Skip to content
Laviyx Learn

Try

Python course menu

Python Regular Expressions (re): Search, Match, Extract and Replace Text

Learn Python regular expressions with the re module: pattern syntax, findall, search, match, groups and named groups, sub and split, flags, validating emails and phone numbers, and greedy vs lazy matching.

Intermediate6 min readUpdated
On this page

A regular expression (regex) is a pattern that describes text: "five digits, a dash, five more digits", or "something that looks like an email address". Python's re module uses these patterns to find, check, extract and replace text, tasks that would take many lines with ordinary string methods.

A first example#

Find all phone numbers in a sentence:

Python
import re

text = "Call 98450-12345 or 99001-67890 today"
print(re.findall(r"\d{5}-\d{5}", text))
Output
['98450-12345', '99001-67890']

\d means "a digit" and {5} means "exactly five times". Patterns are written as raw strings (r"...") so backslashes reach the regex engine unchanged.

Pattern building blocks#

PatternMatches
abcthe exact text "abc"
.any character except a newline
\d / \Da digit / a non-digit
\w / \Wa word character (letter, digit, _) / anything else
\s / \Swhitespace / non-whitespace
[aeiou]any one of these characters
[a-z], [0-9]a character in a range
[^0-9]any character not in the set
^ / $start / end of the string
a|ba or b

Quantifiers say how many times the previous item repeats:

QuantifierMeaning
*0 or more
+1 or more
?0 or 1 (optional)
{n}exactly n
{n,m}between n and m

The main functions#

FunctionReturns
re.findall(p, s)a list of all matches
re.search(p, s)the first match anywhere, or None
re.match(p, s)a match only at the start of the string, or None
re.fullmatch(p, s)a match only if the whole string matches
re.sub(p, repl, s)a new string with matches replaced
re.split(p, s)a list split at every match

search and match objects#

Python
print(bool(re.search(r"python", "I love Python")),
      bool(re.search(r"python", "I love Python", re.IGNORECASE)))

m = re.search(r"(\d+) items", "Order of 12 items placed")
print(m.group(0), m.group(1), m.start())
Output
False True
12 items 12 9
  • Matching is case-sensitive unless you pass re.IGNORECASE.
  • search returns a match object (or None, so always check before using it).
  • group(0) is the whole match; group(1) is the part inside the first ( ).

Groups: extracting parts#

Parentheses capture parts of a match. With findall, each match becomes a tuple of groups:

Python
log = "2026-10-23 ERROR db timeout; 2026-10-24 WARN slow query"
for date_, level in re.findall(r"(\d{4}-\d{2}-\d{2}) (ERROR|WARN)", log):
    print(date_, level)
Output
2026-10-23 ERROR
2026-10-24 WARN

Named groups make patterns self-documenting:

Python
m = re.search(r"(?P<year>\d{4})-(?P<month>\d{2})", "Released 2026-10")
print(m.group("year"), m.group("month"), m.groupdict())
Output
2026 10 {'year': '2026', 'month': '10'}

Validating input#

Anchor the pattern with ^ and $ so the whole string must match:

Python
pattern = r"^[\w.+-]+@[\w-]+\.[\w.]+$"
for email in ["asha@company.com", "ravi.k+test@mail.co.in", "bad-email", "x@y"]:
    print(email, bool(re.match(pattern, email)))
Output
asha@company.com True
ravi.k+test@mail.co.in True
bad-email False
x@y False

Replacing and splitting#

Python
print(re.sub(r"\s+", " ", "too    many   spaces  here"))
print(re.sub(r"\d", "#", "PIN 560001"))
print(re.split(r"[,;]\s*", "a, b;c ,d"))
Output
too many spaces here
PIN ######
['a', 'b', 'c ', 'd']

Compiling patterns#

If you use a pattern many times, compile it once:

Python
phone = re.compile(r"\+91[- ]?\d{10}")
print(phone.findall("Reach +91 9845012345 or +91-9900167890"))
Output
['+91 9845012345', '+91-9900167890']

[- ]? allows an optional dash or space. \+ matches a literal plus sign, because + on its own means "one or more".

Greedy vs lazy#

Quantifiers are greedy: they match as much as possible. Add ? to make them lazy:

Python
print(re.findall(r"<.+>", "<b>bold</b>"), re.findall(r"<.+?>", "<b>bold</b>"))
Output
['<b>bold</b>'] ['<b>', '</b>']

Common mistakes#

Practice#

Practice exercise

Extract every rupee amount from this text as integers, then print the list and the sum of all amounts except the final "Total":

Python
text = "Prices: ₹250, ₹1,200 and ₹75. Total ₹1,525."
Show hint

Use a group after the ₹ sign: r"₹([\d,]+)". Remove commas before converting with int().

Show solution
Python
import re

text = "Prices: ₹250, ₹1,200 and ₹75. Total ₹1,525."
amounts = [int(a.replace(",", "")) for a in re.findall(r"₹([\d,]+)", text)]
print(amounts, sum(amounts[:-1]))
Output
[250, 1200, 75, 1525] 1525

The three prices add up to the stated total, so the data checks out.

Key takeaway#

Finished this lesson?

Related lessons

PythonPython Strings: Indexing, Slicing, Methods and f-stringsA complete beginner guide to Python strings: creating strings, indexing and slicing, immutability, essential string methods (strip, split, join, replace, find), f-string formatting, and checking content.Beginner8 min readPythonPython File Handling: Read, Write and Append Files (with open and pathlib)Learn file handling in Python: open files with the with statement, read whole files or line by line, write and append, file modes, encodings, pathlib paths and folders, CSV files, and handling missing files.Intermediate7 min readPythonPython Web Scraping With requests and BeautifulSoup (Beginner Guide)Learn web scraping in Python: download pages with requests, parse HTML with BeautifulSoup, find elements with find and CSS selectors, extract text and attributes, follow pagination, and scrape responsibly with robots.txt.Intermediate8 min readPythonAutomate Boring Tasks With Python: Files, Folders, CSV Reports and BackupsPractical Python automation for beginners: organise a messy downloads folder by file type, batch rename files, turn CSV data into a summary report, zip backups, scan log files, and schedule scripts to run automatically.Intermediate8 min read