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Python Regex: The 5 Exclusive Examples

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 Regular expressions (regex) are powerful tools for pattern matching and text manipulation in Python. Here are five Python regex examples with explanations: 01 Matching a Simple Pattern 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. 02 Matching Multiple Patterns 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. 03 Matching Any Digit   import re text = "The price of the
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What is IBM InfoSphere DataStage

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It integrates data across multiple systems using a high-performance parallel framework, and it supports extended metadata management and enterprise connectivity.

IBM InfoSphere

Powerful, scalable ETL platform—supports the collection, integration, and transformation of large volumes of data, with data structures ranging from simple to complex.
  • Support for big data and Hadoop—enables you to directly access big data on a distributed file system, and helps clients more efficiently leverage new data sources by providing JSON support and a new JDBC connector. 
  • Near real-time data integration—as well as connectivity between data sources and applications. 
  • Workload and business rules management—helps you optimize hardware utilization and prioritize mission-critical tasks. 
  • Ease of use—helps improve speed, flexibility, and effectiveness to build, deploy, update and manage your data integration infrastructure. 
  • Rich support for DB2Z and DB2 for z/OS—including data load optimization for DB2Z and balanced optimization for DB2 on z/OS 
  • Ref: IBM

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