Lesson 7 · Python standard library deep dive

Python re Explained: Regular Expressions Made Simple | Standard Library #7

Video seven of the twenty-five-part series: re, Python's pattern-matching engine for text. Matching, searching, groups, substitution, compiling, and flags.…

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CoursePython standard library deep dive
Lesson7 of 24
Video18 min
FormatJupyter notebook · 15 code cells

regex (re)

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Python Standard Library Deep-Dive, Video 7: re (Regular Expressions)#

Video seven of the twenty-five-part series: re, Python's pattern-matching engine for text.
Matching, searching, groups, substitution, compiling, and flags.
Let's get into it.

Part 1: What re Offers#

import re
text = 'The year 2026 was eventful'
match = re.search(r'\d+', text)
print(match)
print(match.group())

<re.Match object; span=(9, 13), match='2026'>
2026

Part 2: match(), search(), fullmatch()#

text = 'hello world'
print(re.match(r'hello', text))
print(re.match(r'world', text))
print(re.search(r'world', text))
print(re.fullmatch(r'hello world', text))
print(re.fullmatch(r'hello', text))

<re.Match object; span=(0, 5), match='hello'>
None
<re.Match object; span=(6, 11), match='world'>
<re.Match object; span=(0, 11), match='hello world'>
None

Part 3: findall() and finditer()#

text = 'Order 12 has 5 items, order 45 has 2 items'
numbers = re.findall(r'\d+', text)
print(numbers)
for m in re.finditer(r'\d+', text):
    print(m.group(), m.start(), m.end())

['12', '5', '45', '2']
12 6 8
5 13 14
45 28 30
2 35 36

Part 4: Character Classes and Quantifiers#

text = 'Call 555-1234 or email me@test.com, id_007 works too'
print(re.findall(r'\d+', text))
print(re.findall(r'\w+', text))
print(re.findall(r'\s+', text))
print(re.findall(r'[aeiou]', 'hello world'))
print(re.findall(r'[^aeiou\s]', 'hello world'))

['555', '1234', '007']
['Call', '555', '1234', 'or', 'email', 'me', 'test', 'com', 'id_007', 'works', 'too']
[' ', ' ', ' ', ' ', ' ', ' ', ' ']
['e', 'o', 'o']
['h', 'l', 'l', 'w', 'r', 'l', 'd']

print(re.findall(r'ab?c', 'ac abc abbc'))
print(re.findall(r'ab*c', 'ac abc abbbc'))
print(re.findall(r'ab+c', 'ac abc abbbc'))
print(re.findall(r'\d{3}', '12 123 1234 12345'))
print(re.findall(r'\d{2,4}', '12 123 1234 12345'))

['ac', 'abc']
['ac', 'abc', 'abbbc']
['abc', 'abbbc']
['123', '123', '123']
['12', '123', '1234', '1234']

Part 5: Anchors and Boundaries#

print(re.findall(r'^\d+', '123 abc 456'))
print(re.findall(r'\d+$', '123 abc 456'))
print(re.findall(r'\bcat\b', 'cat category cats cat'))
print(re.findall(r'cat', 'cat category cats cat'))

['123']
['456']
['cat', 'cat']
['cat', 'cat', 'cat', 'cat']

Part 6: Groups and Capturing#

text = 'Date: 2026-03-15'
match = re.search(r'(\d{4})-(\d{2})-(\d{2})', text)
print(match.group())
print(match.group(0))
print(match.group(1))
print(match.groups())

2026-03-15
2026-03-15
2026
('2026', '03', '15')

match = re.search(r'(?P<year>\d{4})-(?P<month>\d{2})-(?P<day>\d{2})', text)
print(match.group('year'))
print(match.group('month'))
print(match.groupdict())

2026
03
{'year': '2026', 'month': '03', 'day': '15'}

Part 7: sub() and subn()#

text = 'Contact: 555-1234 or 555-5678'
redacted = re.sub(r'\d{3}-\d{4}', 'XXX-XXXX', text)
print(redacted)
result, count = re.subn(r'\d{3}-\d{4}', 'XXX-XXXX', text)
print(result, count)

Contact: XXX-XXXX or XXX-XXXX
Contact: XXX-XXXX or XXX-XXXX 2

text = 'John Smith, Jane Doe'
swapped = re.sub(r'(\w+) (\w+)', r'\2 \1', text)
print(swapped)
def uppercase_match(m):
    return m.group().upper()
shouted = re.sub(r'\w+', uppercase_match, text)
print(shouted)

Smith John, Doe Jane
JOHN SMITH, JANE DOE

Part 8: split() with Regex#

text = 'apple, banana;  cherry,date'
print(re.split(r'[,;]\s*', text))
print(text.split(','))
text2 = 'one1two22three333four'
print(re.split(r'\d+', text2))

['apple', 'banana', 'cherry', 'date']
['apple', ' banana;  cherry', 'date']
['one', 'two', 'three', 'four']

Part 9: Compiling Patterns for Reuse#

phone_pattern = re.compile(r'\d{3}-\d{3}-\d{4}')
text1 = 'Call 555-123-4567'
text2 = 'Or reach 555-987-6543 instead'
print(phone_pattern.search(text1).group())
print(phone_pattern.search(text2).group())
print(phone_pattern.findall('555-111-2222 and 555-333-4444'))

555-123-4567
555-987-6543
['555-111-2222', '555-333-4444']

Part 10: Flags: IGNORECASE, MULTILINE, DOTALL#

print(re.findall(r'python', 'Python PYTHON python', re.IGNORECASE))
text = 'line one\nline two\nline three'
print(re.findall(r'^line', text))
print(re.findall(r'^line', text, re.MULTILINE))
print(re.findall(r'one.two', 'one\ntwo'))
print(re.findall(r'one.two', 'one\ntwo', re.DOTALL))

['Python', 'PYTHON', 'python']
['line']
['line', 'line', 'line']
[]
['one\ntwo']

Part 11: Common Patterns#

email_pattern = re.compile(r'^[\w.+-]+@[\w-]+(?:\.[\w-]+)+$')
candidates = ['user@example.com', 'not-an-email', 'a.b+c@sub.domain.co']
for candidate in candidates:
    is_valid = bool(email_pattern.match(candidate))
    print(candidate, is_valid)

user@example.com True
not-an-email False
a.b+c@sub.domain.co True

report = 'Revenue: $45,231.50 up from $38,900.00 last quarter, a 16.28% increase'
numbers = re.findall(r'\d[\d,]*\.?\d*', report)
print(numbers)
cleaned = [float(n.replace(',', '')) for n in numbers]
print(cleaned)

['45,231.50', '38,900.00', '16.28']
[45231.5, 38900.0, 16.28]

Wrap-Up: What You Learned#

match, search, and fullmatch, each anchoring differently.
findall for a plain list of matches, finditer for match objects with position data.
Character classes, quantifiers, anchors, and word boundaries.
Capturing groups, both positional and named, and how to pull them apart.
sub and subn for substitution, including function-based and backreference replacements.
re.split for pattern-based splitting, and re.compile for reusable, faster patterns.
Flags: IGNORECASE, MULTILINE, DOTALL.
Two real patterns: email validation and extracting numbers from mixed text.
That wraps up re. Next up: json and csv, for structured data serialization.

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