import re

fh = open("sample_phone_book.txt")

for line in fh:
    if re.search(r"J.*Neu",line):
        print(line.rstrip())

    if re.search(r"a*Neu",line):
        print(line.rstrip())
fh.close()

Allison Neu 555-8396 …

import re

names = ['A2B8']

for name in names:
    m = re.match("^[A-Z]\d[A-Z]\d", name)

    if(m):
        print(m.groups())
        print('matched : ', name)

()
matched :  A2B8

content = '15. TFRecord in Tensorflow'

content

'15. TFRecord in Tensorflow'

import re

result = re.sub(r'\d+\.', '', content)

result.strip()

'TFRecord in Tensorflow'

content2 = """1. Cross Entropy Loss Derivation

2. How to split a tensorflow model …

content = "This device is costing only 12.89$. This is fantastic!"

content

'This device is costing only 12.89$. This is fantastic!'

import re

re.sub(r'[^\w]', ' ', content)

'This device is costing only 12 89 …

import re

data = [
    "name['toronto'] = 'One'",
    "state['ontario'] = 'Two'",
    "country['canada']['ca'] = 'Three'",
    "extra['maple'] = 'Four'"
]

REGEX = re.compile(r"\['(?P<word>.*?)'\]")

for line in data:
    found = REGEX.search(line)
    if found:
        print(found.group('word'))

toronto …

import re

content = "Eminem means positive"

a = re.search('^Em.*ve$', content)

if(a):
    print('matched')
else:
    print('not matched')

matched

import re

pattern = 'awesome'

content = 'Duckduck go is awesome and it is getting better everyday'

match = re.search(pattern, content)

#print(match)

start = match.start()
end = match.end()

#print(match.string)

print(start, end)

15 22 …

import re

fn = "DC_QnA_bo_v.15.12.3_DE_duplicates.xlsx"
rgx = re.compile('\b_[A-Z]{2}\b')
print(re.findall(rgx, fn))

[]

rgx = re.compile('(?<=_)[A-Z]+(?=_)')
print …