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15 Python Tips : How to Write Code Effectively

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 Here are some Python tips to keep in mind that will help you write clean, efficient, and bug-free code.     Python Tips for Effective Coding 1. Code Readability and PEP 8  Always aim for clean and readable code by following PEP 8 guidelines.  Use meaningful variable names, avoid excessively long lines (stick to 79 characters), and organize imports properly. 2. Use List Comprehensions List comprehensions are concise and often faster than regular for-loops. Example: squares = [x**2 for x in range(10)] instead of creating an empty list and appending each square value. 3. Take Advantage of Python’s Built-in Libraries  Libraries like itertools, collections, math, and datetime provide powerful functions and data structures that can simplify your code.   For example, collections.Counter can quickly count elements in a list, and itertools.chain can flatten nested lists. 4. Use enumerate Instead of Range     When you need both the index and the value in a loop, enumerate is a more Pyth

Data Analytics Key Role of NOSQL


Traditional database theory dictates that you design the data set before entering any data. A data lake, also called an enterprise data lake or enterprise data hub, turns that model on its head, says Chris Curran, principal and chief technologist in PricewaterhouseCoopers’ U.S. advisory practice. 

“It says we’ll take these data sources and dump them all into a big Hadoop repository, and we won’t try to design a data model beforehand,” he says. Instead, it provides tools for people to analyze the data, along with a high-level definition of what data exists in the lake. “People build the views into the data as they go along.

It’s a very incremental, organic model for building a large-scale database,” Curran says. On the downside, the people who use it must be highly skilled

Speed of NOSQL

Alternatives to traditional SQL-based relational databases, called NoSQL (short for “Not Only SQL”) databases, are rapidly gaining popularity as tools for use in specific kinds of analytic applications, and that momentum will continue to grow, says Curran.
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