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Step-by-Step Guide to Reading Different Files in Python

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 In the world of data science, automation, and general programming, working with files is unavoidable. Whether you’re dealing with CSV reports, JSON APIs, Excel sheets, or text logs, Python provides rich and easy-to-use libraries for reading different file formats. In this guide, we’ll explore how to read different files in Python , with code examples and best practices. 1. Reading Text Files ( .txt ) Text files are the simplest form of files. Python’s built-in open() function handles them effortlessly. Example: # Open and read a text file with open ( "sample.txt" , "r" ) as file: content = file.read() print (content) Explanation: "r" mode means read . with open() automatically closes the file when done. Best Practice: Always use with to handle files to avoid memory leaks. 2. Reading CSV Files ( .csv ) CSV files are widely used for storing tabular data. Python has a built-in csv module and a powerful pandas library. Using cs...
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How to Read Kafka Logs Quickly

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In Kafka, the log file's function is to store entries. Here, you can find entries for the producer's incoming messages. You can call these topics. And, topics are divided into partitions.


How to Read Logs in Kafka

IN THIS PAGE

  1. Kafka Logs
  2. How Producer Messages Store
  3. Benefits of Kafka Logs
  4. How to check Logs in Kafka
How to Read Kafka Logs Quickly

1. Kafka Logs

  • The mechanism underlying Kafka is the log. Most software engineers are familiar with this. It tracks what an application is doing. 
  • If you have performance issues or errors in your application, the first place to check is the application logs. But it is a different sort of log. 
  • In the context of Kafka (or any other distributed system), a log is "an append-only, totally ordered sequence of records - ordered by time.

Kafka Basics [Video]





2. How Producer Messages Store

  • The producer writes the messages to Broker, and the records are stored in a log file. The records are stored as 0,1,2,3 and so on.
  • Each record will have one unique id.

4. Benefits of Kafka Logs

  • Logs are a simple data abstraction with powerful implications. If you have records in order with time, resolving conflicts, or determining which update to apply to different machines becomes straightforward.
  • Topics in Kafka are logs that are segregated by topic name. You could almost think of topics as labeled logs. If the log is replicated among a cluster of machines, and a single machine goes down, it’s easy to bring that server back up: just replay the log file. 
  • The ability to recover from failure is precisely the role of a distributed commit log.

5. How to Read Logs in Kafka

# The directory under which to store log files 

$  log.dir=/tmp/kafka8-logs 

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