Python me Regular Expressions (RegEx) kya hai?

Regular Expression (RegEx) ek pattern hai jo strings me specific text dhundhne, check karne ya replace karne ke kaam aata hai. Jaise email validate karna, phone number check karna — yeh sab RegEx se bahut aasaan ho jaata hai. Python me re module use hota hai.

Is page me yeh sab sikhenge :-

1. re module aur basic functions
2. Meta characters
3. re.search() aur re.match()
4. re.findall()
5. re.sub()
6. re.split()
7. Groups aur Practical Examples

1. re Module aur Basic Functions

Function	Kaam
re.match(pat, str)	String ke shuru me pattern dhundho
re.search(pat, str)	String ke kahi bhi pattern dhundho
re.findall(pat, str)	Saare matches ki list do
re.sub(pat, repl, str)	Pattern ko replace karo
re.split(pat, str)	Pattern pe split karo
re.compile(pat)	Pattern ko compile karo

Example 1: re.search() — basic pattern dhundhna

Python

In [1]:

import re

text = "Mujhe Python bahut pasand hai. Python ek great language hai."

result = re.search("Python", text)

if result:
    print("Pattern mila!")
    print("Match      :", result.group())
    print("Start index:", result.start())
    print("End index  :", result.end())
else:
    print("Pattern nahi mila.")

Output

2. Meta Characters — Special Symbols

Symbol	Matlab	Example
.	Koi bhi ek character	a.c → abc, aXc
^	String ka shuru	^Hello
$	String ka ant	world$
*	0 ya zyada baar	ab*
+	1 ya zyada baar	ab+
?	Optional (0 ya 1 baar)	colou?r
{n,m}	n se m baar	\d{2,4}
\d	Digit (0-9)	\d+
\w	Word character	\w+
\s	Whitespace	\s+
[]	Character class	[aeiou]
()	Group	(\d{2})

Example 1: \d, \w, \s meta characters

Python

In [1]:

import re

text = "Rahul ke 3 subjects me 95, 88, aur 76 marks hain."

# \d+ — saare numbers
numbers = re.findall(r"\d+", text)
print("Numbers:", numbers)

# \w+ — saare words
words = re.findall(r"\w+", text)
print("Word count:", len(words))
print("First 5 words:", words[:5])

Output

3. re.search() vs re.match()

re.match() sirf string ke bilkul shuru me dhundhta hai. re.search() string me kahin bhi dhundhta hai.

Example 1: match vs search — fark samjho

Python

In [1]:

import re

text = "Hello, Python world!"

m1 = re.match(r"Hello", text)
m2 = re.match(r"Python", text)   # Python shuru me nahi

print("match('Hello') :", m1.group() if m1 else "Not found")
print("match('Python'):", m2.group() if m2 else "Not found")

s1 = re.search(r"Hello", text)
s2 = re.search(r"Python", text)

print("search('Hello') :", s1.group() if s1 else "Not found")
print("search('Python'):", s2.group() if s2 else "Not found")

Output

4. re.findall() — Saare Matches Nikalna

Example 1: Emails aur phone numbers nikalna

Python

In [1]:

import re

data = "Contact: support@codepth.com or admin@python.org. Call: 9876543210 or 8765432109"

emails = re.findall(r"[\w.]+@[\w.]+\.\w+", data)
print("Emails:", emails)

phones = re.findall(r"\d{10}", data)
print("Phones:", phones)

Output

Example 2: Dates aur hashtags dhundhna

Python

In [1]:

import re

post = "Aaj 15-03-2024 ko #Python aur #Coding class thi. Bahut #Maza aaya!"

dates    = re.findall(r"\d{2}-\d{2}-\d{4}", post)
hashtags = re.findall(r"#\w+", post)
caps     = re.findall(r"[A-Z][a-z]+", post)

print("Dates    :", dates)
print("Hashtags :", hashtags)
print("Cap words:", caps)

Output

5. re.sub() — Replace Karna

Example 1: Text clean karna

Python

In [1]:

import re

text = "Mera   phone   number   hai   9876543210."

# Multiple spaces → ek space
cleaned = re.sub(r"\s+", " ", text)
print("Cleaned:", cleaned)

# Phone number chhupao
masked = re.sub(r"\d{10}", "XXXXXXXXXX", text)
print("Masked :", masked)

# Sab digits hatao
no_nums = re.sub(r"\d+", "", "Price: 599 aur discount: 100 rupees")
print("No nums:", no_nums)

Output

6. re.split() — Pattern Pe Split Karna

Example 1: Multiple separators pe split

Python

In [1]:

import re

text = "Apple,Mango;Banana|Grapes,Kiwi"
fruits = re.split(r"[,;|]", text)
print("Fruits:", fruits)

sentence = "Python3is4awesome5really"
words = re.split(r"\d", sentence)
print("Words:", words)

data = "Rahul   Priya\tArjun\nNeha"
names = re.split(r"\s+", data)
print("Names:", names)

Output

7. Groups aur Practical Examples

Example 1: Groups — date ke parts alag nikalna

Python

In [1]:

import re

date_text = "Aaj ki date hai 15-08-2024"

pattern = r"(\d{2})-(\d{2})-(\d{4})"
match = re.search(pattern, date_text)

if match:
    print("Full match:", match.group(0))
    print("Day       :", match.group(1))
    print("Month     :", match.group(2))
    print("Year      :", match.group(3))

Output

Example 2: Email validation

Python

In [1]:

import re

def validate_email(email):
    pattern = r"^[\w.-]+@[\w-]+\.[a-zA-Z]{2,}$"
    if re.match(pattern, email):
        return f"Valid   : {email}"
    else:
        return f"Invalid : {email}"

emails = ["rahul@gmail.com", "priya@yahoo.co.in", "badmail@", "no_at_sign.com", "user@domain.org"]

for e in emails:
    print(validate_email(e))

Output

Example 3: Password strength check

Python

In [1]:

import re

def check_password(pwd):
    errors = []
    if len(pwd) < 8:
        errors.append("8+ characters chahiye")
    if not re.search(r"[A-Z]", pwd):
        errors.append("Ek uppercase letter chahiye")
    if not re.search(r"[a-z]", pwd):
        errors.append("Ek lowercase letter chahiye")
    if not re.search(r"\d", pwd):
        errors.append("Ek digit chahiye")
    if not re.search(r"[!@#$%^&*]", pwd):
        errors.append("Ek special character chahiye")
    if not errors:
        return "Strong password!"
    return "Weak: " + ", ".join(errors)

passwords = ["abc", "Password1", "Pass@1", "MyPass@123"]
for p in passwords:
    print(f"'{p}': {check_password(p)}")

Output

Quick Summary — RegEx ek nazar me

Function / Symbol	Kaam
re.search(pat, s)	Kahi bhi dhundho
re.match(pat, s)	Sirf shuru me dhundho
re.findall(pat, s)	Saare matches ki list
re.sub(pat, r, s)	Replace karo
re.split(pat, s)	Split karo
\d, \w, \s	Digit, Word, Whitespace
+, *, ?	1+, 0+, optional
^, $	Start, End
[], ()	Character set, Group

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