- Python Text Processing - Home
- Python Text Processing - Introduction
- Python Text Processing - Environment
- Python Text Processing - String Immutability
- Python Text Processing - Sorting Lines
- Python Text Processing - Counting Token in Paragraphs
- Python Text Processing - Binary ASCII Conversion
- Python Text Processing - Strings as Files
- Python Text Processing - Backward File Reading
- Python Text Processing - Filter Duplicate Words
- Python Text Processing - Extract Emails from Text
- Python Text Processing - Extract URL from Text
- Python Text Processing - Pretty Print
- Python Text Processing - State Machine
- Python Text Processing - Capitalize and Translate
- Python Text Processing - Tokenization
- Python Text Processing - Remove Stopwords
- Python Text Processing - Synonyms and Antonyms
- Python Text Processing - Translation
- Python Text Processing - Word Replacement
- Python Text Processing - Spelling Check
- Python Text Processing - WordNet Interface
- Python Text Processing - Corpora Access
- Python Text Processing - Tagging Words
- Python Text Processing - Chunks and Chinks
- Python Text Processing - Chunk Classification
- Python Text Processing - Classification
- Python Text Processing - Bigrams
- Python Text Processing - Process PDF
- Python Text Processing - Process Word Document
- Python Text Processing - Reading RSS feed
- Python Text Processing - Sentiment Analysis
- Python Text Processing - Search and Match
- Python Text Processing - Text Munging
- Python Text Processing - Text wrapping
- Python Text Processing - Frequency Distribution
- Python Text Processing - Summarization
- Python Text Processing - Stemming Algorithms
- Python Text Processing - Constrained Search
Python Text Processing Useful Resources
Python Text Processing - Constrained Search
Many times, after we get the result of a search we need to search one level deeper into part of the existing search result. For example, in a given body of text we aim to get the web addresses and also extract the different parts of the web address like the protocol, domain name etc. In such scenario we need to take help of group function which is used to divide the search result into various groups bases on the regular expression assigned. We create such group expression by separating the main search result using parentheses around the searchable part excluding the fixed words we want match.
Example - Usage of Search
main.py
import re
text = "The web address is https://www.tutorialspoint.com"
# Taking "://" and "." to separate the groups
result = re.search('([\\w.-]+)://([\\w.-]+)\\.([\\w.-]+)', text)
if result :
print("The main web Address: ",result.group())
print("The protocol: ",result.group(1))
print("The doman name: ",result.group(2))
print("The TLD: ",result.group(3))
Output
When we run the above program, we get the following output −
The main web Address: https://www.tutorialspoint.com The protocol: https The doman name: www.tutorialspoint The TLD: com
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