.append(stanza)
print(stanza)
test_cases[test_file] = expected
# We are using a list because hidden from students at submission time we
# have multiple implementations.
fns_to_test = [a3.convert_lines_to_paragraphs]
for convertfn in fns_to_test:
print("testing " + convertfn.__name__)
for test_file in test_cases:
if verbose:
print("\tTesting " + str(test_file))
expected = test_cases[test_file]
test_input = a3.get_content_lines(test_file)
ca.assert_equals(expected, convertfn(test_input))
test_input = []
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals([], convertfn(test_input))
test_input = ["\n", "\n"] # all lines blank
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals([], convertfn(test_input))
# ends with multiple blank lines
test_input = ["\n", "\n", "just one content line", "\n"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["just one content line"], convertfn(test_input))
# embedded newline
test_input = [
"I'm\ntricky", "and you can be too \n", "\n", "stay in school"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["I'm\ntricky and you can be too", "stay in school"],
convertfn(test_input))
test_file = add_sources_to_fname('lonely_as_a_cloud.txt')
if verbose:
print("\tTesting file " + str(test_file))
test_input = a3.get_content_lines(test_file)
result = convertfn(test_input)
ca.assert_equals(
result[0],
"i wandered lonely as a cloud that floats on high o'er vales and hills when all at once i saw a crowd a host of golden daffodils beside the lake beneath the trees fluttering and dancing in the breeze"
)
ca.assert_equals(
result[1],
'continuous as the stars that shine and twinkle on the milky way they stretched in never ending line along the margin of a bay ten thousand saw i at a glance tossing their heads in sprightly dance'
)
ca.assert_equals(
result[2],
'the waves beside them danced but they out did the sparkling waves in glee a poet could not but be gay in such a jocund company i gazed and gazed but little thought what wealth the show to me had brought'
)
ca.assert_equals(
result[3],
'for oft when on my couch i lie in vacant or in pensive mood they flash upon that inward eye which is the bliss of solitude and then my heart with pleasure fills and dances with the daffodils'
)
# ... STUDENT-ADDED NON-DICT. CONVERT...PARA TEST CASES BELOW THIS LINE ....
#STUDENT-ADDED NON-DICT
#empty linelist
test_input = []
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals([], convertfn(test_input))
#non-empty linelist with only empty strings
test_input = ["", "", "", ""] # all lines blank
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals([], convertfn(test_input))
#begins with blank line
test_input = ["\n", "just one content line", "how are you"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["just one content line how are you"],
convertfn(test_input))
#ends with blank line
test_input = ["hello my boy", "just one content line", "\n"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hello my boy just one content line"],
convertfn(test_input))
#blank line in middle
test_input = [
"hello my boy", "hi", "\n", "just one content line", "blue"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hello my boy hi", "just one content line blue"],
convertfn(test_input))
#begins with multiple blank lines
test_input = ["\n", "\n", "\n", "just one content line", "how are you"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["just one content line how are you"],
convertfn(test_input))
#ends with multiple blank lines
test_input = [
"hello my boy", "just one content line", "\n", "\n", "\n"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hello my boy just one content line"],
convertfn(test_input))
#multiple blank lines in middle
test_input = [
"hello my boy", "hi", "\n", "\n", "\n", "just one content line",
"blue"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hello my boy hi", "just one content line blue"],
convertfn(test_input))
#one word paragraphs
test_input = ["hi", "\n", "blue"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hi", "blue"], convertfn(test_input))
#ensures code treats capital letters the same as lowercase letters
test_input = ["Hi", "\n", "Blue"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["Hi", "Blue"], convertfn(test_input))
#one item linelist
test_input = ["hi"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hi"], convertfn(test_input))
#paragraph begins with embedded blank line
test_input = ["\njust one", "just one content line", "how are you"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["just one just one content line how are you"],
convertfn(test_input))
#paragraph ends with emdedded blank line
test_input = ["hello my boy\n", "just one content line\n"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hello my boy just one content line"],
convertfn(test_input))
#emdedded blank line in middle of paragraph
test_input = [
