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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 ...

Exclusive Apache Kafka Top Features

Here are the top features of Kafka. It works on the principle of publishing messages. It routes real-time information to consumers far faster. Also, it connects heterogeneous applications by sending messages among them. Here the prime component (a.k.a message router) is a broker. The top features you can read here.


Kafka features


The exclusive Kafka features

The message broker provides seamless integration, but there are two collateral objectives: the first is to not block the producers and the second is to not let the producers know who the final consumers are.

Apache Kafka is a real-time publish-subscribe solution messaging system: open source, distributed, partitioned, replicated, commit-log based with a publish-subscribe schema. Its main characteristics are as follows:

1. Distributed. Cluster


Centric design that supports the distribution of the messages over the cluster members, maintaining the semantics. So you can grow the cluster horizontally without downtime.

2. Multiclient.


Easy integration with different clients from different platforms: Java, .NET, PHP, Ruby, Python, etc.

3. Persistent.


You cannot afford any data lost. Kafka is designed with efficient O(1), so data structures provide constant time performance no matter the data size.

4. Real time.


The messages produced are immediately seen by consumer threads; these are the basis of the systems called complex event processing (CEP).

5. Very high throughput.


As we mentioned, all the technologies in the stack are designed to work in commodity hardware. Kafka can handle hundreds of read and write operations per second from a large number of clients.


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