How Can I Efficiently Process Large Text Files Line by Line Without Exceeding Memory Limits?

Reading Large Text Files Line by Line Efficiently: A Memory-Conscious Approach

The task at hand involves processing a sizable text file that exceeds 5GB without straining memory resources by loading its entire content at once. To achieve this, we can employ an alternative approach that allows line-by-line reading without excessive memory utilization.

Solution: Line-by-Line File Reading

Instead of using the readlines() function, which creates a large list in memory, we can iterate over the file object using a for loop. This approach avoids creating an in-memory representation of the entire file, allowing us to process it without consuming substantial amounts of memory.

Implementation Using Context Manager

For efficient resource management, it's recommended to use a context manager with open(). By wrapping the file object within a with statement, we ensure that the file is correctly closed after reading, even if an exception is raised during processing:

with open("log.txt") as infile:
    for line in infile:
        print(line)

This code snippet opens the "log.txt" file using a context manager. The for loop then iterates over the file line by line, and for each line, it performs the desired operation, such as printing it to the console.

Advantages of This Approach:

• Memory Efficiency: The line-by-line reading approach ensures that only the necessary portion of the file is loaded into memory at any given time, minimizing memory usage.
• Robustness: The use of a context manager handles file closing automatically, reducing the risk of resource leaks or data corruption.
• Scalability: This technique can handle large files without memory constraints, making it suitable for processing extensive datasets.

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