"hello \n my boy", "hi", "\n", "just one content\n line", "blue"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(
["hello \n my boy hi", "just one content\n line blue"],
convertfn(test_input))
#paragraph which is just white space this should become two spaces between lines as shown in convert_lines_to_string
test_input = ["just one", " ", "how are you"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["just one how are you"], convertfn(test_input))
#multiple paragraphs which are just white spaces
test_input = ["just one", " ", " ", "how are you"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["just one how are you"], convertfn(test_input))
#paragraph which is just white at beginning
test_input = [" ", "hello", "hi", "how are you"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals([" hello hi how are you"], convertfn(test_input))
#paragraph which is just white at end
test_input = ["hello", "hi", " "]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hello hi "], convertfn(test_input))
#paragraph begins with trailling white spaces
test_input = [" just one", " just one content line", "how are you"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["just one just one content line how are you"],
convertfn(test_input))
#paragraph ends with trailling white spaces
test_input = ["hello my boy ", "just one content line "]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hello my boy just one content line"],
convertfn(test_input))
#trailling white spaces in middle of paragraph
test_input = [
"hello my boy", "hi", "\n", "just one content line", "blue"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(
["hello my boy hi", "just one content line blue"],
convertfn(test_input))
#white spaces and new lines in middle of lines
test_input = [
"hello \n\n \n my boy", "hi", "\n",
"just one content \n line", "blue"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(
["hello \n\n \n my boy hi", "just one content \n line blue"],
convertfn(test_input))
# white spaces and new lines at beginning of lines
test_input = [
"\n just one\n ", " \n just one content line ",
"\n how are you"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["just one just one content line how are you"],
convertfn(test_input))
#line in paragraph which is not exactly "\n" (example has white spaces " \n ")
test_input = [
"hello my boy", "hi", " \n ", "just one content line", "blue"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hello my boy hi just one content line blue"],
convertfn(test_input))
#multiple paragraphs in list
test_input = [
"hello my", "hi", "\n", "just lie", "blue", "\n", "may act", "red",
"\n", "may thee", "purp"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(
["hello my hi", "just lie blue", "may act red", "may thee purp"],
convertfn(test_input))
#one line paragraph in beginning and even number of paragraphs
test_input = ["hello my boy", "\n", "just one content line", "blue"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hello my boy", "just one content line blue"],
convertfn(test_input))
#one line paragraph at end and even number of lines
test_input = ["hello my boy", "just one content line", "\n", "blue"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hello my boy just one content line", "blue"],
convertfn(test_input))
#one line paragraph in middle and odd number of paragraphs
test_input = [
"hello my boy", "hi", "\n", "just one content line", "\n", "blue",
"hi"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(
["hello my boy hi", "just one content line", "blue hi"],
convertfn(test_input))
#one large paragrpah from multiple lines and odd number of lines
test_input = [
"hello my boy", "hi", "just one content line", "blue", "hi"
]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hello my boy hi just one content line blue hi"],
convertfn(test_input))
#linelist with only blank lines
test_input = ["\n", "\n", "\n", "\n"] # all lines blank
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals([], convertfn(test_input))
#multiple new blank lines in one line(behaves like a paragraph of white spaces)
test_input = ["hi", "\n\n\n", "blue"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hi blue"], convertfn(test_input))
#miswritten blank line that is blank line with slash turned-> /n
test_input = ["hi", "/n", "blue"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hi /n blue"], convertfn(test_input))
#ensuring code is case sensitive for blank lines
test_input = ["hi", "\\N", "blue"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["hi \\N blue"], convertfn(test_input))
#ensuring code doesnt strip away ending punctuation
test_input = ["Hi", "Blue!\n"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["Hi Blue!"], convertfn(test_input))
#ensuring code doesnt strip away ending backslashes
test_input = ["Hi", "Blue\\\n"]
if verbose:
print("\tTesting " + str(test_input))
ca.assert_equals(["Hi Blue\\"], convertfn(test_input))