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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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The best solution Ceph Data Storage for big data

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#The best solution Ceph Data Storage for big data:
#The best solution Ceph Data Storage for big data:
The power of Ceph can transform your organization’s IT infrastructure and your ability to manage vast amounts of data. If your organization runs applications with different storage interface needs, Ceph is for you! Ceph’s foundation is the Reliable Autonomic Distributed Object Store (RADOS), which provides your applications with object, block, and file system storage in a single unified storage cluster—making Ceph flexible, highly reliable and easy for you to manage.

Ceph’s RADOS provides you with extraordinary data storage scalability—thousands of client hosts or KVMs accessing petabytes to exabytes of data. Each one of your applications can use the object, block or file system interfaces to the same RADOS cluster simultaneously, which means your Ceph storage system serves as a flexible foundation for all of your data storage needs. You can use Ceph for free, and deploy it on economical commodity hardware. Ceph is a better way to store data.

OBJECT-BASED STORAGE
Organizations prefer object-based storage when deploying large scale storage systems, because it stores data more efficiently. Object-based storage systems separate the object namespace from the underlying storage hardware—this simplifies data migration.

WHY IT MATTERS
By decoupling the namespace from the underlying hardware, object-based storage systems enable you to build much larger storage clusters. You can scale out object-based storage systems using economical commodity hardware, and you can replace hardware easily when it malfunctions or fails.

THE CEPH DIFFERENCE
Ceph’s CRUSH algorithm liberates storage clusters from the scalability and performance limitations imposed by centralized data table mapping. It replicates and re-balance data within the cluster dynamically—elminating this tedious task for administrators, while delivering high-performance and infinite scalability.

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