How to Read a CSV File from Amazon S3 Using Python (With Headers and Rows Displayed)

Regular expressions (regex) are powerful tools for pattern matching and text manipulation in Python. Here are five Python regex examples with explanations:
import re
text = "Hello, World!"
pattern = r"Hello"
result = re.search(pattern, text)
if result:
print("Pattern found:", result.group())
Output:
Output:
Pattern found: Hello
This example searches for the pattern "Hello" in the text and prints it when found.
import re
text = "The quick brown fox jumps over the lazy dog."
patterns = [r"fox", r"dog"]
for pattern in patterns:
if re.search(pattern, text):
print(f"Pattern '{pattern}' found.")
Output:
Pattern 'fox' found.
Pattern 'dog' found.
It searches for both "fox" and "dog" patterns in the text and prints when they are found.
import re
text = "The price of the product is $99.99."
pattern = r"\d+"
result = re.search(pattern, text)
if result:
print("Price:", result.group())
Output:
Price: 99
This example extracts digits (numbers) from the text.
import re
text = "Contact us at support@example.com or info@example.org."
pattern = r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,7}\b"
emails = re.findall(pattern, text)
for email in emails:
print("Email:", email)
Output:
Email: support@example.com
Email: info@example.org
It extracts email addresses from the text using a common email pattern.
import re
text = "Please visit our website at http://www.example.com."
pattern = r"http://www\.[A-Za-z]+\.[A-Za-z]+"
replacement = "https://www.example.com"
updated_text = re.sub(pattern, replacement, text)
print("Updated Text:", updated_text)
Output:
Updated Text: Please visit our website at https://www.example.com.
This example replaces a URL with a different URL in the text.
These are just a few examples of what you can do with regular expressions in Python. Regex is a versatile tool for text processing, and you can create complex patterns to match specific text structures or extract information from text data.
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